Smart City Concepts
Architecture of Smart City Infrastructures
Peripheral processors
Data ingestion and mining
Reasoning and Deduction
Data Acting processors
SmartCity Project Coll@bora
SmartCity Project Sii-Mobility
Data Mining and smart City problematics
DISIT Smart City Ontology
Data ingestion and integration
Service Map and Linked Open Graph
Blog Vigilance via Natural Language Processing
Smart City at DISIT Lab, step two after smart city for beginnersPaolo Nesi
Smart City Concepts
Architecture of Smart City Infrastructures
Peripheral processors
Data ingestion and mining
Reasoning and Deduction
Data Acting processors
SmartCity Project Coll@bora
SmartCity Project Sii-Mobility
Data Mining and smart City problematic
DISIT Smart City Ontology
Data ingestion and integration
Service Map and Linked Open Graph
Blog Vigilance via Natural Language Processing
Mobile Emergency
Smart Health
Smart Education
Smart Mobility
Smart Energy
Smart Governmental
Smart economy
Smart people
Smart environment
Smart living
Smart Telecommunication
Overview on Smart City, DISIT lab solution for beginners, 2015, Part 7: Distr...Paolo Nesi
• Smart City Concepts
• Architecture of Smart City Infrastructures
• Peripheral processors
– Data collectors and Managers
– Blog Vigilance via Natural Language Processing
– Twitter vigilance
• Data ingestion and mining
– Data Mining and smart City problematic
– Km4City: Smart City Ontology
– RDF production, reconciliation
– Parallel and distributed processing
• Reasoning and Deduction
– Smart City Engine
– Decision Support System
• Data Acting processors
– Smart City Tools and API
– Service Map and Linked Open Graph
– Mobile applications
• Projects
– SmartCity Project Sii-Mobility SCN
– SmartCity Project Coll@bora SIN
– SmartCity Project RESOLUTE H2020
– Mobile Emergency
Monitoring Public Attention on Environment Issues with Twitter VigilancePaolo Nesi
DISIT Twitter Vigilance is an intelligent multi user tool for creating personal dashboards and study events and trends on Twitter that becomes a mining tool to "Twitter channels" contents. Each channel can be tuned to monitor one or more Search Queries on Twitter with a sophisticated and expressive syntax. Registered users of DISIT Twitter Vigilance tool and service are abled to:
• Create one or more channels (“canale”), as reported in the figure each channel can be tuned to monitor one or more Search Queries on Twitter with a sophisticated and expressive syntax. The simplest query can be the single keyword, tag or user.
• Create and activate multiple channels, that may use new or the same Search Queries;
• Provide public access to their channels analysis (as in the channels accessible without registration);
• Download data sets (trough API service ) for refined analysis;
• Full access at the channel history of User's content per channel, per search, per users, etc.;
• Perform visual view throughput graphs and to export them in different graphic format;
• Perform analyses at level of channel, search, users, tweets, retweets, etc.:
o trends of the Search Queries as reported in the above figure;
o distributions on population and activities of users;
o distributions about other tags/keywords;
o geographic distribution of twitters of single or multiple channels;
o distributions regarding tweet and re-tweets.
A number of research activities on these data area under development.
Km4City: Smart City Model and Tools for City Knowledge ExploitationPaolo Nesi
The proposed presentation is going to expose the integrated solutions around Km4City model which has been set up by the DISIT lab in Florence (http://www.disit.org/6056 ) and adopted in some EC and national smart city projects (Sii-Mobility Smart City MIUR project, RESOLUTE H2020, Km4City service and tools in place in the Florence Area, with many industrial partners as Thales, Swarco, ECM, etc.). The solution is based on Km4City model that is capable to model a large set of the above data kind and provides support for inference and reasoning, on time and space, on public and private data, on static and real time data. In more details, the solution developed is open and accessible for city providing models and tools for its adoption and exploitation, also enabling the full customization. It includes a set of tools:
• Service map: http://servicemap.disit.org is a tool for PA administrators and for developers. For the PA administrators provide access to several kinds of geospatial queries in Florence and in the whole Tuscany region, taking as a results static and real time data, geo-localized. The ServiceMap is also a tool for developers, which can be used to understand the usage of API to access at the Km4City services http://www.disit.org/6597 . The ServiceMap facility allows the visual creation of queries on the city, and may send to the connected user via email the SPARQL code of the visual queries performed, and in addition also a simple Query ID. The Query ID can be used to pose the query without writing it, from any Mobile and Web applications without the needs of learning complex ontological and SPARQL models;
• Linked Open Graph for browsing LOD RDF Stores model including the Km4City Smart City model in Florence and Tuscany and thus for learning how to formulate SPARQL queries http://LOG.disit.org. See for example a view of Florence http://log.disit.org/service/?graph=0f50fffc5bcfc205de5a19b606b61310
• Demonstrative mobile application exploiting ServiceMap API, also presented at the Florence Open Data Day and accessible as open source via: http://www.disit.org/6595 .
• Km4City ontology model and documentation [1], http://smartcity.linkeddata.es/, document http://www.disit.org/5606 , http://www.disit.org/km4city/schema/
• Parallel and distributed architecture based on ETL, scheduler, HBase, Hadoop, for massive big data ingestion (static, quasi static, and real time data), reconciliation, data enrichment (for connecting Km4City URI to dbPedia, geonames, etc. [3]) and for making decision: [1], slide http://www.disit.org/6566 with thousands of accesses on SlideShare. Several examples are accessible about the ETL transformation for data ingestion, quality improvement, conversion in triples, reconciliation in SILK, [1], etc. This engine is also adopted in other Smart City Projects as SMST national cluster.
CINI icitie workshop on smart city and communities, palermo, ottobre 2015
Big Data Smart City processes and tools, Real Time data processing toolsPaolo Nesi
Big Data Smart City Architecture
Smart-city Ontology
Data Ingestion and Mining
-Data Ingestion Manager
-DataSets already integrated
-Static Data: harvesting
-Data Quality Improvement
-Data mapping to Triples
Distributed and real time processes
-Distributed Scheduler
-Real Time Data Ingestion
-Blog Vigilance, NLP, Text Mining
-Parallel and distributed processing
RDF processing
-RDF Store Indexing
-RDF Store Validation
-Semantic Interoperability, reconciliation
-RDF Store Enrichment, for link discovering
-RDF Store Enrichment, for service discovering via web crawling
Smart City Engine
-Service Level Agreements
-Distributed SPARQL queries
-Decision Support System Processes
Development Interfaces
-Service map: http://servicemap.disit.org
service based on OpenStreetMaps that allows to search services available in a preset range from the selected bus stop.
-Linked Open Graph: http://log.disit.org
a tool developed to allow exploring semantic graph of the relation among the entities. It can be used to access to many different LOD repository.
-Ontology Documentation: http://www.disit.org/6507,
http://www.disit.org/5606, http://www.disit.org/6461
-Data Status Web pages: active
Visual Query Graph: under development
Sii-Mobility
Smart City and Open Data Projects and tools of DISIT LabPaolo Nesi
Current research topics
• Social media, collaborative work, Mobile computing, OpenData, LOD
• SmartCity, BigData, data analytics
• Railway signaling, autonomous driving systems, formal methods
• Cloud Computing, grid computing, smart cloud
• Data Mining, Knowledge Acceleration, natural language processing
Main research results
• Knowledge Management and Natural Language Processing: OSIM, CoSkoSAM
• Content and Protection Management, grid computing: AXMEDIS AXCP
• Social Media, recommendations and tool: ECLAP.eu, MyStoryPlayer, Social Graph, IPR Wizard…
• Mobile Computing: Mobile Medicine, Mobile Emergency, etc.….
• Music Transcode, winner of MIREX for piano
• Awards: IEEE ICECCS, DMS, Italia degli Innovatori, etc.
Main sources of funding
• European Commission: ECLAP (social media, Cultural Heritage, open data), AXMEDIS (DRM, protection, automation e grid computing), WEDELMUSIC, IMAESTRO, VARIAZIONI, IMUTUS, MUSICNETWORK, MOODS, MUPAAC, OFCOMP, etc. ……
• Italian Ministry: Smart Cities COLL@BORA (collaborative work, social media), FIRB e PRIN
• Regional: SACVAR (knowledge mining and reasoning), TRACE‐IT (Railway signalling), RAISSS (Railway signalling), ICARO (cloud)
• Fondations: MatchMaking (NLP), OSIM (Knowledge Acceleration, NLP)
DISIT Potential challenges and interests
DISIT is interested in participating in the next calls of the European Commission and in particular for:
• Working on open data and linked open data for smart city, smart cloud, smart manufacturing, smart museum, etc.
• Creating semantic models and reasoning engines
• Creating data mining and natural language processing tools as SACVAR/OSIM
• Working on defining big data solutions and infrastructures
• Working on data analytics algorithms computing:
• Predictions and trends,
• unexpected correlations,
• data inconsistencies and incompleteness,
• etc.
The Department of Information and Communication Technologies at Universitat Pompeu Fabra (DTIC-UPF) was created in 1999 to offer such a multidisciplinary environment. with the vision to become a leading European university department generating frontier research and advanced training at the crossroads created by the close interaction of excellent research in four key areas, namely computing, networking, cognitive sciences and biomedical sciences.
In terms of research, DTIC-UPF is the absolute leader in Spain in EU projects, including 9 prestigious ERC grants.
DTIC-UPF offers a comprehensive portfolio of 1-year research MSc’s in English, fully exploiting synergies among research lines:
- Cognitive Systems and Interactive Media (since 2007-08) offers an in-depth understanding of the design, construction and deployment of advanced autonomous artifacts, grounded in our understanding of biological, psychological and technological principles, by combining the lines in Synthetic Perceptive, Emotive and Cognitive Systems; Cognitive Media Technologies; Musical and Advanced Interaction; Interactive Technologies.
- Sound and Music Computing (since 2008-09) pushes this interdisciplinary field by combining basic engineering strengths in Signal Processing, Machine Learning and HCI with methodologies from other fields such as advanced interface design or cognitive science and psychology, reflecting the impact of ICT technologies in the music industry and research.
- Intelligent Interactive Systems (since 2012-13) trains in the design, analysis, and development of agents and robots that interact intelligently with humans and other agents; agents that can perceive, plan, act, learn, and communicate, by combining DTIC-UPF lines on Artificial Intelligence, Robotics, Machine Learning, Natural Language Interaction and Big Data, with electives including distributed systems and wireless networks.
The offer is being completed with MSc’s in Computer Vision (coordinated by UAB, started in 2013-14), Brain and Cognition (started in 2014-15) and Wireless Communications (jointly with UPC, starting in 2015-16).
Professional MSc are offered throught the UPF - Barcelona School of Management, including Animation, Creation of videogames, digital arts, ICT management and sonology.
Its international PhD program in ICT’s, unique in Spain in terms of its content, aims to provide a bridge between several disciplines,and has serves as a succesful program to boost the careers of alumni in research and industrial environment, including the creation of several start-ups.
Recent awards to PhD alumni include: the Cisco Security Grand Challenge 2014, Best Young European Researcher Award (Euroscience) 2013, MIT Technology Review Innovators under 35 for Spain 2014, the Vodafone Mobile for Good Awards 2013, The National Commendation for Invention - Japan Institute of Invention and Innovation 2013, BBVA Innova Challenge 2013 International Competition on Big Da
A Smart City Development kit for designing Web and Mobile AppsPaolo Nesi
Presentation of some of the Km4City development tools: ServiceMap and App Development Kit, ADK.
ServiceMap is focused on providing information to the developers, to help them learning how to access to the data model, to exploit and use the API
ADK is a drafted modular web and mobile application based on HTML5 and JavaScript (apache Cordova) that can be used to exploit Smart City API to develop a large range of applications.
It is modular, flexible, etc. and allow performing users behavior analysis.
The solutions are currently in use on several EC and national Projects such as: Sii-Mobility, RESOLUTE, REPLICATE, Weee, …
Cities aims at providing new Smart Services to city users:
operators, final users, etc.
In most cases via Web and Mobile Apps which exploit data:
Structural data, open data, real time data, etc., private data from companies
to be aggregated and transformed in services (providing: prediction, information, early warning, relations)
at reasonable cost for: developers, operators, and SME to realize new Apps and services.
If cost is not affordable, Services and Apps are not developed, in most cases the Apps are also provided for free, so that high costs are not sustainable Public Private Partnership
Scenarious vs SmartCity API
Search data: by text, near, along, etc...
Resolving text to GPS and formal city nodes model
Empowering the city users
Access to event information
Supporting City Users in using Public Mobility
Supporting City Users in using Private Mobility
New Experience to access at Cultural and Touristic info
New way to access at health services
Access at Environmental information
Profiled Suggestions to City Users
Personal Assistant
Sharing knowledge among cities
ServiceMap tool
with Km4City are substantially a Smart City Expert System, SCES
includes the Smart City API
is a for developers to: search and browse on Smart City Knowledge, also to generate examples of the Smart City API call to be used in the development of Web and Mobile Apps
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Smart City at DISIT Lab, step two after smart city for beginnersPaolo Nesi
Smart City Concepts
Architecture of Smart City Infrastructures
Peripheral processors
Data ingestion and mining
Reasoning and Deduction
Data Acting processors
SmartCity Project Coll@bora
SmartCity Project Sii-Mobility
Data Mining and smart City problematic
DISIT Smart City Ontology
Data ingestion and integration
Service Map and Linked Open Graph
Blog Vigilance via Natural Language Processing
Mobile Emergency
Smart Health
Smart Education
Smart Mobility
Smart Energy
Smart Governmental
Smart economy
Smart people
Smart environment
Smart living
Smart Telecommunication
Overview on Smart City, DISIT lab solution for beginners, 2015, Part 7: Distr...Paolo Nesi
• Smart City Concepts
• Architecture of Smart City Infrastructures
• Peripheral processors
– Data collectors and Managers
– Blog Vigilance via Natural Language Processing
– Twitter vigilance
• Data ingestion and mining
– Data Mining and smart City problematic
– Km4City: Smart City Ontology
– RDF production, reconciliation
– Parallel and distributed processing
• Reasoning and Deduction
– Smart City Engine
– Decision Support System
• Data Acting processors
– Smart City Tools and API
– Service Map and Linked Open Graph
– Mobile applications
• Projects
– SmartCity Project Sii-Mobility SCN
– SmartCity Project Coll@bora SIN
– SmartCity Project RESOLUTE H2020
– Mobile Emergency
Monitoring Public Attention on Environment Issues with Twitter VigilancePaolo Nesi
DISIT Twitter Vigilance is an intelligent multi user tool for creating personal dashboards and study events and trends on Twitter that becomes a mining tool to "Twitter channels" contents. Each channel can be tuned to monitor one or more Search Queries on Twitter with a sophisticated and expressive syntax. Registered users of DISIT Twitter Vigilance tool and service are abled to:
• Create one or more channels (“canale”), as reported in the figure each channel can be tuned to monitor one or more Search Queries on Twitter with a sophisticated and expressive syntax. The simplest query can be the single keyword, tag or user.
• Create and activate multiple channels, that may use new or the same Search Queries;
• Provide public access to their channels analysis (as in the channels accessible without registration);
• Download data sets (trough API service ) for refined analysis;
• Full access at the channel history of User's content per channel, per search, per users, etc.;
• Perform visual view throughput graphs and to export them in different graphic format;
• Perform analyses at level of channel, search, users, tweets, retweets, etc.:
o trends of the Search Queries as reported in the above figure;
o distributions on population and activities of users;
o distributions about other tags/keywords;
o geographic distribution of twitters of single or multiple channels;
o distributions regarding tweet and re-tweets.
A number of research activities on these data area under development.
Km4City: Smart City Model and Tools for City Knowledge ExploitationPaolo Nesi
The proposed presentation is going to expose the integrated solutions around Km4City model which has been set up by the DISIT lab in Florence (http://www.disit.org/6056 ) and adopted in some EC and national smart city projects (Sii-Mobility Smart City MIUR project, RESOLUTE H2020, Km4City service and tools in place in the Florence Area, with many industrial partners as Thales, Swarco, ECM, etc.). The solution is based on Km4City model that is capable to model a large set of the above data kind and provides support for inference and reasoning, on time and space, on public and private data, on static and real time data. In more details, the solution developed is open and accessible for city providing models and tools for its adoption and exploitation, also enabling the full customization. It includes a set of tools:
• Service map: http://servicemap.disit.org is a tool for PA administrators and for developers. For the PA administrators provide access to several kinds of geospatial queries in Florence and in the whole Tuscany region, taking as a results static and real time data, geo-localized. The ServiceMap is also a tool for developers, which can be used to understand the usage of API to access at the Km4City services http://www.disit.org/6597 . The ServiceMap facility allows the visual creation of queries on the city, and may send to the connected user via email the SPARQL code of the visual queries performed, and in addition also a simple Query ID. The Query ID can be used to pose the query without writing it, from any Mobile and Web applications without the needs of learning complex ontological and SPARQL models;
• Linked Open Graph for browsing LOD RDF Stores model including the Km4City Smart City model in Florence and Tuscany and thus for learning how to formulate SPARQL queries http://LOG.disit.org. See for example a view of Florence http://log.disit.org/service/?graph=0f50fffc5bcfc205de5a19b606b61310
• Demonstrative mobile application exploiting ServiceMap API, also presented at the Florence Open Data Day and accessible as open source via: http://www.disit.org/6595 .
• Km4City ontology model and documentation [1], http://smartcity.linkeddata.es/, document http://www.disit.org/5606 , http://www.disit.org/km4city/schema/
• Parallel and distributed architecture based on ETL, scheduler, HBase, Hadoop, for massive big data ingestion (static, quasi static, and real time data), reconciliation, data enrichment (for connecting Km4City URI to dbPedia, geonames, etc. [3]) and for making decision: [1], slide http://www.disit.org/6566 with thousands of accesses on SlideShare. Several examples are accessible about the ETL transformation for data ingestion, quality improvement, conversion in triples, reconciliation in SILK, [1], etc. This engine is also adopted in other Smart City Projects as SMST national cluster.
CINI icitie workshop on smart city and communities, palermo, ottobre 2015
Big Data Smart City processes and tools, Real Time data processing toolsPaolo Nesi
Big Data Smart City Architecture
Smart-city Ontology
Data Ingestion and Mining
-Data Ingestion Manager
-DataSets already integrated
-Static Data: harvesting
-Data Quality Improvement
-Data mapping to Triples
Distributed and real time processes
-Distributed Scheduler
-Real Time Data Ingestion
-Blog Vigilance, NLP, Text Mining
-Parallel and distributed processing
RDF processing
-RDF Store Indexing
-RDF Store Validation
-Semantic Interoperability, reconciliation
-RDF Store Enrichment, for link discovering
-RDF Store Enrichment, for service discovering via web crawling
Smart City Engine
-Service Level Agreements
-Distributed SPARQL queries
-Decision Support System Processes
Development Interfaces
-Service map: http://servicemap.disit.org
service based on OpenStreetMaps that allows to search services available in a preset range from the selected bus stop.
-Linked Open Graph: http://log.disit.org
a tool developed to allow exploring semantic graph of the relation among the entities. It can be used to access to many different LOD repository.
-Ontology Documentation: http://www.disit.org/6507,
http://www.disit.org/5606, http://www.disit.org/6461
-Data Status Web pages: active
Visual Query Graph: under development
Sii-Mobility
Smart City and Open Data Projects and tools of DISIT LabPaolo Nesi
Current research topics
• Social media, collaborative work, Mobile computing, OpenData, LOD
• SmartCity, BigData, data analytics
• Railway signaling, autonomous driving systems, formal methods
• Cloud Computing, grid computing, smart cloud
• Data Mining, Knowledge Acceleration, natural language processing
Main research results
• Knowledge Management and Natural Language Processing: OSIM, CoSkoSAM
• Content and Protection Management, grid computing: AXMEDIS AXCP
• Social Media, recommendations and tool: ECLAP.eu, MyStoryPlayer, Social Graph, IPR Wizard…
• Mobile Computing: Mobile Medicine, Mobile Emergency, etc.….
• Music Transcode, winner of MIREX for piano
• Awards: IEEE ICECCS, DMS, Italia degli Innovatori, etc.
Main sources of funding
• European Commission: ECLAP (social media, Cultural Heritage, open data), AXMEDIS (DRM, protection, automation e grid computing), WEDELMUSIC, IMAESTRO, VARIAZIONI, IMUTUS, MUSICNETWORK, MOODS, MUPAAC, OFCOMP, etc. ……
• Italian Ministry: Smart Cities COLL@BORA (collaborative work, social media), FIRB e PRIN
• Regional: SACVAR (knowledge mining and reasoning), TRACE‐IT (Railway signalling), RAISSS (Railway signalling), ICARO (cloud)
• Fondations: MatchMaking (NLP), OSIM (Knowledge Acceleration, NLP)
DISIT Potential challenges and interests
DISIT is interested in participating in the next calls of the European Commission and in particular for:
• Working on open data and linked open data for smart city, smart cloud, smart manufacturing, smart museum, etc.
• Creating semantic models and reasoning engines
• Creating data mining and natural language processing tools as SACVAR/OSIM
• Working on defining big data solutions and infrastructures
• Working on data analytics algorithms computing:
• Predictions and trends,
• unexpected correlations,
• data inconsistencies and incompleteness,
• etc.
The Department of Information and Communication Technologies at Universitat Pompeu Fabra (DTIC-UPF) was created in 1999 to offer such a multidisciplinary environment. with the vision to become a leading European university department generating frontier research and advanced training at the crossroads created by the close interaction of excellent research in four key areas, namely computing, networking, cognitive sciences and biomedical sciences.
In terms of research, DTIC-UPF is the absolute leader in Spain in EU projects, including 9 prestigious ERC grants.
DTIC-UPF offers a comprehensive portfolio of 1-year research MSc’s in English, fully exploiting synergies among research lines:
- Cognitive Systems and Interactive Media (since 2007-08) offers an in-depth understanding of the design, construction and deployment of advanced autonomous artifacts, grounded in our understanding of biological, psychological and technological principles, by combining the lines in Synthetic Perceptive, Emotive and Cognitive Systems; Cognitive Media Technologies; Musical and Advanced Interaction; Interactive Technologies.
- Sound and Music Computing (since 2008-09) pushes this interdisciplinary field by combining basic engineering strengths in Signal Processing, Machine Learning and HCI with methodologies from other fields such as advanced interface design or cognitive science and psychology, reflecting the impact of ICT technologies in the music industry and research.
- Intelligent Interactive Systems (since 2012-13) trains in the design, analysis, and development of agents and robots that interact intelligently with humans and other agents; agents that can perceive, plan, act, learn, and communicate, by combining DTIC-UPF lines on Artificial Intelligence, Robotics, Machine Learning, Natural Language Interaction and Big Data, with electives including distributed systems and wireless networks.
The offer is being completed with MSc’s in Computer Vision (coordinated by UAB, started in 2013-14), Brain and Cognition (started in 2014-15) and Wireless Communications (jointly with UPC, starting in 2015-16).
Professional MSc are offered throught the UPF - Barcelona School of Management, including Animation, Creation of videogames, digital arts, ICT management and sonology.
Its international PhD program in ICT’s, unique in Spain in terms of its content, aims to provide a bridge between several disciplines,and has serves as a succesful program to boost the careers of alumni in research and industrial environment, including the creation of several start-ups.
Recent awards to PhD alumni include: the Cisco Security Grand Challenge 2014, Best Young European Researcher Award (Euroscience) 2013, MIT Technology Review Innovators under 35 for Spain 2014, the Vodafone Mobile for Good Awards 2013, The National Commendation for Invention - Japan Institute of Invention and Innovation 2013, BBVA Innova Challenge 2013 International Competition on Big Da
A Smart City Development kit for designing Web and Mobile AppsPaolo Nesi
Presentation of some of the Km4City development tools: ServiceMap and App Development Kit, ADK.
ServiceMap is focused on providing information to the developers, to help them learning how to access to the data model, to exploit and use the API
ADK is a drafted modular web and mobile application based on HTML5 and JavaScript (apache Cordova) that can be used to exploit Smart City API to develop a large range of applications.
It is modular, flexible, etc. and allow performing users behavior analysis.
The solutions are currently in use on several EC and national Projects such as: Sii-Mobility, RESOLUTE, REPLICATE, Weee, …
Cities aims at providing new Smart Services to city users:
operators, final users, etc.
In most cases via Web and Mobile Apps which exploit data:
Structural data, open data, real time data, etc., private data from companies
to be aggregated and transformed in services (providing: prediction, information, early warning, relations)
at reasonable cost for: developers, operators, and SME to realize new Apps and services.
If cost is not affordable, Services and Apps are not developed, in most cases the Apps are also provided for free, so that high costs are not sustainable Public Private Partnership
Scenarious vs SmartCity API
Search data: by text, near, along, etc...
Resolving text to GPS and formal city nodes model
Empowering the city users
Access to event information
Supporting City Users in using Public Mobility
Supporting City Users in using Private Mobility
New Experience to access at Cultural and Touristic info
New way to access at health services
Access at Environmental information
Profiled Suggestions to City Users
Personal Assistant
Sharing knowledge among cities
ServiceMap tool
with Km4City are substantially a Smart City Expert System, SCES
includes the Smart City API
is a for developers to: search and browse on Smart City Knowledge, also to generate examples of the Smart City API call to be used in the development of Web and Mobile Apps
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Keynote: Making Smarter Tuscany and Florence with Km4CityPaolo Nesi
Keynote at International Summit on Smart World and Smart Cities, In Conjunction With 2017 IEEE Smart World Congress
August 5, 2017, San Francisco, USA
http://smart-city-conference.com/summit2017/
Sentient Urban Platform for Smart City
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: big data, users behavior and needs, ...
IOT, Open data sensors, private data, static and real time data.
City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
What is enabling and providing smart services
Smart Parking, in Tuscany
Smart First Aid in Tuscany
Smart Fuel pricing in Tuscany
Smart search for POI and public transport srv.
Public Transportation in Tuscany
Routing and multimodal in Tuscany
Social Media Monitoring and acting
Traffic events and Resilience in Florence
Bike Sharing in Pisa and Siena
Recharge stations for e-vehicles
Entertainment Events in Florence
Traffic Sensors in Tuscany
Weather forecast/condition in Tuscany
Pollution and Pollination in Tuscany
People Monitoring Assessment in the City, in Florence via WiFi
People Monitoring, in Tuscany via App
All Point of Interests, cultural activities, IOT, …
Over than 1.2 Million of complex events per day!
Twitter Vigilance: a Multi-User platform for Cross-Domain Twitter Data Analyt...Paolo Nesi
Citizens as sensors to
Assess sentiment on services, events, …
Response of consumers wrt…
Early detection of critical conditions
Information channel
Opinion leaders
Communities
Formation
Predicting volume of visitors for tuning the services
Collecting Tweets
on the basis of several criterial, searches
Multiple users may have multiple searches and multiple purposes (views on those searches) minimization of searches
With high reliable model exploiting Twitter Search and/or Stream API
Performing NLP and Sentiment Analysis
Real time or daily
Multiple languages
Compute Metrics:
different kinds, etc.: volume, users, etc..
Low and High Level,
Work on daily, hourly and real time
Downloading data: raw data and derived metrics
Providing support for drilling down on data
to perform inspection and analysis, faceted search for instance
perform data analytics
exploiting metrics on Machine Learning and predictive tools
Providing API for querying, dashboard
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Presentation at the Workshop on Expectations for AAL and enhanced living environments in 2025/2030, by Francisco Florez-Revuelta, Susanna Spinsante, and Nuno Garcia, all members of the Cost Action IC1303 - AAPELE - Algorithms, Architectures and Platforms for Enhanced Living Environments
DISIT: Competenze per Industria 4.0
Technical Areas:
Industrial Internet: integrazione di fabbrica, ..
Smart/Advanced manufacturing: mobility, delivering, optimization, etc.
(Smart City: mobility and transport, energy, IOT/IOE, analytics, …)
(Smart Retail: user behavior analysis, engagement, …)
Technologies:
Big Data and Analytics: data management, user analysis, user engagement, prediction, early detection, data intelligence, …
Data Mining: artificial intelligence, semantic computing, semantic reasoner, expert systems, statistic analysis, ..
IOT/IOE: internet of things/everything, brokers, microservices, ..
Cloud: smart cloud, cloud simulation, optimization, ..
Mobile Computing: mobile application, user behavior analysis, ..
NLP and Sentiment Analysis: response Vigilance, interaction, answering, ..
See projects on: http://www.disit.org/5501
Big Data analytics Aree Applicative
-Smart manufacturing
-Personal assistants
-Autonomous engine, semantic reasoners
-Experts systems
-Smart Cloud
-Services and microservices integration
-Industrie farmaceutiche
-Mobilità e Trasporti
-Turismo e Cultura
-Smart City, Innovation Lab
Servizi alla persona
Km4City: una soluzione aperta per erogare servizi Smart CityPaolo Nesi
Km4City: Integrated Urban Platform, Open Source
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
The DIGCOMP conceptual reference model (DIGCOMP 2.0) - April 2016Riina Vuorikari
Phase 1: Almost publishable version with comments from the consultation. Publication expected in the end of May - Phase2: 8 levels of learning outcomes in the end of 2016.
The DTIC hosts faculty and researchers in the field of Information and Communication Technologies, which groups the disciplines of Telecommunications and Computer Science. Through UPF's Polytechnic School (ESUP), the DTIC supports degrees in Telematics Engineering, Audiovisual Systems Engineering and Computer Science. At the postgraduate level, the DTIC offers several master's degrees and a full Ph.D. program. Some of these master programs are offered in cooperation with other UPF departments and research institutions.
The DTIC's research activities are organized around 15 groups pursuing a wide range of topics that include networking, wireless communications, multimedia, image and music processing, medical imaging, interactive technologies, artificial intelligence, data mining, and computational neuroscience, among others. The department participates extensively in National and European research programmes, and has active cooperation agreements with other prominent universities and corporations.
The DTIC is sited in UPF's Communication Campus, which was opened in 2009 and is located within the vibrant 22@ technological district of Barcelona. The campus features modern facilities for both research and teaching, in close proximity to other research institutions, industry, technology start-up clusters, and government agencies.
Surfing, creating and networking: Tampere City Library drives into the Inform...ePractice.eu
Author: Elina Harju
At the Tampere City Library we are hoping to be interpreters of the information society and to encourage adults to find new ways to express, share and understand through hands-on media education.
Integrating digital literacy and inquiry learningJune Wall
This session overviews 21st century learning, digital literacy and how these are place within an inquiry learning process. It presents an approach for teachers to consider as one way to embed digital literacy in an inquiry classroom.
Innovation at the Age of Future Government. This was presented during a seminar at the UAE University. The presentation highlights important concepts about creativity and innovation, how to develop the creative skills, and discusses the characteristics of the creative personality. Also, it highlights the relationship between excellence and innovation and provide extensive examples of innovation in the UAE Government.
Furthermore, it provides coverage of the types and tools used for innovation.
Keynote: Making Smarter Tuscany and Florence with Km4CityPaolo Nesi
Keynote at International Summit on Smart World and Smart Cities, In Conjunction With 2017 IEEE Smart World Congress
August 5, 2017, San Francisco, USA
http://smart-city-conference.com/summit2017/
Sentient Urban Platform for Smart City
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: big data, users behavior and needs, ...
IOT, Open data sensors, private data, static and real time data.
City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
What is enabling and providing smart services
Smart Parking, in Tuscany
Smart First Aid in Tuscany
Smart Fuel pricing in Tuscany
Smart search for POI and public transport srv.
Public Transportation in Tuscany
Routing and multimodal in Tuscany
Social Media Monitoring and acting
Traffic events and Resilience in Florence
Bike Sharing in Pisa and Siena
Recharge stations for e-vehicles
Entertainment Events in Florence
Traffic Sensors in Tuscany
Weather forecast/condition in Tuscany
Pollution and Pollination in Tuscany
People Monitoring Assessment in the City, in Florence via WiFi
People Monitoring, in Tuscany via App
All Point of Interests, cultural activities, IOT, …
Over than 1.2 Million of complex events per day!
Twitter Vigilance: a Multi-User platform for Cross-Domain Twitter Data Analyt...Paolo Nesi
Citizens as sensors to
Assess sentiment on services, events, …
Response of consumers wrt…
Early detection of critical conditions
Information channel
Opinion leaders
Communities
Formation
Predicting volume of visitors for tuning the services
Collecting Tweets
on the basis of several criterial, searches
Multiple users may have multiple searches and multiple purposes (views on those searches) minimization of searches
With high reliable model exploiting Twitter Search and/or Stream API
Performing NLP and Sentiment Analysis
Real time or daily
Multiple languages
Compute Metrics:
different kinds, etc.: volume, users, etc..
Low and High Level,
Work on daily, hourly and real time
Downloading data: raw data and derived metrics
Providing support for drilling down on data
to perform inspection and analysis, faceted search for instance
perform data analytics
exploiting metrics on Machine Learning and predictive tools
Providing API for querying, dashboard
The IEEE Smart World Congress originated from the 2005 Workshop on Ubiquitous Smart Worlds (USW, Taipei) and the 2005 Symposium on Ubiquitous Intelligence and Smart World (UISW, Nagasaki). SmartWorld 2017 in San Francisco is the next edition after the successful SmartWorld 2016 in Toulouse France and SmartWorld 2015 in Beijing China. SmartWorld 2017 is to provide a high-profile, leading-edge platform for researchers and engineers to exchange and explore state-of-art advances and innovations in graceful integrations of Cyber, Physical, Social, and Thinking Worlds for the theme
http://ieee-smartworld.org/2017/smartworld/
Presentation at the Workshop on Expectations for AAL and enhanced living environments in 2025/2030, by Francisco Florez-Revuelta, Susanna Spinsante, and Nuno Garcia, all members of the Cost Action IC1303 - AAPELE - Algorithms, Architectures and Platforms for Enhanced Living Environments
DISIT: Competenze per Industria 4.0
Technical Areas:
Industrial Internet: integrazione di fabbrica, ..
Smart/Advanced manufacturing: mobility, delivering, optimization, etc.
(Smart City: mobility and transport, energy, IOT/IOE, analytics, …)
(Smart Retail: user behavior analysis, engagement, …)
Technologies:
Big Data and Analytics: data management, user analysis, user engagement, prediction, early detection, data intelligence, …
Data Mining: artificial intelligence, semantic computing, semantic reasoner, expert systems, statistic analysis, ..
IOT/IOE: internet of things/everything, brokers, microservices, ..
Cloud: smart cloud, cloud simulation, optimization, ..
Mobile Computing: mobile application, user behavior analysis, ..
NLP and Sentiment Analysis: response Vigilance, interaction, answering, ..
See projects on: http://www.disit.org/5501
Big Data analytics Aree Applicative
-Smart manufacturing
-Personal assistants
-Autonomous engine, semantic reasoners
-Experts systems
-Smart Cloud
-Services and microservices integration
-Industrie farmaceutiche
-Mobilità e Trasporti
-Turismo e Cultura
-Smart City, Innovation Lab
Servizi alla persona
Km4City: una soluzione aperta per erogare servizi Smart CityPaolo Nesi
Km4City: Integrated Urban Platform, Open Source
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
The DIGCOMP conceptual reference model (DIGCOMP 2.0) - April 2016Riina Vuorikari
Phase 1: Almost publishable version with comments from the consultation. Publication expected in the end of May - Phase2: 8 levels of learning outcomes in the end of 2016.
The DTIC hosts faculty and researchers in the field of Information and Communication Technologies, which groups the disciplines of Telecommunications and Computer Science. Through UPF's Polytechnic School (ESUP), the DTIC supports degrees in Telematics Engineering, Audiovisual Systems Engineering and Computer Science. At the postgraduate level, the DTIC offers several master's degrees and a full Ph.D. program. Some of these master programs are offered in cooperation with other UPF departments and research institutions.
The DTIC's research activities are organized around 15 groups pursuing a wide range of topics that include networking, wireless communications, multimedia, image and music processing, medical imaging, interactive technologies, artificial intelligence, data mining, and computational neuroscience, among others. The department participates extensively in National and European research programmes, and has active cooperation agreements with other prominent universities and corporations.
The DTIC is sited in UPF's Communication Campus, which was opened in 2009 and is located within the vibrant 22@ technological district of Barcelona. The campus features modern facilities for both research and teaching, in close proximity to other research institutions, industry, technology start-up clusters, and government agencies.
Surfing, creating and networking: Tampere City Library drives into the Inform...ePractice.eu
Author: Elina Harju
At the Tampere City Library we are hoping to be interpreters of the information society and to encourage adults to find new ways to express, share and understand through hands-on media education.
Integrating digital literacy and inquiry learningJune Wall
This session overviews 21st century learning, digital literacy and how these are place within an inquiry learning process. It presents an approach for teachers to consider as one way to embed digital literacy in an inquiry classroom.
Innovation at the Age of Future Government. This was presented during a seminar at the UAE University. The presentation highlights important concepts about creativity and innovation, how to develop the creative skills, and discusses the characteristics of the creative personality. Also, it highlights the relationship between excellence and innovation and provide extensive examples of innovation in the UAE Government.
Furthermore, it provides coverage of the types and tools used for innovation.
Digital diplomacy empowering 21 century diplomat in the conduct of diplomacySaeed Al Dhaheri
This was a lecture presented at the Emirates Diplomatic Academy on the 8th of May 2016. The presentation highlights the practice of digital diplomacy today and provides examples from leading MFAs in the practice of digital diplomacy. It also highlights the skills needed by the 21st century diplomats to practice digital diplomacy and the risks and challenges facing MFAs in this area.
This presentation was conducted during a panel discussion organized by the Dubai Government Excellence Program DGEP on how to achieve agile government. The presentation covers the agile principles and how to apply them outside software projects to include government service delivery and achieve an agile and lean organization.
How UAE is driving smart sustainable cities: key achievements and future cons...Saeed Al Dhaheri
This presentation was delivered during the Schneider Electric Power to the cloud 2016 event in April in Dubai. The presentation highlights the role of UAE in leading and driving smart sustainable cities locally and globally. Also provides insights into achievements of Dubai Smart cities program and what other cities in UAE is doing to transform into smart cities.
Finally, provides considerations for how to successfully transform into a smart city
Overcoming the cybersecurity challenges of smart citiesSaeed Al Dhaheri
This presentation was presented during the "Towards Dubai 2020 Smart City Conference held at the University of Dubai on 15th January 2017. The presentation highlights the importance of cybersecurity strategic planning for smart cities and discuss the Cybersecurity challenges facing smart cities initiatives and solutions.
DISIT lab Overview on Tourism and Training, June 2014Paolo Nesi
Semantic Model and Tools
• OSIM, knowledge mining, competence management
• RDF stores, Open Data, Linked Open Data management
• Content Tools
• Content modeling, indexing and querying, recommendations
• Content management and distribution
• Intellectual property management and conditional access (enabling
and actuating legal control)
• Devices:
• iOS Apple, Android, Windows Phone, Smart TV
• Tourism
• Open Data and Smart City data
• Training E‐learning
• Tools for e‐learning/distance/blended learning, anywhere learning,
certified e‐learning, social learning and networking
KM4city, Il Valore degli #OpenData: Esperienze a confrontoPaolo Nesi
le città si stanno adeguando alle crescenti necessità cercando di: garantire elevati livelli di qualità della vita, fornire nuovi servizi; limitando i costi, aumento di efficienza; allestire strutture decisionali adeguate; facilitare la creazione di nuovi servizi anche da parte di terzi:
-Pubblicazione Open Data
-Creare i presupposti per un mercato dei dati anche privati ma connessi agli -OpenData
->per una la crescita sostenibile da vari punti di vista
I dati, statici e real time sono stati resi interoperabili tramite algoritmi di data mining che possono essere applicati anche alle vostre problematiche
I dati aggregati ora sono accessibili in modo semplice tramite degli strumenti di sviluppo ed accesso che permettono di abbattere I costi di sviluppo delle applicazioni web e mobili
Service Map:http://servicemap.disit.org
Permette allo sviluppatore di realizzare delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
La selezione effettuata può essere richiamata e anche inserita in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive, la complessità sta sul server e non sulle App !!
LOG: http://log.disit.org
Permette allo sviluppatore di navigare nelle strutture complesse di uno o più database RDF accessibili per formulare dei grafici e delle query in modo visuale e farsi mandare il codice di richiesta tramite email.
Questo codice può essere utilizzato in App mobili e web per semplificare la programmazione e realizzare app che non devono essere manutenute quanto il server cambia…
Il grafo puo’ essere richiamato e anche inserito in pagine web di terzi, l’applicazione web è già pronta.
Manteniamo le App Vive !!
Smart City Strategic Forecast, SmartCity360, BratislavaPaolo Nesi
Smart City strategy, city smartening, big data amanagement,
-Taking into account results of participatory actions
-Smart city strategic plan, city agenda: prioritizing interventions
-Agreements for collaborations with main actors:
main research centers, main City Operators, etc.
-Direct collaborations on specific projects on:
ICT, Mobility, Culture, Energy, etc.
Experimenting on specific projects of the Smart City Strategic Plan
-Needs of harmonizing results and aggregating data towards dashboards
Basi di dati, SQL
Casi: Analisi della struttura di documenti
Intelligenza Artificiale
Apprendimento, clustering, alberi decisionali
Web crawling, XML, analisi dei testo
Casi di studio: OSIM
Reasoning and inferential
Big data introduction: NoSQL, graph database, ..
Social Media: user profiling, recommendations
Caso di Studio: Twitter Vigilance, sentiment analysis
Architetture parallele
Casi di studio: smart city
Casi di studio: Smart Cloud
Knowledge mining and Semantic Models: from Cloud to Smart CityPaolo Nesi
Course for the Doctorate in Information Technologies, DIST, at DINFO UNIFI
Pierfrancesco Bellini, Paolo Nesi, DISIT Lab
Dipartimento di Ingegneria dell’Informazione, DINFO
Università degli Studi di Firenze,Via S. Marta 3, 50139, Firenze, Italy
Tel: +39-055-2758511, fax: +39-055-2758570
http://www.disit.dinfo.unifi.it alias http://www.disit.org
Pierfrancesco.bellini@unifi.it , Paolo.nesi@unifi.it
.
program:
From RDF to OWL
Knowledge engineering for Beginners
Smart Cloud Application (ICARO Case)
Big Data Smart City Architecture
Smart-city Ontology
Data Ingestion and Mining
Distributed and real time processes
RDF processing
Smart City Engine
Development Interfaces
Sii-Mobility
The data!
Services from Data via Smart City API
IOT Applications and IOT
Personal Data vs Open
Big Data Analytics
App as data collection and User Engagement
Social Media Analysis
Visual Analytics and Dashboards
The Living Lab Approach
DISIT Lab overview: smart city, big data, semantic computing, cloudPaolo Nesi
Smart City
• Projects: http://www.disit.org/5501
– Sii-Mobility, http://www.sii-mobility.org
– Service Map: http://servicemap.disit.org
– Social Innovation: Coll@bora http://www.disit.org/5479
– Navigation Indoor/outdoor: Mobile Emergency http://www.disit.org/5404
– Mobility and Transport: TRACE-IT, RAISSS, TESYSRAIL
• Tools: http://www.disit.org/5489
– Data gathering, data mining and reconciliation
– Data reasoning, deduction, prediction
– Smart city ontology and reasoning tools
– Service analysis and recommendations
– Autonomous train operator, train signaling
– Risk analysis, decision support systems
– Mobile Applications
Data Analytics - Big data
• Projects: http://www.disit.org/5501
– Linked Open Graph: http://LOG.disit.org
– Sii-Mobility, http://www.sii-mobility.org
– Service on a number of projects
• Tools: http://www.disit.org/5489
– Open data and Linked Open Data
– LOG LOD service and tools
– Data mining and reconciliation
– Data reasoning, deduction, prediction, decision support
– SN Analysis and recommendations
– User behavior monitoring and analysis
Smart Cloud - Computing
• Projects: http://www.disit.org/5501
– ICARO: http://www.disit.org/5482
– Cloud ontology: http://www.disit.org/5604
– Cloud simulator:
– Smart Cloud: http://www.disit.org/6544
• Tools: http://www.disit.org/5489
– Cloud Monitoring
– Smart Cloud Engine and reasoner,
– Service Level Analyzer and control
– Configuration analysis and checker
– Cloud Simulation
Text and Web Mining
• Projects: http://www.disit.org/5501
– OSIM: http://www.disit.org/5482
– SACVAR: http://www.disit.org/5604
– Blog/Twitter Vigilance
• Tools: http://www.disit.org/5489
– Text and web mining, Natural Language Processing
– Service localization
– Web Crawling
– Competence analysis
– Blog Vigiliance, sentiment analysis
Social Media and e-Learning
• Projects: http://www.disit.org/5501
– ECLAP, http://www.eclap.eu
– ApreToscana: http://www.apretoscana.org
– Others: AXMEDIS, VARIAZIONI, SMNET, etc.
– Samsung Smart TV: http://www.disit.org/6534
• Tools: http://www.disit.org/5489
– XLMS, Cross Media Learning System
– IPR and content protection and distribution
– Mobile and SmartTv Applications
– Suggestions and recommendations
– Matchmaking solutions
– Media Tools for cross media content
Mobile Computing
• Projects:
– ECLAP: http://www.eclap.eu
– Mobile Medicine: http://mobmed.axmedis.org
– Mobile Emergency: http://www.disit.org/5500
– Smart City, FODD 2015: http://www.disit.org/6593
– Resolute: Mobiles as sensors
• Tools and support:
– Content distribution: e-learning
– Integrated Indoor/outdoor navigation
– User networking and collaboration
– Service localization
– Smart city and services
– OS: iOS, Android, Windows Phone, etc.
– Tech: IOT, iBeacoms, NFC, QR, ….
Technologies for Enhancing Knowledge and Training, the future of e-learning t...Paolo Nesi
E-learning infrastructure
Tools for e-learning/distance learning
References
Support for blended learning
Distance testing and assessment
Advanced aspects with respect to Moodle, Atutor, etc.
Content production and development
Content management and distribution
anywhere learning
certified e-learning
social learning and networking
Knowledge management
Legal, Intellectual property management and conditional access (enabling and actuating legal control)
Scalability: Hardware/Software
ECLAP: life long learning, social learning
http://www.eclap.eu
FirstClass: certified blended learning, paid courses
http://fad.fclass.it
IUF.Csavri: blended learning for entrepreneurs incubation and spin-offs
http://iuf.csavri.org
APRETOSCANA: formation for researchers
http://www.apretoscana.org
DISIT.DINFO.UNIFI.IT: research management and dissemination
http://www.disit.dinfo.uinifi.it
OSIM.UNIFI: knowledge management for UNIFI
http://openmind.disit.org
RESOLUTE: Resilience management guidelines and Operationalization applied to ...Paolo Nesi
--Conducting a systematic review and assessment of the state of the art of the Resilience assessment and Management concepts, national guidelines and their implementation strategies in order to develop a conceptual framework for resilience within Urban Transport Systems
--Development of European Resilience Management Guidelines (ERMG)
--Operationalize and validate the ERMG by implementing the RESOLUTE Collaborative Resilience Assessment and Management Support System (CRAMSS) for Urban Transport System (UTS) addressing Roads and Rails Infrastructures
--Enhancing resilience through improved support to human decision making processes, particularly through increased focus on the training of final users (first responders, civil protections, infrastructure managers) and population on ERMG and RESOLUTE system
--ERMG wide dissemination, acceptance and adoption at EU and Associated Countries level
DRS-7-2015 - RIA – start 1/5/2015 - end 30/4/2018 Budget 3.8M
Ontology Building vs Data Harvesting and Cleaning for Smart-city ServicesPaolo Nesi
Presently, a very large number of public and private data sets are available around the local governments. In most cases, they are not semantically interoperable and a huge human effort is needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity and reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to smart-city ontology and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users. The paper presents the process adopted to produce the ontology and the knowledge base and the mechanisms adopted for the verification, reconciliation and validation. Some examples about the possible usage of the coherent knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection. Keywords Smart city, knowledge base construction, reconciliation, validation and verification of knowledge base, smart city ontology, linked open graph.
DAI DATI INTELLIGENTI AI SERVIZI Smart City API HackathonPaolo Nesi
DAI DATI INTELLIGENTI AI SERVIZI
Smart City API Hackathon
Premi per 14.000 euro
Data: 7 e 8 aprile 2017
Luogo: Scuola di Ingegneria, Università degli Studi di Firenze
Il progetto Sii-Mobility, Smart City nazionale (MIUR), organizza il primo hackathon per promuovere lo sviluppo di applicazioni fisse e mobili sulla base delle http://www.disit.org/6991che si basano sul modello http://www.km4city.org .
Scopo dell'evento di hackathon è identificare nuove applicazioni che possano essere sviluppate sulla base di dati ed elaborazioni messi disposizione dalle smart city API di Sii-Mobility. I Dati sono in tutta la toscana e come dagli scenari http://www.disit.org/6995, sono relativi alla mobilità pubblica e privata, alla partecipazione, alle informazioni geolocalizzate dei punti di interesse, della salute, ambiente, e servizi di suggerimento e di coinvolgimento e assistenza.
Le tematiche affrontate dalle App proposte dovranno essere relative ad aspetti di mobilità, e in particolare ai seguenti 5 temi: Trasporto pubblico; Coinvolgimento dei cittadini, mobilità e turismo, mobilità e servizi, giochi in mobilità.
http://www.sii-mobility.org/index.php/eventi/hackathon-sii-mobility/registrati-all-evento-del-7-mattina
Documentazione e informazioni dalla pagina: http://www.sii-mobility.org/
Scadenza sottomissione delle proposte: 31 marzo 2017.
Premi per 14.000 euro, #hackathon #smartcity API, #bigdata #opendata della #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
#hackathon #smartcity #bigdata #opendata #Toscanadigitale #firenze #pisa #arezzo #direfare #forumpa
Smart City API, 14.000 euro di premi, Hackathon
Open Urban Platform for Smart City: Technical View Paolo Nesi
Km4City Roadmap
Data and Model
Control Room
Monitoring Traffic Flow and Parking
Monitoring City Users via Wi-Fi
Engaging Users Via Mobile App
Development Tools
Who is using it
City Resilience and DSS
Info and Documents
Open Urban Platform: Technical View 2018: Km4CityPaolo Nesi
Aggregate & integrate data
Multiple protocols from urban operators, ....
open data, IOT, sensors, internet of everything, cloud, mobile devices, Wi-Fi, social media, ...
Data Exploitation performing
predictions, reasoning, business intelligence, ..
users behavior analysis, decision support system, ..
Control Room, Real Time Monitoring tools, ….
Produce value from data enabling to
Stimulate virtuous behavior, influence City Users!
Put in action CITY Strategies
Km4City: Smart City Ontology Building for Effective Erogation of ServicesPaolo Nesi
Provides a unique point of service with integrated and aggregated data and tools for
-- Qualified users: public administrations à developers
-- Operators: mobility, energy, SME, shops, ….. à developers
-- Final users à citizens, students, pendular, tourists
Problems:
--Aggregated Data are not available:
not semantically interoperable, heterogeneous for: format, vocabulary, structure, velocity, volume, ownership/control, access / license, …
---As OD, LD, LOD, private data, ..
---Lack of Services and tools to make the adoption simple
Final Users tools:
--Km4City mobile app with personal assistant is coming…
--Km4City mobile applications: Google Play, Apple Store, …
--Km4City web application: http://www.km4city.org
--Open Source Mobile Application, FODD: an example in open source http://www.disit.org/6595
Public administrator tools:
--Smart decision support system, http://smartds.disit.org
--Developers http://www.disit.org/km4city tools:
--Service Map Server, plus API, http://servicemap.disit.org
--LOG LOD browser: an ultimate visual tool to browse the RDF Store.
--Ontology Documentation: an ultimate tool to understand,
if needed !!
The dirty work of Km4City service
--Data Ingestion Manager, DIM
--RDF Indexer Manager, RIM
--RDF Store Methodology
--RDF store enricher with dbPedia
--Distributed SCE Scheduler, DISCES
--SCE: Smart City Engine
--Doc and info on http://www.disit.org/km4city
Open Data Day 2016, Km4City, L’universita’ come aggregatore di Open Data del ...Paolo Nesi
Open Data Day, UNIMORE, Modena, 5 Marzo 2016.
Aggregazione dati, experienza di Firenze,
Smart City, Km4City,
Smart Decision Support,
Data Ingestion manager,
Data aggregation,
User profiling on demand.
Mobilità: inter-modalità, bigliettazione integrata, sostenibile, scambiatori, sfruttamento stazioni, etc.,
Servizi: gov ..SUAP, edu, turismo, beni culturali, salute, etc.,
Energia: risparmio energetico, riduzione amissioni, inquinamento, etc.,
Ambiente: qualità dell’aria, fiumi, meteo, rifiuti, etc.,
… commercio, industria, etc.
... Infrastrutture critiche. resilienza
Collezionamento dati statici, quasi statici e real time, stream
Dati open: geo localizzati, servizi, statistiche, censimenti, etc.
Dati privati degli operatori: con licenze limitate per non permettere di fare profitto ad altri operatori sulla base dei loro dati
Dati personali delle persone: profili, comportamenti tramite APP, IOT, sensori, web, etc.
Integrazione dati per renderli semanticamente interoperabili, ed operare deduzioni (time, space… )
I tradizionali collettori di open data danno visioni statistiche ma non sono adatti a produrre servizi integrati
Integrazione con modelli semantici unificanti come Km4City
Control Room delle Città Metropolitane devono:
arrivare a supervisionare domini multipli e le interdipendenze fra mobilità, energia, comunicazione, servizi, flussi traffico, flussi pedonali, turismo, etc.
Migliorare la loro Resilienza, capacità di reazione ed assorbimento
ridurre i costi sociali della mobilità per le persone
consentendo minori disagi, maggiore efficienza,
maggiore sensibilità verso le necessità del cittadino,
minori emissioni, migliori condizioni ambientali;
percorsi info-formativi in modo che il cittadino cambi le abitudini non virtuose;
ridurre i costi di trasporto ed i tempi di percorrenza per gli utenti, per i gestori e le amministrazioni, tramite soluzioni di ottimizzazione.
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• Snap4City Architecture, roadmap, logos, innovations
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• Dashboards production
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• Snap4City Living Lab for Collaborative Work
• Development Life Cycle
• Development tools
• Data protection, personal da vs GDPR
• Snap4City and Km4City Projects
• Acknowledgment
Km4City: Smart City HowTo and Overview, 2016Paolo Nesi
Km4City storia e roadmap
Dati e Modello
Development Tools
App: Web e Mobile
Mobile reasoning and Monitoring
Monitoring via Wi-Fi
Control Room
Twitter Vigilance
Progetti Connessi
Set up an ICT based Urban Platform integrated and unified data management among services, city operators and city users:
Control Room, Real Time Monitoring
decision support, assessing and monitoring risk and resilience
Data analytics and business intelligence
predictions, reasoning, city users behavior analysis, ….
Reading the city: data, users behavior and needs, ...
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City Strategies: stimulate virtuous behavior of City Users
participation, totem, twitter, Apps, etc.
Transform Data into value
Put in action smart city innovative solutions and services, development tools
Smart Cloud Engine and Solution based on Knowledge BasePaolo Nesi
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Overview on Smart City: Smart City for Beginners
1. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
1
Overview on Smart City
Smart City for Beginners
2014, Part 9, Corso di Sistemi Distribuiti
Scuola di Ingegneria di Firenze
Prof. Paolo Nesi
DISIT Lab
Dipartimento di Ingegneria dell’Informazione
Università degli Studi di Firenze
Via S. Marta 3, 50139, Firenze, Italia
tel: +39-055-4796523, fax: +39-055-4796363
http://www.disit.dinfo.unifi.it
paolo.nesi@unifi.it
DISIT Lab, Univ. Florence, 2014
2. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 2
3. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Motivations
• Societal challenge
– We see a strong increment of population of our
cities, since in the cities the life is simple and of
higher quality in term of services and working
opportunities
– The cities needs to be adapted to the increment of
population, to new evolving ages, to the new
technologies and expectations of population
• Sustainability of the growth
DISIT Lab, Univ. Florence, 2014 3
4. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 4
5. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 5
6. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 6
7. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 7
8. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Sustainability of the Growth
• To be planned and managed with respect to increment of
population and their needs
– increment of efficiency:
• compensation of the increments of costs
– Increment of quality of life:
• compensation of the decrement of quality of life
– provisioning of new services:
• compensation of the inadequacy of services
– Decision support for strategic aspects
• Corrections, prediction, new services, etc.
• Towards citizens
– Informing citizens on the new adaptations, making them
aware about that
– Forming citizens to adopt virtuous behaviour in the usage of
services and resources DISIT Lab, Univ. Florence, 2014 8
9. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smartness, smart city needs 6 features
• Smart Health
• Smart Education
• Smart Mobility
• Smart Energy
• Smart Governmental
– Smart economy
– Smart people
– Smart environment
– Smart living
• Smart Telecommunication
DISIT Lab, Univ. Florence, 2014 9
10. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart health
(can be regarded as smart governmental)
• Online accessing to health services:
– booking and paying
– selecting doctor
– access to EPR (Electronic Patient Record)
• Monitoring services and users for,
– learn people behavior, create collective
profiles
– personalized health
– Inform citizens to the risks of their habits
– Improve efficiency of services
– redistribute workload, thus reducing the
peak of consumption
DISIT Lab, Univ. Florence, 2014 10
11. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Education
(can be regarded as smart governmental)
• Diffusion of ICT into the schools:
– LIM, PAD, internet connection, tables, ..
• Primary and secondary schools university
industry & services
• Monitoring the students and quality of
service,
– learn student behavior, create collective profiles,
– personalized education
• suggesting behavior to
– Informing the families
– moderate the peak of consumption
– increase the competence in specific needed
sectors, etc.
– Increase formation impact and benefits
DISIT Lab, Univ. Florence, 2014 11
12. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Mobility
• Public transportation:
– bus, railway, taxi, metro, etc.,
• Public transport for services:
– garbage collection, ambulances,
• Private transportation:
– cars, delivering material, etc.
• New solutions (public and/or
private):
– electric cars, car sharing, car
pooling, bike sharing, bicycle paths
• Online:
– ticketing, monitoring travel,
infomobility, access to RTZ, parking,
etc.
DISIT Lab, Univ. Florence, 2014 12
13. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Mobility and urbanization
• Monitoring the city status,
– learn city behavior on mobility
– learn people behavior
– create collective profiles
– tracking people flows
• Providing Info/service
– personalized
– Info about city status to
– help moving people and
material
– education on mobility,
– moderate the peak of
consumption
• Reasoning to
– make services sustainable
– make services accessible
– Increase the quality of service
DISIT Lab, Univ. Florence, 2014 13
14. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Energy
• Smart building:
– saving and optimizing energy consumption,
district heating
– renewable energy: photovoltaic, wind energy,
solar energy, hydropower, etc.
• Smart lighting:
– turning on/off on the basis of the real needs
• Energy points for electric: c
– ars, bikes, scooters,
• Monitoring consumption, learn people/city
behavior on energy consumption, learn
people behavior, create collective profiles
• Suggesting consumers
– different behavior for consumption: different
time to use the washing machine
• Suggesting administrations
– restructuring to reduce the global
consumption,
– moderate the peak of consumption
DISIT Lab, Univ. Florence, 2014 14
15. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Governmental Services
• Service toward citizens:
– on‐line services:
• register, certification, civil
services,
taxes, use of soil, …
– Payments and banking:
• taxes, schools, accesses
– Garbage collection:
• regular and exceptional
– Quality of air:
• monitoring pollution
– Water control:
• monitoring water quality,
water dispersion, river status
DISIT Lab, Univ. Florence, 2014 15
16. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Smart Governmental Services
• Service toward citizens:
– Cultural Heritage: ticketing on museums,
– Tourism: ticketing, visiting, planning, booking
(hotel and restaurants, etc. )
– social networking: getting service feedbacks,
monitoring
• Social sustainability of services:
– crowd services
• Social recovering of infrastructure,
– New services, exploiting infrastructures
• Monitoring consumption and exploitation of
services, learn people behavior, create collective
profiles
– Discovering problems of services,
– Finding collective solutions and new needs…
DISIT Lab, Univ. Florence, 2014 16
17. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Telecommunication, broadband
• Fixed Connectivity:
– ADSL or more, fiber,
• Mobile Connectivity:
– Public wifi, Services on WiFi,
HSPDA, LTE
• Monitoring communication
infrastructure
• Providing information and
formation on:
– how to exploit the
communication infrastructure
– Exploiting the communication
for the other services,
– moderate the peak of
consumption
DISIT Lab, Univ. Florence, 2014 17
18. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 18
19. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Profiled
Services
Profiled
Services
Smart City Paradigm
DISIT Lab, Univ. Florence, 2014 19
Interoperability
Data
processing
Smart City
Engine
Data
Harvesting
Data / info
Rendering
Data / info
Exploitation
Suggestions
and Alarms
Real Time
Data
Social Data
trends
Data
Sensors
Data Ingesting
and mining
Reasoning and
Deduction
Data Acting
processors
Real Time
Computing
Traffic
control
Social
Media
Sensors
control
Peripheral
processors
Energy
central
eHealth
Agency
eGov Data
collection
Telecom.
Services
…….
Citizens
Formation
Applications
20. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Challenges (addressed by DISIT)
• Social Media blog analysis
• Energy Control for bike sharing
• Wi‐Fi as a sensor for people mobility
• Internet of Things as sensors
– Low costs Bluetooth monitoring
devices
– Vehicle kits with sensors
– Sensors networks spread in the city
and managed by centrals
– Traffic flow sensors
• ..
DISIT Lab, Univ. Florence, 2014 20
Traffic
Control
Social
Media
Sensors
control
Peripheral
processors
Energy
Central
eHealth
Agency
eGov Data
collection
Telecom.
Services
…….
21. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Challenges (addressed by DISIT)
• OD/LOD, Open Data/Linked Open Data:
– gathering, collection,
• Data Mining:
– ontology mapping, integration,
semantically interoperable
– reconciliation, enrichment,
– quality assessment and improvement
• Data Filtering on Streaming
• Blog Vigilance
DISIT Lab, Univ. Florence, 2014 21
Data
Harvesting
Real Time
Data
Social Data
trends
Data
Sensors
Data Ingesting
and mining
22. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Challenges (addressed by DISIT)
• Reasoning and Data processing
– Data analytics, Semantic computing
– Link Discovering
– Inferential reasoning
– Identification of critical condition
– unexpected correlations
– predictions, etc.
• “Real time” Computing out of peripherals
– Action / reaction
• Activation of rules
– Firing conditions for activating computing
– Acceptance of external rules
DISIT Lab, Univ. Florence, 2014 22
Data
processing
Smart City
Engine
Reasoning and
Deduction
Real time
Computing
23. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Challenges (addressed by DISIT)
• User profiling, collective profiles
• Computing Suggestions:
– Information and formation
– Virtuous behavior stimulation
– For citizens and administrators
– …
• Data export:
– API, LOD, ..
– Connection with other Smart City
DISIT Lab, Univ. Florence, 2014 23
Profiled
Services
Profiled
Services
23
Data / info
Rendering
Data / info
Exploitation
Suggestions
and Alarms
Data Acting
processors
Citizens
Formation
Applications
Interoperability
24. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 24
25. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
25
Sii‐Mobility (Smart City) nuove tecnologie e soluzioni intelligenti per
migliorare l'interoperabilità dei sistemi di gestione, di infomobilità urbana e
metropolitana, e di accesso a dati integrati collegati. (TRASPORTI E MOBILITÀ
TERRESTRE )
Coll@bora (Smart City Social Innovation) strumenti collaborativi e di
protezione nel supporto fra strutture sanitarie, associazioni e famiglie con
disabili. (TECNOLOGIE WELFARE E INCLUSIONE)
Contesto: Smart City
DISIT Lab, Univ. Florence, 2014
26. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Coll@bora
• Title: Collaborative Support for Parents and Operators of Disabled
• Objectives: providing strong advantages for
1. Relatives interested in facilitating relations with the
management team;
2. Associations in order to offer a better service to the families
and people with disabilities by providing a collaborative
support to the involved teams, but also to manage the
wealth of knowledge, to support the training of the staff,
etc.
Coll@bora provides a secure collaboration tool for the teams and
for the association to support the families and the disabled
people.
• Link: http://www.disit.dinfo.unifi.it/collabora.html
DISIT Lab, Univ. Florence, 2014 26
27. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 27
28. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Sii-Mobility
• Title: Support of Integrated Interoperability for Services
to Citizens and Public Administration
• Objectives:
1. Reduction of social costs of mobility;
2. Simplify the use of mobility systems;
3. Developing working solutions and application, with testing methods;
4. Contribute to standardization organs, and establishing relationships with
other smart cities’ management systems.
The Sii‐Mobility platform will be capable to provide support for SME and Public
Administrations. Sii‐Mobility consists in a federated/integrated interoperable
solution aimed at enabling a wide range of specific applications for private
services to citizen and commercial services to SME.
• Coordinatore Scientifico: Paolo Nesi, DISIT DINFO UNIFI
• Partner: ECM; Swarco Mizar; University of Florence (svariati gruppi+CNR); Inventi In20;
Geoin; QuestIT; Softec; T.I.M.E.; LiberoLogico; MIDRA; ATAF; Tiemme; CTT Nord;
BUSITALIA; A.T.A.M.; Sistemi Software Integrati; CHP; Effective Knowledge; eWings; Argos
Engineering; Elfi; Calamai & Agresti; KKT; Project; Negentis.
• Link: http://www.disit.dinfo.unifi.it/siimobility.html
DISIT Lab, Univ. Florence, 2014 28
29. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 29
30. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Sii‐Mobility
DISIT Lab, Univ. Florence, 2014 30
31. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 31
• Sperimentazioni principalmente in Toscana
• Sperimentazioni piu’ complete in aree primarie ad alta integrazione dati
• Integrazione con i sistemi presenti
Sii‐Mobility
32. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Sii‐Mobility: Scenari principali
• soluzioni di guida/percorso connessa/o
– servizi personalizzati, segnalazioni, il veicolo/la persona riceve comandi e informazioni in tempo reale ma
modo personalizzato e contestualizzato;
• Piattaforma di partecipazione e sensibilizzazione
– per ricevere dal cittadino informazioni, il cittadino come sensore intelligente, informare e formare il cittadino,
tramite totem, applicazioni mobili, web applications, etc.;
• gestione personalizzata delle politiche di accesso
– Politiche di incentivazione e di dissuasione dell’uso del veicolo, Crediti di mobilità, monitoraggio flussi;
• interoperabilità ed integrazione dei sistemi di gestione
– contribuzione a standard, verifiche e validazione dei dati, riconciliazione dei dati, etc.;
• integrazione di metodi di pagamento e di identificazione
– Politiche pay‐per‐use, monitoraggio comportamento degli utenti;
• gestione dinamica dei confini delle aree a traffico controllato
– tariffazione dinamica e per categoria di veicoli;
• gestione rete condivisa di scambio dati fra servizi (PA e privati)
– affidabilità dei dati e separazione delle responsabilità, Integrazione di open data, riconciliazione, ….;
• monitoraggio della domanda e dell’offerta di trasporto pubblico in tempo reale
– soluzioni per l’integrazione e l’elaborazione dei dati.
DISIT Lab, Univ. Florence, 2014 32
33. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Supporto di Interoperabilita’ Integrato
Architettura Sii‐Mobility
DISIT Lab, Univ. Florence, 2014 33
Supporto: data analytics,
semantic computing
Data Processing:
validation, integration,
geomap.., reconcil, …
Orari, percorsi, fermate,
Valori attuali, politiche di
azione, etc.
profiles,
modelli di
costo, users,
..
Interfaccia di Controllo e
Monitoraggio
API Data publication verso
altricentridi Servizio Utenti
Centrale Operativa:
Supporto alle decisioni,
simulazioni, …
API altri Sii‐Mobility
API altre Centrali SC
Gestori:
Gestori Flotte, AVM,
TPL, Parcheggi,
Autostrade, Car
Sharing, Bike
sharing, ZTL,
direzionatori …..
Agrgegazionedati,
propagazioneazioni
API Centrali nazionali
Social Media:
twitter FaceBook, Blogs
Data ingestion and
pre processing
Acq Dati Emegenza
Open Data:
ambientali, energia,
ordinanze, grafo, ….
Supporto: bigliettazione,
prenotazione, pianificazione, …
Additional
algorithms, ..…..
Big Data processing grid
Sistemi di Gestione
Dati integrati dal territorio
Interoperabilità da e verso altri
sistemi di gestione integrata e SC
Infomobilità e publicazione
Piattaforma di partecipazione e di
Sensibilizzazione
Info. Services for
Totem, Mobile, ..
Applicazioni
Web e Totem
Applicazioni
Mobili
Infrastruttura HW Sii‐Mobility
Sensori e
Apparati di
Rilevazione
Kit veicoli e Attuatori
34. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Linee Azioni (versione breve)
interoperabilità,
integrazione e
modellazione dati
• Interoperabilità, verifiche e validazione dei dati, riconciliazione, etc.
• sistemi distribuiti e mobili, mobile computing, data security, user privacy,..
• data modeling, integrazione Open Data/LOD Pubblici e privati,..
• social media, crowd sourcing, natural language processing
analisi ed
elaborazione dati in
automatico
• semantic computing, knowledge management, verifiche di consistenza e
completezza, user profiling, soluzioni di sentiment and affective analysis, …
• data analytics e ricerca operativa, artificial intelligence; stima di predizioni,
percorsi ottimi, correlazioni inattese, tariffe dinamiche, costi medi, ..
• Bigdata, indicizzazione navigazione ed elaborazione
sensori ed attuatori
innovativi
• sensor network, communication system e mobile, istrumentare la città,
raccolta dati di flusso, velocità ed ambientali, attuazione…
kit per veicoli,
sistemi di
informazione
• sensor KIT evoluti (bus, car, bike).
• Integrazione con metodi di pagamento, gestione e apertura varchi,
direzionatori
Comunicazione e
azione verso il
cittadino
• modelli di comunicazione con il cittadino, sistemi di informazione
• Valutazione e stimolo comportamenti virtuosi, informazione critica e di
criticità
DISIT Lab, Univ. Florence, 2014 34
Sii‐Mobility: Linee di Ricerca
35. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 35
36. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Problematiche di Ricerca “Smart”
• Modellazione della conoscenza con semantica coerente per
effettuare deduzioni corrette sfruttando informazioni numeriche e
simboliche, su grandi volumi e flussi di dati, automazione
– Problematiche derivate da oltre 1000 OD e PD, servizi con modelli diversi
e formati diversi: resilienza, qualità, misura, accesso, integrazione real
time, …
– Tecniche di: modellazione, semantic computing, scheduling, …
• Ricerca su integrazione e modellazione dati:
– Alto livello: predizione su servizi e comportamenti, correlazioni
inattese, situazioni critiche, flusso dei viaggiatori, …
– Problemi e algoritmi di riconciliazione del dato, tracciamento e
versionamento, reputazione, filtraggio, integrazione OD e LOD
internazionali/nazionali, validazione e verifica formale, …. …. ….
36DISIT Lab, Univ. Florence, 2014
37. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Why: Create an ontology that allows to combine
all data provided by the city of Florence and the
Tuscan region.
• Problems: data have different formats, they must
be reconciled in order to be effectively
interconnected to each other, but sometimes
information is incomplete.
• Objective: take advantage of the created
repository and ontology to implement new
integrated services related to mobility; to provide
repository access to SMEs to create new services.
DISIT Lab, Univ. Florence, 2014 37
Research objectives
38. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Analysis of Available Data
• 519 OpenData (Municipality of Florence)
• 145 OpenData (Tuscany Region)
• TPL Timetable and TPL Route
• Street Graph
• Point of Interest
• Real Time Data from traffic sensors
• Real Time Data from parking sensors
• Real Time Data from AVM systems
• Weather Forrecast (consortium Lamma)
DISIT Lab, Univ. Florence, 2014 38
39. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• From MIIC web services (real time)
o Parking payloadPublication (updated every h)
o Traffic sensors payloadPublication (updated every 5‐10min)
o AVM client pull service (updated every 24h)
o Street Graph
• From Municipality of Florence:
o Tram line: KMZ file that represents the path of tram in Florence
o Statistics on monthly access to the LTZ, tourist arrivals per year, annual
sales of bus tickets, accidents per year for every street, number of
vehicles per year
o Municipality of Florence resolutions
• From Tuscany Region:
o Museums, monuments, theaters, libraries, banks, courier services,
police, firefighters, restaurants, pubs, bars, pharmacies, airports, schools,
universities, sports facilities, hospitals, emergency rooms, doctors'
offices, government offices, hotels and many other categories
o Weather forecast of the consortium Lamma (updated twice a day)
DISIT Lab, Univ. Florence, 2014 39
DataSet already integrated
40. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Le misurazioni comprendono dati
come distanza media tra veicoli,
velocità media di transito,
percentuale di occupazione della
strada, transiti orari, ecc.
I sensori sono divisi in gruppi,
ciascuno identificato da un codice di
catalogo che viene passato come
parametro in fase di invocazione del
web service
Un gruppo è un insieme di sensori
che monitora un tratto stradale
I gruppi producono una misurazione
ogni 5 o ogni 10 minuti
Attualmente sono attivi 71 gruppi su
tutto il territorio toscano, per un
totale di 126 sensori
Analisi dei dati attuali MIIC
Sensori traffico: dati relativi alla situazione della viabilità
stradale provenienti da gestori di sistemi di rilevamento a
sensori
40DISIT Lab, Univ. Florence, 2014
41. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Lo stato di un parcheggio viene
descritto da dati come il numero di
posti totali e occupati, il numero di
veicoli in entrata e in uscita, ecc.
I parcheggi sono divisi in gruppi,
ciascuno identificato da un codice di
catalogo che viene passato come
parametro in fase di invocazione del
web service
Un gruppo corrisponde all’insieme di
parcheggi appartenenti a un comune
La situazione di ogni parcheggio
viene pubblicata circa ogni minuto
Attualmente vengono monitorati 50
parcheggi
Analisi dei dati attuali MIIC
Parcheggi: dati relativi allo stato di occupazione dei
parcheggiprovenienti da gestori di aree di parcheggio.
41DISIT Lab, Univ. Florence, 2014
42. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
42
DISIT Lab, Univ. Florence, 2014
Models for Knowledge Representation
• Explicit typologies of Knowledge which can be made
machine‐readable and machine‐understandable:
Structured Knowledge (Ontologies, Taxonomies etc.)
Semi‐structured (DBMS)
Weakly structured (HTML, Tables etc.)
Not structured (Natural Language unstructured text,
images, drawings etc.)
43. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
43
DISIT Lab, Univ. Florence, 2014
Web Ontologies and Languages
• In Computer/Information Science, an Ontology is defined as the conceptualization
of a specific domain of interest, expressed through entities (Classes), descriptors
(Attributes), relationships (Properties) and a pre‐defined rule corpus (Semantics).
• Representation syntax can be equivalently expressed in XML‐based formats, as well
as in the following triple format: <subject> <predicate> <object>.
• Language used for Ontologies representation:
OWL (Web Ontology Language) is the W3C standard for Ontology definition
for Semantic Web.
RDF/XML
N‐triples, N3 etc.
• Interrogation / Query languages:
SPARQL
SERQL
44. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Macroclasses’ Connections
DISIT Lab, Univ. Florence, 2014 44
45. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Maps and Geographical information: formed by
classes Road, Node, RoadElement, AdministrativeRoad,
Milestone, StreetNumber, RoadLink, Junction, Entry,
and EntryRule, Manoeuver, is used to represent the
entire road system of Tuscany region.
• Point of Interest: economical services (public and
privates), activities, which may be useful to the citizen
and who may have the need to search for and to arrive
at. Classification will be based on the division into
categories planned at regional level.
• Weather: including status and forecasts from the
consortium Lamma in Tuscany.
DISIT Lab, Univ. Florence, 2014 45
Ontology’ Macroclasses
46. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Transport: data coming from major LPT companies
including scheduled times, the rail graph, data relating to
real time passage at bus stops. Classes: bus line, Ride,
Route, record, RouteSection, BusStopForeast, RouteLink.
• Sensors: concerning data coming from sensors; they may
include information such as pressure, humidity, pollution,
car flow, car velocity, number of passed cars and tracks, etc.
• Administration: includes information coming from public
administrations such as resolutions issued by each
administration, planned events, changes in the traffic
arrangement, planned VIP visits, sports events, etc.
DISIT Lab, Univ. Florence, 2014 46
Ontology’ Macroclasses
47. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• RoadElement: delimited by a start node and an end node
(ObjectProperties "starts" e "ends");
• Road: composed by RoadElement and Node ("contains")
• AdministrativeRoad: connected to RoadElement
(“isComposed” e “forming”), to Road (“coincideWith”).
Road : AdministrativeRoad = N:M. Both in a 1:N relation
with RoadElement;
• EntryRule: connected to RoadElement ("hasRule",
"accessTo ");
• Maneouvre: linked to EntryRule ("isDescribed").
Described through "hasFirstElem", "hasSecondElem" and
"hasThirdElem". "concerning" fastes a maneouvre to the
concerned junction.
DISIT Lab, Univ. Florence, 2014 47
Maps Macroclass
48. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Node: georeferenced through geo:lat and geo:long.
• Milestone: associated with 1 AdministrativeRoad
("placedIn"), georeferenced through geo:lat and
geo:long.
• StreetNumber: always related to at least 1entry (internal
or external). Connected to RoadElement and Road
("standsIn" and "belongTo"); reverse:"hasStreetNumber".
• Entry: connected to StreetNumber through
"hasInternalAccess" and "hasExternalAccess", with
cardinality resrictions, subclass of geo:SpatialThing,
maximum cardinality restriction 1 to geo:lat and geo:long
• "ownerAuthority" and "managingAuthority": linked to PA
macroclass.
DISIT Lab, Univ. Florence, 2014 48
Maps Macroclass
49. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 49
Maps Macroclass
50. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• OTN: an ontology of traffic networks that is more
or less a direct encoding of GDF (Geographic Data
Files) in OWL;
• dcterms: set of properties and classes maintained
by the Dublin Core Metadata Initiative;
• foaf: dedicated to the description of the relations
between people or groups;
• vCard: for a description of people and
organizations;
• wgs84_pos: vocabulary representing latitude and
longitude, with the WGS84 Datum, of geo‐objects.
DISIT Lab, Univ. Florence, 2014 50
Reused Vocabulary
51. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 51
52. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 52
53. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 53
RDF Store,
Knowledge
base
BigData Store
Dati Statici
ETL
Transfor
mation
ETL
Transfor
mation
ETL
Transfor
mation
ETL
Transfor
mation
Mapping
processe
s
Temp
Store
Triple
Generati
on
Data
Integrati
on Tool
DISIT
Ontology
for
Smart City
R2RML
Model
Reconciliation consolleProcess
Scheduler
Ingestion
Temp
Store
SQL Store
NoSQL Store
BigData Store
Dati Real Time
SQL Store
ETL
Transfor
mation
Validation
Query
SPARQL
Linked Open Graph
Log.disit.org
ServiceMap
servicemap.disit.org
Mapping
SPARQL end point
Access
Server
54. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 54
• Phase 1: collect data from different sources
(MIIC Web Service, Portale dell’Osservatorio
dei Trasporti e della Mobilita’, Municipality of
Florence and Tuscany Region Web Sites).
• Phase 2: first processing means ETL tool and
NoSQL database storage.
• Phase 3: second transformation using ETL
tools and RDF triples creation.
• Phase 4: Saving triple in RDF store.
From Open Data to Triples
55. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• ETL Trasformation
• To realize the R2RML model
• RDF Store
DISIT Lab, Univ. Florence, 2014 55
Helpful Tools
56. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
56
GET
URL
HTTP GET
condizionata
Trasformazione
HBase
Process
Table
Parametro:
nome file
GET
last_update
Process
Table
Aggiornamento
last_update
Process
Table
Ingestion, un esempio
Eseguita da Pentaho Kettle (software ETL)
1) Si passa il nome del file da processare
2) Viene recuperato l’URL della risorsa
3) Download del file (solo se è stato aggiornano dall’ultima volta)
4) Aggiornamento della data di download
5) Trasformazione risorsa: da XML a forma tabulare, eliminazione caratteri
speciali, creazione chiavi, informazioni aggiuntive …
6) Memorizzazione su HBase
DISIT Lab, Univ. Florence, 2014
57. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Ingestion (un esempio)
57DISIT Lab, Univ. Florence, 2014
58. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• To automate the different phases, we have
created an architecture that includes a process
scheduler.
• The process scheduler implementation was
necessary to repeat the 4 phases, from ingestion
to transformation in triple.
• We storing data in Hbase according to a
programmed rate, which is closely linked to the
type of data (static/real time):
o Real‐time data: every 10min;
o Other data: 2 ‐ 15 times a day;
o Static data: once a month or more.
DISIT Lab, Univ. Florence, 2014 58
Architecture
59. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Major problems with the data:
o inconsistent data (different municipality to the same
service, city names that are not a municipality)
o missing data (street number)
o incorrect data (spelling errors)
• Need to validate the data, but above all to
reconcile them to be able to connect with each
other:
o Service – Street Name Reconciliation
o Service – Coordinate Reconciliation
DISIT Lab, Univ. Florence, 2014 59
Data Validation & Reconciliation
60. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Services: ~ 30.100 (all over Tuscan region) of
which:
o Geolocalized Services: ~ 12.400
o Services located at street level: ~ 8.300
• Remaining Services: ~ 9.000 of which:
o Non‐unique results to locate the service at street level
o Street Number missing
o Unusual letters in municipality names or street names
o Address does not exist on Street Graph: ~ 2.200 (next
step: use the Google geocoding API)
DISIT Lab, Univ. Florence, 2014 60
Reconciliation Numbers
61. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Weather: 286 files uploaded twice a day
270,000 Hbase rows/month ~4 million
triples/month;
• Sensors: 126 active sensors 18.000 Hbase
rows/day, 50 supervised parking
~10GB/mese;
• Street Graph: 68M triples.
• For an amount of ~ 80MTriples on repository
DISIT Lab, Univ. Florence, 2014 61
Real Time Data Numbers
62. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 62
63. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Linked Open Graph (LOG): a tool developed to
allow exploring semantic graph of the relation
among the entities. It can be used to access to
many different LOD repository.
(http://log.disit.org/)
• Maps: service based on OpenStreetMaps that
allows to search services available in a preset
range from the selected bus stop.
(http://servicemap.disit.org/)
DISIT Lab, Univ. Florence, 2014 63
App Examples
64. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 64
log.disit.org/
65. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
DISIT Lab, Univ. Florence, 2014 65
servicemap.disit.org
66. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
http://servicemap.disit.org
DISIT Lab, Univ. Florence, 2014 66
67. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
• Integration of rail graph into the ontology;
• Insertion of other static datasets from the
municipality of Florence and other Tuscany PA;
• Using Google Geocoding API to finish services
reconciliation;
• Improvement of services’ list and their
geolocation;
• Creation of other apps that suggest to SME and
PA how to use data.
DISIT Lab, Univ. Florence, 2014 67
Future Works
68. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Major topics addressed
• Smart City Concepts
• Architecture of Smart City Infrastructures
– Peripheral processors
– Data ingestion and mining
– Reasoning and Deduction
– Data Acting processors
• Progetto SmartCity Coll@bora
• Progetto SmartCity Sii‐Mobility
• Data Mining e Problematiche smart City
– DISIT Smart City Ontology
– Data ingestion and integration
– Service Map and Linked Open Graph
• Blog Vigilance via Natural Language Processing
DISIT Lab, Univ. Florence, 2014 68
69. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
‐ Search
‐ Q&A
‐ Graph
of Relations
‐ Social Platform
69
DISIT Lab, Univ. Florence, 2014
Knowledge Work‐flow: from Sources to Final Users
Semantic
Repository
Databases,
Open Data
Archives,
Open Archives
Web
Pages
Semantic
Computing
NLP
Inference
& Reasoning
Recommendations
& Suggestions
Link
Discovering
Reconciliation &
Disambiguation
(Names, Geo Tags etc.)Text
Documents
Publications
Metadata,
Descriptors etc.
70. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
70
DISIT Lab, Univ. Florence, 2014
Data Integrity: Accuracy and Reliability of Data
• Big Data Mining issues
• Many different formats
• Ambiguities and inconsistencies of descriptors, metadata etc.
• Unstructured, decontextualized data does not allow to extract high level
information
• Several different efforts of structure KBs, ontologies, taxonomies etc. in many
fields of Knowledge
• There is necessity of:
– Reconciliation and disambiguation of ingested data
– Organize data into proper forms of structured knowledge
– Standardize definitions, languages, vocabularies etc.
– Link discovering among different knowledge bases
– Make inference to produce additional knowledge
– Detect unexpected correlations, produce suggestions and recommendations
– Provide semantic interoperability among resources and applications.
71. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
71
DISIT Lab, Univ. Florence, 2014
New Approaches ‐ The Semantic Web
• Web of documents (HTML) VS Web of data
(RDF Triples)
• Relational DBMS VS Semantic Datastores
(Ontologies etc.)
• Keyword‐based Search Engines VS NLP Q&A
Tools
72. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
Crawling Strategies:Web‐Crawler
Architecture:
Document / Pages Parsing:Robot Exclusion Protocol
DISIT Lab, Univ. Florence, 2014 72
Web Crawling and Data Mining
# Robots.txt for
http://www.springer.com (fragment)
User-agent: Googlebot
Disallow: /chl/*
Disallow: /uk/*
Disallow: /italy/*
Disallow: /france/*
User-agent: MSNBot
Disallow:
Crawl-delay: 2
User-agent: scooter
Disallow:
# all others
User-agent: *
Disallow: /
73. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
•Finding relationships between entities, LODs etc.,
within different RDF data sources.
DISIT Lab, Univ. Florence, 2014 73
Link Discovering
Source: SILK ‐ http://events.linkeddata.org/ldow2009/papers/ldow2009_paper13.pdf
Semantic
Store
Semantic
Store
. . .
Config
LINKS
Core Logic
Comparison Loop
Resource
Lister
Metrics
Definition
& Evaluation
Resource
Indexer
SPARQL SPARQL
74. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
74
Natural Language
Text
Syntactical Analysis
Tokenizer
Morphologic Analysis
Part‐of‐Speech Tagger
Chunker
Syntactical Parse
Semantic Analysis
Natural Language sentences are subsequently processed
and coded into a semantic representation (by means of
logic formalisms, semantic networks and ontologies)
Text is segmented into sequences of characters
(tokens).
A grammar category is assigned to each token
Each word of a sentence/period is annotated
with its logical rule (subject, predicate,
complement etc.)
This phase uses previous annotations to group
nominal and verbal phrases for each sentence
Produces the Syntactic Parse Tree for each
sentence
NLP ‐ Natural Language Processing Phases
DISIT Lab, Univ. Florence, 2014
75. DISIT Lab, Distributed Data Intelligence and Technologies
Distributed Systems and Internet Technologies
Department of Information Engineering (DINFO)
http://www.disit.dinfo.unifi.it
75
Overview on Smart City
Smart City for Beginners
Corso di Sistemi Distribuiti
Scuola di Ingegneria di Firenze
Prof. Paolo Nesi
DISIT Lab
Dipartimento di Ingegneria dell’Informazione
Università degli Studi di Firenze
Via S. Marta 3, 50139, Firenze, Italia
tel: +39-055-4796523, fax: +39-055-4796363
http://www.disit.dinfo.unifi.it
paolo.nesi@unifi.it
DISIT Lab, Univ. Florence, 2014