The digital reflection of our cities is sharpening and it is tracking their evolution with a decreasing delay. This happens thanks to the pervasive deployment of sensors, the wide adoption of smart phones, the usage of (location-based) social networks and the availability of datasets about urban environment. So while data becomes every day more abundant, decision makers face the challenge to increase their capability to create value out of the analysis of this data. This key note presents how advance visual analytics, ontology base data access and information flow processing methods can help in making sense of Social Media Streams and Call Data Records from Mobile Network Operators during city scale events. Real-world deployments demonstrate the ability of those methods to advance our ability to feel the pulse of our cities in order to deliver innovative services.
The 10 minutes presentation I gave at my PhD defence on 21.9.2015 in Amsterdam. Prof. Frank van Harmelen was my promoter. Prof. Ian Horrocks, prof. Manfred Hauswirth, prof. Geert-Jan Houben, Peter Boncz and prof. Guus Schreiber were my opponents.
Stream reasoning: mastering the velocity and the variety dimensions of Big Da...Emanuele Della Valle
More and more applications require real-time processing of heterogeneous data streams. In terms of the “Vs” of Big Data (volume, velocity, variety and veracity), they require addressing velocity and variety at the same time. Big Data solutions able to handle separately velocity and variety have been around for a while, but only Stream Reasoning approaches those two dimensions at once. Current results in the Stream Reasoning field are relevant for application areas that require to: handle massive datasets, process data streams on the fly, cope with heterogeneous incomplete and noisy data, provide reactive answers, support fine-grained information access, and integrate complex domain models. This talk starting from those requirements, frames the problem addressed by Stream Reasoning. It poses the research question and operationalise it with four simpler sub-questions. It describes how the database group of Politecnico di Milano positively answered those sub-questions in the last 7 years of research. It briefly surveys alternative approaches investigated by other research groups world wide and it elaborates on current limitations and open challenges.
The second lecture of the course I'm giving on "Interoperability and Semantic Technologies" at Politecnico di Milano in the academic year 2015-16. It discusses interoperability using HL7 v2 and v3 as examples of syntactic and semantic interoperability, respectively.
The third lecture of the course I'm giving on "Interoperability and Semantic Technologies" at Politecnico di Milano in the academic year 2015-16. It presents an introduction to the Semantic Web taking a brief walk through in this 15 years of research, standardisation and industrial uptake.
It's a Streaming World! Reasoning upon Rapidly Changing Information (Milano, ...Emanuele Della Valle
Reasoning on rapidly chancing information requires: a) semantic models for representing both data streams and continuous querying/reasoning tasks, and b) reasoning algorithms optimised for continuous reactive query-answering. This talk presents applications cases from which Stream Reasoning requirements were elicited, it briefly covers the findings of 5 year of research, it presents an optimised algorithm for Incremental Reasoning on RDF Streams (IMaRS), and offers an outlook on future research opportunities.
The talk about "Stream Reasoning" for INQUEST -- INnovative QUErying of STreams 2012 -- (http://games.cs.ox.ac.uk/inquest12/) organized in Oxford, United Kingdom, September 25-27 2012.
The talks presents a comprehensive view on "Stream Reasoning" -- reasoning on rapidly flowing information. It illustrates the challenges, presents the achievements of the database group of Politecnico di Milano on the topic, reviews the challenges pointing to results and ongoing work in the Semantic Web community and proposes how to go beyond the current Stream Reasoning concept. It particular, it points out that "orders matters" when processing massive data and it proposes to investigate streaming algorithms for automated reasoning that can be applied not only to data streams that are "naturally" ordered (by recency) but to any sortable data source.
Order Matters! Harnessing a World of Orderings for Reasoning over Massive DataEmanuele Della Valle
More and more applications require real-time processing of massive, dynamically generated, ordered data; order is an essential factor as it reflects recency or relevance. Semantic technologies risk being unable to meet the needs of such applications, as they are not equipped with the appropriate instruments for answering queries over massive, highly dynamic, ordered data sets. This talk argues that some order-aware data management techniques should be exported to the context of semantic technologies, by integrating ordering with reasoning, and by using methods which are inspired by stream and rank-aware data management. This talk systematically explores the problem space, and points both to problems which have been successfully approached and to problems which still need fundamental research, in an attempt to stimulate and guide a paradigm shift in semantic technologies.
The 10 minutes presentation I gave at my PhD defence on 21.9.2015 in Amsterdam. Prof. Frank van Harmelen was my promoter. Prof. Ian Horrocks, prof. Manfred Hauswirth, prof. Geert-Jan Houben, Peter Boncz and prof. Guus Schreiber were my opponents.
Stream reasoning: mastering the velocity and the variety dimensions of Big Da...Emanuele Della Valle
More and more applications require real-time processing of heterogeneous data streams. In terms of the “Vs” of Big Data (volume, velocity, variety and veracity), they require addressing velocity and variety at the same time. Big Data solutions able to handle separately velocity and variety have been around for a while, but only Stream Reasoning approaches those two dimensions at once. Current results in the Stream Reasoning field are relevant for application areas that require to: handle massive datasets, process data streams on the fly, cope with heterogeneous incomplete and noisy data, provide reactive answers, support fine-grained information access, and integrate complex domain models. This talk starting from those requirements, frames the problem addressed by Stream Reasoning. It poses the research question and operationalise it with four simpler sub-questions. It describes how the database group of Politecnico di Milano positively answered those sub-questions in the last 7 years of research. It briefly surveys alternative approaches investigated by other research groups world wide and it elaborates on current limitations and open challenges.
The second lecture of the course I'm giving on "Interoperability and Semantic Technologies" at Politecnico di Milano in the academic year 2015-16. It discusses interoperability using HL7 v2 and v3 as examples of syntactic and semantic interoperability, respectively.
The third lecture of the course I'm giving on "Interoperability and Semantic Technologies" at Politecnico di Milano in the academic year 2015-16. It presents an introduction to the Semantic Web taking a brief walk through in this 15 years of research, standardisation and industrial uptake.
It's a Streaming World! Reasoning upon Rapidly Changing Information (Milano, ...Emanuele Della Valle
Reasoning on rapidly chancing information requires: a) semantic models for representing both data streams and continuous querying/reasoning tasks, and b) reasoning algorithms optimised for continuous reactive query-answering. This talk presents applications cases from which Stream Reasoning requirements were elicited, it briefly covers the findings of 5 year of research, it presents an optimised algorithm for Incremental Reasoning on RDF Streams (IMaRS), and offers an outlook on future research opportunities.
The talk about "Stream Reasoning" for INQUEST -- INnovative QUErying of STreams 2012 -- (http://games.cs.ox.ac.uk/inquest12/) organized in Oxford, United Kingdom, September 25-27 2012.
The talks presents a comprehensive view on "Stream Reasoning" -- reasoning on rapidly flowing information. It illustrates the challenges, presents the achievements of the database group of Politecnico di Milano on the topic, reviews the challenges pointing to results and ongoing work in the Semantic Web community and proposes how to go beyond the current Stream Reasoning concept. It particular, it points out that "orders matters" when processing massive data and it proposes to investigate streaming algorithms for automated reasoning that can be applied not only to data streams that are "naturally" ordered (by recency) but to any sortable data source.
Order Matters! Harnessing a World of Orderings for Reasoning over Massive DataEmanuele Della Valle
More and more applications require real-time processing of massive, dynamically generated, ordered data; order is an essential factor as it reflects recency or relevance. Semantic technologies risk being unable to meet the needs of such applications, as they are not equipped with the appropriate instruments for answering queries over massive, highly dynamic, ordered data sets. This talk argues that some order-aware data management techniques should be exported to the context of semantic technologies, by integrating ordering with reasoning, and by using methods which are inspired by stream and rank-aware data management. This talk systematically explores the problem space, and points both to problems which have been successfully approached and to problems which still need fundamental research, in an attempt to stimulate and guide a paradigm shift in semantic technologies.
A Healthcare Support System for Assisted Living Facilities: an IoT SolutionFulvio Corno
Presentation of the paper "A Healthcare Support System for Assisted Living Facilities: an IoT Solution" at the 40th IEEE Computer Society International Conference on Computers, Software & Applications (COMPSAC 2016) in Atlanta, Georgia, USA on June 10-14, 2016
Presentation of the paper "IoT Meets Caregivers: a Healthcare Support System in Assisted Living Facilities" at the 1st International Conference on IoT Technologies for HealthCare (healthyIoT 2014)
Internet of Things - Cos'è e cosa ci posso fare?Fulvio Corno
Seminario introduttivo sull'Internet of Things, rivolto a studenti delle scuole tecniche secondarie nell'ambito dei programmi di alternanza scuola-lavoro. Organizzato a cura di Forte Chance Torino.
PowerOnt: an ontology-based approach for power consumption estimation in Smar...Luigi De Russis
Presentation given at the 1st Cognitive Internet of Things Technologies (COIOTE 2014)
October 27, 2014, Rome, Italy
The paper is available on the PORTO open access repositor of Politecnico di Torino: http://porto.polito.it/2570936/
Brief report about the contents of the Stream Reasoning workshop at SIWC 2016. Additional info about the event are available at: http://streamreasoning.org/events/sr2016
Build an application upon Semantic Web models. Brief overview of Apache Jena and OWL-API.
Semantic Web course
e-Lite group (https://elite.polito.it)
Politecnico di Torino, 2017
These slides are for a talk that I give at Macquarie University. The offer advice for presenting an academic paper and getting the most out of academic conferences, including preparing slides, basic guidelines for presenting, and taking advantage of opportunities at conferences.
Errori comuni nei documenti di Analisi dei RequisitiRiccardo Cardin
This presentation talks about common errors that I found in my career in documents of specification of requirements. In the presentation are described common errors on use cases, use cases' diagrams and on requirements' specification.
The presentation is took from the Software Engineering course I run in the bachelor-level informatics curriculum at the University of Padova.
Listening to the pulse of our cities with Stream Reasoning (and few more tech...Emanuele Della Valle
The digital reflection of our cities is sharpening and it is tracking their evolution with a decreasing delay. However, we risk that data piles up without easing decision making. This key note, which I gave at the 12th Semantic Web Summer School, presents how stream reasoning (an approach to tame simultaneously the variety and velocity dimensions of Big Data) and advance visual analytics can support decision makers and discusses the lesson learnt.
City Data Fusion: A Big Data Infrastructure to sense the pulse of the city in...Emanuele Della Valle
Streams of information flow through our cities thanks to their progressive instrumentation with diverse sensors, a wide adoption of smart phones and social networks, and a growing open release of datasets. This research investigates the possibility to feel the pulse of our cities in real-time by fusing and making sense of all those information flows. The expected result is a Big Data infrastructure that exploits: semantic technologies, streaming databases, visual analytics, and crowd-sourcing techniques whose incentives are designed for urban environment and life styles. Early deployments for city scale events offer insights on the kind of services such infrastructure will enable.
City Data Fusion and City Sensing presented at EIT ICT Labs for EXPO 2015Emanuele Della Valle
EIT ICT Labs wants be present at EXPO 2015. The City Data Fusion project proposes to install City Sensing in EXPO Gate to display the pulse of Milano during the EXPO. The idea of City Data Fusion and the installation of City Data Fusion for Milano Design Week 2014 is covered in the slides.
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
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
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!
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, ….
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
A Healthcare Support System for Assisted Living Facilities: an IoT SolutionFulvio Corno
Presentation of the paper "A Healthcare Support System for Assisted Living Facilities: an IoT Solution" at the 40th IEEE Computer Society International Conference on Computers, Software & Applications (COMPSAC 2016) in Atlanta, Georgia, USA on June 10-14, 2016
Presentation of the paper "IoT Meets Caregivers: a Healthcare Support System in Assisted Living Facilities" at the 1st International Conference on IoT Technologies for HealthCare (healthyIoT 2014)
Internet of Things - Cos'è e cosa ci posso fare?Fulvio Corno
Seminario introduttivo sull'Internet of Things, rivolto a studenti delle scuole tecniche secondarie nell'ambito dei programmi di alternanza scuola-lavoro. Organizzato a cura di Forte Chance Torino.
PowerOnt: an ontology-based approach for power consumption estimation in Smar...Luigi De Russis
Presentation given at the 1st Cognitive Internet of Things Technologies (COIOTE 2014)
October 27, 2014, Rome, Italy
The paper is available on the PORTO open access repositor of Politecnico di Torino: http://porto.polito.it/2570936/
Brief report about the contents of the Stream Reasoning workshop at SIWC 2016. Additional info about the event are available at: http://streamreasoning.org/events/sr2016
Build an application upon Semantic Web models. Brief overview of Apache Jena and OWL-API.
Semantic Web course
e-Lite group (https://elite.polito.it)
Politecnico di Torino, 2017
These slides are for a talk that I give at Macquarie University. The offer advice for presenting an academic paper and getting the most out of academic conferences, including preparing slides, basic guidelines for presenting, and taking advantage of opportunities at conferences.
Errori comuni nei documenti di Analisi dei RequisitiRiccardo Cardin
This presentation talks about common errors that I found in my career in documents of specification of requirements. In the presentation are described common errors on use cases, use cases' diagrams and on requirements' specification.
The presentation is took from the Software Engineering course I run in the bachelor-level informatics curriculum at the University of Padova.
Listening to the pulse of our cities with Stream Reasoning (and few more tech...Emanuele Della Valle
The digital reflection of our cities is sharpening and it is tracking their evolution with a decreasing delay. However, we risk that data piles up without easing decision making. This key note, which I gave at the 12th Semantic Web Summer School, presents how stream reasoning (an approach to tame simultaneously the variety and velocity dimensions of Big Data) and advance visual analytics can support decision makers and discusses the lesson learnt.
City Data Fusion: A Big Data Infrastructure to sense the pulse of the city in...Emanuele Della Valle
Streams of information flow through our cities thanks to their progressive instrumentation with diverse sensors, a wide adoption of smart phones and social networks, and a growing open release of datasets. This research investigates the possibility to feel the pulse of our cities in real-time by fusing and making sense of all those information flows. The expected result is a Big Data infrastructure that exploits: semantic technologies, streaming databases, visual analytics, and crowd-sourcing techniques whose incentives are designed for urban environment and life styles. Early deployments for city scale events offer insights on the kind of services such infrastructure will enable.
City Data Fusion and City Sensing presented at EIT ICT Labs for EXPO 2015Emanuele Della Valle
EIT ICT Labs wants be present at EXPO 2015. The City Data Fusion project proposes to install City Sensing in EXPO Gate to display the pulse of Milano during the EXPO. The idea of City Data Fusion and the installation of City Data Fusion for Milano Design Week 2014 is covered in the slides.
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
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
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!
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, ….
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
Snap4City a Solution for highly collaborative Smart Cities Environments Paolo Nesi
Snap4City has been created in response to Select4Cities PCP (http://www.select4cities.eu/) call as an open, standardized, data-driven, service-oriented, user-centric platform enabling large-scale co-creation IOT/IOE applications and services for Helsinki, Copenhagen and Antwerp. Snap4City is a fully open source, robust, scalable, easy to use solution, provides tools for co-creation of mixt data driven, stream and batch processing, extending the powerful semantic reasoner of Km4City https://www.km4city.org, with IOT/IOE, GDPR, and city dashboards. Snap4City (Https://www.snap4city.org ) is a solution for setting up Living Labs engaging different all kinds of stakeholders (city operators, researchers, city users, in house, industries) in contributing to the city evolutions, with a platform providing online tools for developing IOT applications, web and mobile Apps, data analytics, micro Applications, external services, KPI, POI, dashboards, IOT edge, etc.
Snap4City/Km4City has been validated in multiple devices (PC, Android, Raspberry, IOT Button, Arduino, ..), and domains: mobility and transport, tourism, health, welfare, social and cities such as Florence, Pisa, Arezzo, and large area of millions on inhabitants as Tuscany and millions of data per day. The innovation is mainly related to semantic reasoning, IOT interoperability, microservices, automated dashboard production, end-2-end encrypted secure communications, GDPR, .. thus setting up in a Snap smart city solutions.
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.
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
RESOLUTE: Governing for Resilience – Implementation Challenges Paolo Nesi
Conducting systematic review and assessment of the state of the art of Resilience Assessment and management concepts, national guidelines and their implementation strategies in order to develop a
conceptual framework for resilience with Urban Transport Systems, UTS
Development of European Resilience Management Guidelines, ERMG
Operationalize and validate the ERMG by implementing the Collaborative Resilience Assessment and Management Support System (CRAMSS) for UTS addressing Roads and Rails infrastructures
Enhancing resilience through improved support to human decision making processes, particularly through increased focus on the training of first responders and population on ERMG and RESOLUTE System
ERMG wide dissemination promoting acceptance and adoption at EU and Associate Countries level
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Listening to the pulse of our cities fusing Social Media Streams and Call Data Records
1. Listening to the pulse of our cities
fusing Social Media Streams and
Call Data Records
Emanuele Della Valle
emanuele.dellavalle@polimi.it
http://emanueledellavalle.org
18th International Conference on
Business Information Systems
24-26 June 2015, Poznań, Poland
2. http://emanueledellavalle.org - Emanuele Della Valle
Me
Assistant Professor at DEIB
Politecnico di Milano
Expert in semantic technologies
and stream computing
Inventor of stream reasoning:
an approach to master the
velocity and variety dimension
of Big Data
15 years experience in research
and innovation projects
startupper: fluxedo.com
3
Emanuele Della Valle http://emanueledellavalle.
3. http://emanueledellavalle.org - Emanuele Della Valle
Acknowledgements
Politecnico di Milano
• DEIB
– What
- Scientific direction
- Semantic technologies
- Stream Processing
- Data science
– Who
- Emanuele Della Valle
- Marco Balduini
• Density Design Lab
– What
- Visual analytics
– Who
- Paolo Ciuccarelli
- Matteo Azzi
Telecom Italia
• SKIL Lab
– What
- Big Data technology
- Data Science
– Who
- Fabrizio Antonelli
- Roberto Larker
Funding agency
4
5. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
6
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
6. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
7
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
because the urban environment
is captured in open datasets
7. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
8
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
and streams of information flows
through our cities thanks to
8. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
9
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
and streams of information flows
through our cities thanks to
the pervasive deployment
of sensors
9. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
10
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
and streams of information flows
through our cities thanks to
the wide adoption of smart
phones
10. http://emanueledellavalle.org - Emanuele Della Valle
The digital reflection of our cities is sharpening
11
[photo: http://hoglundassociates.com/Images/Cloud_Gate.jpg]
and streams of information flows
through our cities thanks to
the usage of (location-based)
social networks
12. http://emanueledellavalle.org - Emanuele Della Valle
and it is tracking changes with a decreasing delay
13
Data source By when Frequency Delay
Census data 100s year years months
Newspaper 100s year days 1 day
Weather sensors 10s year hours/minutes hours/minutes
TV news 10s years hours minutes
Traffic sensors years 15 minutes minutes
Call Data Recors years 15 minutes hours
Social media years seconds seconds
IoT recently milliseconds milliseconds
14. http://emanueledellavalle.org - Emanuele Della Valle
But smarter Big Data can …
…advance our ability to feel the pulse of our cities
15
fusing all those
data sources
making sense of the
fused information
mayor
Definitely E!
to improve decision making and deliver innovative services
15. http://emanueledellavalle.org - Emanuele Della Valle
Can we collect, analyse and repurpose
• social media and
• Call Data Records
to allow
• perceiving emerging patterns and
• observing their dynamics?
Let's focus on a concrete research question
16
[photo: https://www.flickr.com/photos/debord/4932655275]
16. http://emanueledellavalle.org - Emanuele Della Valle
Can we collect, analyse and repurpose
• social media captured at place and events and
• privacy-preserving aggregates of Call Data Records
to allow visually
• perceiving emerging patterns and
• observing their dynamics?
More precisely, the research question is
17
[photo: https://www.flickr.com/photos/debord/4932655275]
17. http://emanueledellavalle.org - Emanuele Della Valle
How to set up an experiment?
18
[photo: https://www.flickr.com/photos/myfuturedotcom/6053042920]
Question Answer
Which city? Milan
Comparing what? Milan Design Week vs. Milan in general
Experimental subjects? Event Managers & casual audience
18. http://emanueledellavalle.org - Emanuele Della Valle
What's Milan Design Week?
19
[map: http://www.fuorisalone.it]
The Milan Design Week (MDW) is a city-scale event
• held yearly in Milan,
• featuring around 1,200 events
• in 500+ places spread across the city and
• attracting about half a million people from all over the
world.
19. http://emanueledellavalle.org - Emanuele Della Valle
Ingredients of the proposed solution
Big Data technologies
- Address "velocity" of data streams in memory
- Address "volume" of data that do not fit in memory
semantic technologies
- Address "variety" using Ontology Based Data Access
- Named Entity Recognition and Linking
data science
- Statistical modelling
- detecting anomalies
Visual analytics
- Allow no-expert access to data
- Tell stories out of data
20
20. http://emanueledellavalle.org - Emanuele Della Valle 21
CitySensing - a solution for event managers (2013)
F. Antonelli, M.Azzi,
M.Balduini, P.Ciuccarelli,
E.Della Valle, R. Larcher:
City sensing: visualising
mobile and social data
about a city scale event.
AVI 2014: 337-338
http://jol.telecomitalia.com/jols
kil/citysensing/
21. http://emanueledellavalle.org - Emanuele Della Valle 22
CitySensing - a solution for casual audience (2014)
M.Balduini, E.Della Valle, M.Azzi, R.Larcher, F.Antonelli, and P.Ciuccarelli:
CitySensing: Fusing City Data for Visual Storytelling. IEEE MultiMedia. TO APPEAR
http://jol.telecomitalia.com/jolskil/citysensing/
http://citysensing.fuorisalone.it/
22. http://emanueledellavalle.org - Emanuele Della Valle 23
How CitySensing works – step 0
Set up a conceptual model (FraPPE) to master the variety in the data sources
M.Balduini, E. Della Valle: FraPPE: a vocabulary to represent heterogeneous
spatio-temporal data to support visual analytics. ISWC 2015 TO APPEAR
23. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 0
FraPPE
• Goal: a vocabulary to represent heterogeneous spatio-
temporal data to support visual analytics
FraPPE offers an homogenous view to the
visual analytics interface built on heterogeneous
data
24
24. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 1
25
For every pixel compute the volume of Call Data Records
(using privacy-preserving aggregation)
Real data recorded on 13 April 2013 between 13:00 and 00:00
25. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 2
26
Find the anomalous pixels comparing the current
volumes with a model of the volumes in this time period
Real data recorded on 13 April 2013 between 13:00 and 00:00
26. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 3
27
Map anomalies to the districts of Milano Design Week
Brera
Tortona
What's
this?
Real data recorded on 13 April 2013 between 13:00 and 00:00
27. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 4
28
For every anomalous pixel capture the hashtags and semantic
entities named in the social media streams
Brera
Tortona
What's
this?
Real data recorded on 13 April 2013 between 13:00 and 00:00
28. http://emanueledellavalle.org - Emanuele Della Valle
How CitySensing works – step 5
29
Take away the hashtags and semantic entities that are
systematically used
Brera
Tortona
Real data recorded on 13 April 2013 between 13:00 and 00:00
29. http://emanueledellavalle.org - Emanuele Della Valle 30
Logical architecture of CitySensing – setup time
Analyse Data Stream
Build Models
Capture Data Stream Capture Static Data
MDW
30. http://emanueledellavalle.org - Emanuele Della Valle 31
Logical architecture of CitySensing – run time
Analyse Data Stream
Build Models
Detect Anomalies
Capture Data Stream
Visualize Analysis
Store Analysis
Capture Static Data
MDW
31. http://emanueledellavalle.org - Emanuele Della Valle
Capturing static data via FraPPE
The frame duration was fixed to
15 minutes
Milano area was covered with
• 1 grid (100x100)
• 10,000 cells
• 250x250 meters in each cell
(the size of the mobile
network cells in the centre
of Milan)
During the Milano Design Week
a total of 5.76 Mln pixel were
captured
+1000 events in +600 places
where collected using the
crowd-sourced databases of fuorisalone.it, breradesigndistrict.it and
tortonaroundesign.com thanks to a partnership with studiolabo
32
Cells in which there are places
hosting Milan Design Week 2013
events
32. http://emanueledellavalle.org - Emanuele Della Valle
Processing Telecom Italia Call Data Records
1.92 Mln Gaussian models were built
• one for each pixel (i.e., for each frame and cell)
• grouping the frames by working and week-end days
• using two months of Call Data Records, and
• verifying volume of CDR has a Gaussian distribution with an
Anderson-Darling test with a significance of 0.05
Built on Pig, R e Cascalog
The processing on 7 m1.large EC2 machines took 24 hours
33
Bad case Good case
Histogram
Histogram
Q-QPlot
Q-Qplot
33. http://emanueledellavalle.org - Emanuele Della Valle
Processing Telecom Italia Call Data Records
Volume of CDR captured in Milan during the Design Week
Calls, SMS and Internet access
were aggregated
(with privacy-preserving
methods) and an
anomaly index was
computed for each of
the 5.76 Mln pixel
The processing of 1 day on 7 m1.large EC2 took 20 mins
34
What 2013 2014
Calls 16,743,875 19,719,629
SMSs 19,454,497 20,240,485
Internet data accesses 137,381,761 197,767,245
[image: https://cerijayne.files.wordpress.com/2011/10/outliersss.png]
34. http://emanueledellavalle.org - Emanuele Della Valle
Do CDR-anomalous pixels relate to events?
CDR-anomalous pixels =pixels in which the anomaly
index is high (>+2σ and <-2σ)
To test if the anomalous pixels were related to the events
of the Milan Design Week
• We used three ground truth
– the pixel of Milan
– the pixels of Brera district
– the pixels of Tortona district
where there was at least an event of Milan Design Week 2013
• We compute
– Precision
– Recall
of the anomalous pixels to find pixels in those three ground
truths
35
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Processing Social Streams
The machinery: the Streaming Linked Data framework
39
M.Balduini, E.Della Valle, D.Dell'Aglio, M.Tsytsarau, T.Palpanas, and C.Confalonieri:
Social Listening of City Scale Events Using the Streaming Linked Data Framework.
International Semantic Web Conference (2) 2013: 1-16
Stream Bus
AnalyserDecorator
Adapter Publisher VisualizerStream
HTTP
HTTP
Data Source Streaming Linked Data Server HTML5 Browser
39. http://emanueledellavalle.org - Emanuele Della Valle
Processing Social Streams
Decoration at work
40
Happily into a bottle of Heineken
bear #heinekendesignweek
@ the Heineken Magazzini
City-Scale Event: Milano Design Week
Event: Heineken Design Week
Location: The Magazzini
hosts
takesPlaceIn
M.Balduini, A.Bozzon, E.Della Valle, Y.Huang, G-J Houben: Recommending Venues Using
Continuous Predictive Social Media Analytics. IEEE Internet Computing 18(5): 28-35
(2014)
40. http://emanueledellavalle.org - Emanuele Della Valle
Processing Social Streams
predictive models were built
• For hastags and semantic entities systematically present
• Using a Holt-Winter method
• grouping the frames by
– working and week-end days and
– Early morning, morning, afternoon, evening, and late night
• Analysing 300,000 geo-located micro-posts collected other
6 months in Milano area (november 2013, aprile 2014)
• It takes few seconds per hashtag/semantic entity on a
60€/month VM in a IaaS
41
Data
Fitted
Forecast
Lower 2,5%
Upper 97,5%
41. http://emanueledellavalle.org - Emanuele Della Valle
Processing Social Streams
Usage of #milan in the weeks around Milan Design Week
Subtracting the predicted usage of #milan
42
200 – 700
700 – 1100
1100 – 1400
1400 – 1900
1900 – 200
200 – 700
700 – 1100
1100 – 1400
1400 – 1900
1900 – 200
WD WE WD WE WD WE WD WE WD
Milan
Design
Week
WD WE WD WE WD WE WD WE WD
42. http://emanueledellavalle.org - Emanuele Della Valle
Processing Social Streams
The difference between the observed and the predicted
usage of #milan perfectly fits the usage of #mdw (the official
hashtag of Milan Design Week)
43
200 – 700
700 – 1100
1100 – 1400
1400 – 1900
1900 – 200
200 – 700
700 – 1100
1100 – 1400
1400 – 1900
1900 – 200
WD WE WD WE WD WE WD WE WD
Milan
Design
Week
Anomalous
usage of
#milan
Usage of
#mdw
43. http://emanueledellavalle.org - Emanuele Della Valle
Processing Social Streams
Geo-references micro-posts captured, semantically annotated,
cleansed using the predictive models and analyzed in Milan area
For each pixel with at least 1 micro-post we computed
The volume related to Milano Design Week
The top-10 hashtags
The top-3 locations/events
Real-time processing was possible with our in-memory
C-SPARQL engine and the Streaming Linked Data framework on
a 20€/month VM in a IaaS
44
What 2013 2014
Geo-located micropost 57,154 21,782
Linked to Milano Design Week 3,569 3,499
Linked to a specific location/event 761 547
44. http://emanueledellavalle.org - Emanuele Della Valle
Do socially active pixels relate to events?
socially active pixels =pixels in which we captured social
media that talk about Milan
Design Week
To computes
• precision
• recall
of the socially active pixels in find pixels in pixels in the
three ground truths about Milan, Brera district and
Tortona district
45
49. http://emanueledellavalle.org - Emanuele Della Valle
Anomalous Socially active Intersection Similar?
Are CDR-anomalous and socially active pixels similar?
Which of the following four scenarios?
50
50. http://emanueledellavalle.org - Emanuele Della Valle
Are CDR-anomalous and socially active pixels similar?
More formally
• Jaccard
• E.g.,
51
J(A,B) = 8/11 J(A,B) = 3/11
A B A
B
J(A,B) =
|A ∩ B|
|A∪B|
54. http://emanueledellavalle.org - Emanuele Della Valle
Evaluation methodology for the casual audience
Guessability study
• Can you guess what I mean without any explanation?
E.g.
55
Dinosaur extinction
"The Shining" by Stephen King
56. http://emanueledellavalle.org - Emanuele Della Valle
The patters you should have got
The CDR-anomaly and the social activity is
57
Correlated Partially correlated Not correlated
57. http://emanueledellavalle.org - Emanuele Della Valle
Evaluation of interface guessability
58
Q: In Brera District
the volume of social
media signal is
partially correlated
with the value of
mobile anomaly
signal
A:
0
0.2
0.4
0.6
0.8
1
58. http://emanueledellavalle.org - Emanuele Della Valle
Evaluation of interface guessability
59
Q: In Porta Romana
the volume of social
media signal is
strongly correlated
with the value of
mobile anomaly
signal
A:
0
0.2
0.4
0.6
0.8
1
59. http://emanueledellavalle.org - Emanuele Della Valle
Evaluation of interface guessability
60
Q: In Tortona District
the volume of social
media signal is
strongly correlated
with the value of
mobile anomaly
signal
A:
0
0.2
0.4
0.6
0.8
1
60. http://emanueledellavalle.org - Emanuele Della Valle
Back to the research question
61
[photo: https://www.flickr.com/photos/debord/4932655275]
Can we collect, analyse and repurpose
• social media captured at place and events and
• privacy-preserving aggregates of Call Data Records
to allow visually
• perceiving emerging patterns and
• observing their dynamics?
Yes!
at least, in Milano Design Week 2013 and 2014
[photo: https://flic.kr/p/beuDaX ]
62. http://emanueledellavalle.org - Emanuele Della Valle 63
Take home message … guess it :-)
Emanuele Della Valle
emanuele.dellavalle@polimi.it
http://emanueledellavalle.org
63. Listening to the pulse of our cities
fusing Social Media Streams and
Call Data Records
Emanuele Della Valle
emanuele.dellavalle@polimi.it
http://emanueledellavalle.org
18th International Conference on
Business Information Systems
24-26 June 2015, Poznań, Poland