Challenges and opportunities in Artificial IntelligenceXavier de Pedro
Short Talk in a Workshop to discuss use of Artificial Intelligence among cities, universities and other partners for potential projects in this area. Held at the Barcelona Supercomputing Center.
The document summarizes Barcelona's Digital City Plan for 2017-2020, which includes several government measures related to open data and digitization. The plan focuses on 5 strategic areas: data sovereignty, ethical data management, developing a city-wide data infrastructure called CityOS, using data to drive internal innovation, and sharing data through a data commons. It will be implemented according to a scheduled timeline and coordinated by a board for transversal data coordination alongside the Municipal Data Office.
CityPulse aims to support the discovery and integration of heterogeneous dynamic data streams from smart city infrastructure, perform real-time quality analysis over live data streams, and employ big data analytics to extract meaningful knowledge from large numbers of data streams and big datasets. It also aims to enable smart adaptation and user-centric decision support, as well as bridge the gap between IoT application technologies and real-world data streams. The project will implement the top 21 ranked use case scenarios out of over 100 collected through crowd-sourcing as proof of concepts, such as a context aware travel planner prototype.
FIWARE Tech Summit - URBO - Map-based City Operational Dashboards BasedFIWARE
Urbo is an operational dashboard developed by Geographica for cities and public administrations that analyzes real-time data from various sensors to provide insights about parking, waste management, lighting, transportation and other systems. It aims to improve citizens' quality of life by optimizing resource usage and promoting accurate, agile decision making while also preventing unwanted events through predictive analytics. The dashboard utilizes specialized PostgreSQL functions and a module for processing tasks to perform advanced spatial operations and analyses.
1. The public sector cannot create data value chains alone and needs to co-create them with the private sector. Co-creation can augment data quality, combine public and private sector data, and enable new AI services and business models.
2. Case studies of data sharing initiatives showed that without standardization of data models, APIs, and unified access, it is difficult to build applications that can utilize different data sources.
3. Data sharing spaces need to evolve into data ecosystems and platforms with interoperability, common data models, value-added services, and data governance frameworks to fully realize the potential of co-creating data value chains between the public and private sectors.
This document discusses automating spatial data sharing between data producers and end users in Wallonia, Belgium. It describes using FME to create an integrated workflow that simplifies data sharing. The workflow validates and transforms data from multiple producers into various formats, then distributes updated data on demand to end users based on their specifications. This automated process saves time by eliminating repetitive manual data distribution tasks.
Challenges and opportunities in Artificial IntelligenceXavier de Pedro
Short Talk in a Workshop to discuss use of Artificial Intelligence among cities, universities and other partners for potential projects in this area. Held at the Barcelona Supercomputing Center.
The document summarizes Barcelona's Digital City Plan for 2017-2020, which includes several government measures related to open data and digitization. The plan focuses on 5 strategic areas: data sovereignty, ethical data management, developing a city-wide data infrastructure called CityOS, using data to drive internal innovation, and sharing data through a data commons. It will be implemented according to a scheduled timeline and coordinated by a board for transversal data coordination alongside the Municipal Data Office.
CityPulse aims to support the discovery and integration of heterogeneous dynamic data streams from smart city infrastructure, perform real-time quality analysis over live data streams, and employ big data analytics to extract meaningful knowledge from large numbers of data streams and big datasets. It also aims to enable smart adaptation and user-centric decision support, as well as bridge the gap between IoT application technologies and real-world data streams. The project will implement the top 21 ranked use case scenarios out of over 100 collected through crowd-sourcing as proof of concepts, such as a context aware travel planner prototype.
FIWARE Tech Summit - URBO - Map-based City Operational Dashboards BasedFIWARE
Urbo is an operational dashboard developed by Geographica for cities and public administrations that analyzes real-time data from various sensors to provide insights about parking, waste management, lighting, transportation and other systems. It aims to improve citizens' quality of life by optimizing resource usage and promoting accurate, agile decision making while also preventing unwanted events through predictive analytics. The dashboard utilizes specialized PostgreSQL functions and a module for processing tasks to perform advanced spatial operations and analyses.
1. The public sector cannot create data value chains alone and needs to co-create them with the private sector. Co-creation can augment data quality, combine public and private sector data, and enable new AI services and business models.
2. Case studies of data sharing initiatives showed that without standardization of data models, APIs, and unified access, it is difficult to build applications that can utilize different data sources.
3. Data sharing spaces need to evolve into data ecosystems and platforms with interoperability, common data models, value-added services, and data governance frameworks to fully realize the potential of co-creating data value chains between the public and private sectors.
This document discusses automating spatial data sharing between data producers and end users in Wallonia, Belgium. It describes using FME to create an integrated workflow that simplifies data sharing. The workflow validates and transforms data from multiple producers into various formats, then distributes updated data on demand to end users based on their specifications. This automated process saves time by eliminating repetitive manual data distribution tasks.
Luigi Selmi - The Big Data Integrator PlatformBigData_Europe
The document discusses the SC4 pilot project, which aims to build a scalable and fault-tolerant platform for processing large datasets using open source frameworks. The platform utilizes a microservices architecture and processes real-time floating car data for tasks like map matching and short-term traffic forecasting using algorithms like feedforward artificial neural networks. It also discusses how semantic technologies from projects like SANSA-Stack and LinkedGeoData could enable additional use cases for the SC4 platform.
The document discusses the plan4business project, which aims to develop a platform to aggregate, integrate, and analyze urban and regional planning data. This will allow users like researchers, planners, and private sector groups to perform complex analyses and visualizations of trends over time and across regions. The platform will offer planning data and tools via an API and web interface. Key challenges are integrating diverse planning datasets and efficiently querying them. The business model involves data providers, curators, clients, and a data broker hosting the portal to generate revenue from on-demand and subscription services.
CubiCasa converts hundreds of floor plans and 3D scans into BIM models daily using AI/neural networks. The BIM models contain quantified and feature data about the properties. Image recognition technology analyzes quality and features from property photos. This creates a unique data combination of the BIM model data and derived image data in CubiCasa's Property Data Platform. The Platform can then be used for real estate listings, property reports, appraisals, and other innovative property apps.
A spatial approach to the energy generating potential of real estateJene van der Heide
This document discusses a project by the Netherlands' Cadastre to map state and city buildings in The Hague to analyze their energy characteristics and potential for renewable energy generation. The Cadastre is collecting data on building attributes, underground infrastructure, and land ownership to visualize on an ArcGIS Online platform. Stakeholders like the city and utility companies are sharing data on energy usage, employees, and solar potential. The ultimate goals are to define opportunities to reduce and stabilize energy costs and facilitate private sector involvement through an open tender. Visualization of spatial energy and heat exchange potentials between buildings is seen as key to developing viable business cases for renewable solutions.
Qinetiq is an international technology company employing over 6,000 technical personnel working across multiple disciplines. They have developed open source visual data extraction software that can build 3D point cloud models from images to assess their use in vehicle navigation. While initial tests extracting images from "non-iconic" locations showed potential, there was a large gap between the available image density and what is required. Going forward, Qinetiq aims to include video and intelligence data, provide image location services for areas of interest, and develop tools to exploit extracted data for image and intelligence analysis.
The document describes a proposed system to improve search and rescue efforts for victims in mountain environments. The system would integrate geospatial data, allow for multiple competing hypotheses, and support rescuers' reasoning processes. It includes features like a searchable tree of map items, management of clues and uncertainty parameters, and visualization of probable location areas on an interactive map. The goal is to help rescuers more effectively deduce victims' locations based on verbal clues and manage the imperfect nature of information received.
The document summarizes updates on Colorado's state GIS programs. It discusses annual updates to statewide parcel and address datasets collected from counties. It also provides an overview of the state's broadband mapping project, including data collection from providers, processing, quality control, and publishing results. Additionally, it outlines the state's ongoing LiDAR data collection efforts across Colorado and plans for a new self-serve distribution system. The presentation concludes with information on the state's annual data call process and outreach to local agencies.
Citizen centric services business & ict consulting sept 2014Thierry Holoffe
The document discusses how cities are becoming more citizen-centric by leveraging technology. As urban populations grow, citizens expect personalized, instant services from public entities. Cities are shifting from traditional top-down models to bottom-up, citizen-focused approaches using open data and mobile apps. Examples provided include social networks for neighborhoods, apps for reporting issues, and participatory budgeting. The keys to success include revising processes, coordination, infrastructure, inclusion, and change management to empower citizens and make cities smarter.
The document describes a digital innovation hub for agriculture that is a new and evolving project. It has a scalable cloud-based architecture built on open source technologies. The hub provides a web interface for integrating development and analytic tools to support machine learning processing of Earth observation data. Results can be visualized using OGC services. The hub will be available for testing during a hackathon event.
Conekt provides engineering consultancy and testing services to companies across industries. It developed an efficient process to reduce data from cameras descending on an array by extracting key frames for 3D map generation. This was demonstrated by presenting a mixed 3D/2D context view from a ground-launched system. Going forward, Conekt aims to enable real-time high tempo 2D imaging, automate base station processing for faster 3D modeling, and integrate the system onto various vehicles and soldier-mounted devices.
The document discusses smart city modeling and presents a framework for general indicator modeling. It proposes modeling indicators separately from geospatial data using a general indicator model. This separates indicator application models defined by domain experts from underlying geospatial models. It advocates linking indicator and geospatial models through a weaving model to enable automatic derivation of indicator values from city object attributes and computations. The framework represents indicators and their relationships using formal models to support indicator-based evaluation and decision making for smart city planning and management.
Using big data and open source for smart city planningGuy Hadash
This document discusses using big data and open source tools for smart city planning and transportation monitoring in Madrid. It notes that the Internet of Things market will grow significantly by 2020, producing massive amounts of data from billions of devices. However, simply archiving large datasets is not sufficient - the data must be processed and analyzed to extract value. The document outlines a project that analyzed historical sensor data from 300 traffic sensors on a Madrid highway to develop a proof of concept dashboard for the city council. By applying machine learning algorithms to the historical data, the system can detect anomalies in current traffic speeds and intensities and report them via the dashboard. Future plans could include using historical data to identify traffic bottlenecks, predict correlations with other data sources like weather,
ECPPM 2018 (Copenhagen) congress:
"Collaborative platform based on standard services for the semi-automated generation of the 3D city model on the cloud"
Big data and transport - where can it take us? Paul KompfnerBigData_Europe
Big data has the potential to provide surprising insights into mobility if used purposefully to answer specific questions. Sources of big transport data include vehicle sensors, infrastructure sensors, mobile devices, social media, and associated transaction systems. In the future, mobility-as-a-service platforms will depend heavily on big data handling to broker demand, understand customer journey plans, and efficiently fulfill transport services through extensive data processing and analysis. Key open questions include who will be the customers and owners of these big data systems and what their long-term business models will be.
The document discusses key concepts in data visualization including interactivity, multidimensionality, and mapping. It outlines advantages such as dynamism, flexibility, interactivity, editability and exportability. Examples of data visualization projects are provided.
This document describes a pilot project called the Digital Democracy and Common Data Commons (DDDC) pilot that will take place in Barcelona from October 2018 to April 2019. The pilot will use DECODE and Decidim technology to enable citizens to make policy proposals and collectively govern data commons. It will involve a series of engagement events focused on governance, legal and economic issues relating to data and digital democracy. The goal is to experiment with technologies that empower citizens to transparently and privately propose, debate, and decide on data issues.
Luigi Selmi - The Big Data Integrator PlatformBigData_Europe
The document discusses the SC4 pilot project, which aims to build a scalable and fault-tolerant platform for processing large datasets using open source frameworks. The platform utilizes a microservices architecture and processes real-time floating car data for tasks like map matching and short-term traffic forecasting using algorithms like feedforward artificial neural networks. It also discusses how semantic technologies from projects like SANSA-Stack and LinkedGeoData could enable additional use cases for the SC4 platform.
The document discusses the plan4business project, which aims to develop a platform to aggregate, integrate, and analyze urban and regional planning data. This will allow users like researchers, planners, and private sector groups to perform complex analyses and visualizations of trends over time and across regions. The platform will offer planning data and tools via an API and web interface. Key challenges are integrating diverse planning datasets and efficiently querying them. The business model involves data providers, curators, clients, and a data broker hosting the portal to generate revenue from on-demand and subscription services.
CubiCasa converts hundreds of floor plans and 3D scans into BIM models daily using AI/neural networks. The BIM models contain quantified and feature data about the properties. Image recognition technology analyzes quality and features from property photos. This creates a unique data combination of the BIM model data and derived image data in CubiCasa's Property Data Platform. The Platform can then be used for real estate listings, property reports, appraisals, and other innovative property apps.
A spatial approach to the energy generating potential of real estateJene van der Heide
This document discusses a project by the Netherlands' Cadastre to map state and city buildings in The Hague to analyze their energy characteristics and potential for renewable energy generation. The Cadastre is collecting data on building attributes, underground infrastructure, and land ownership to visualize on an ArcGIS Online platform. Stakeholders like the city and utility companies are sharing data on energy usage, employees, and solar potential. The ultimate goals are to define opportunities to reduce and stabilize energy costs and facilitate private sector involvement through an open tender. Visualization of spatial energy and heat exchange potentials between buildings is seen as key to developing viable business cases for renewable solutions.
Qinetiq is an international technology company employing over 6,000 technical personnel working across multiple disciplines. They have developed open source visual data extraction software that can build 3D point cloud models from images to assess their use in vehicle navigation. While initial tests extracting images from "non-iconic" locations showed potential, there was a large gap between the available image density and what is required. Going forward, Qinetiq aims to include video and intelligence data, provide image location services for areas of interest, and develop tools to exploit extracted data for image and intelligence analysis.
The document describes a proposed system to improve search and rescue efforts for victims in mountain environments. The system would integrate geospatial data, allow for multiple competing hypotheses, and support rescuers' reasoning processes. It includes features like a searchable tree of map items, management of clues and uncertainty parameters, and visualization of probable location areas on an interactive map. The goal is to help rescuers more effectively deduce victims' locations based on verbal clues and manage the imperfect nature of information received.
The document summarizes updates on Colorado's state GIS programs. It discusses annual updates to statewide parcel and address datasets collected from counties. It also provides an overview of the state's broadband mapping project, including data collection from providers, processing, quality control, and publishing results. Additionally, it outlines the state's ongoing LiDAR data collection efforts across Colorado and plans for a new self-serve distribution system. The presentation concludes with information on the state's annual data call process and outreach to local agencies.
Citizen centric services business & ict consulting sept 2014Thierry Holoffe
The document discusses how cities are becoming more citizen-centric by leveraging technology. As urban populations grow, citizens expect personalized, instant services from public entities. Cities are shifting from traditional top-down models to bottom-up, citizen-focused approaches using open data and mobile apps. Examples provided include social networks for neighborhoods, apps for reporting issues, and participatory budgeting. The keys to success include revising processes, coordination, infrastructure, inclusion, and change management to empower citizens and make cities smarter.
The document describes a digital innovation hub for agriculture that is a new and evolving project. It has a scalable cloud-based architecture built on open source technologies. The hub provides a web interface for integrating development and analytic tools to support machine learning processing of Earth observation data. Results can be visualized using OGC services. The hub will be available for testing during a hackathon event.
Conekt provides engineering consultancy and testing services to companies across industries. It developed an efficient process to reduce data from cameras descending on an array by extracting key frames for 3D map generation. This was demonstrated by presenting a mixed 3D/2D context view from a ground-launched system. Going forward, Conekt aims to enable real-time high tempo 2D imaging, automate base station processing for faster 3D modeling, and integrate the system onto various vehicles and soldier-mounted devices.
The document discusses smart city modeling and presents a framework for general indicator modeling. It proposes modeling indicators separately from geospatial data using a general indicator model. This separates indicator application models defined by domain experts from underlying geospatial models. It advocates linking indicator and geospatial models through a weaving model to enable automatic derivation of indicator values from city object attributes and computations. The framework represents indicators and their relationships using formal models to support indicator-based evaluation and decision making for smart city planning and management.
Using big data and open source for smart city planningGuy Hadash
This document discusses using big data and open source tools for smart city planning and transportation monitoring in Madrid. It notes that the Internet of Things market will grow significantly by 2020, producing massive amounts of data from billions of devices. However, simply archiving large datasets is not sufficient - the data must be processed and analyzed to extract value. The document outlines a project that analyzed historical sensor data from 300 traffic sensors on a Madrid highway to develop a proof of concept dashboard for the city council. By applying machine learning algorithms to the historical data, the system can detect anomalies in current traffic speeds and intensities and report them via the dashboard. Future plans could include using historical data to identify traffic bottlenecks, predict correlations with other data sources like weather,
ECPPM 2018 (Copenhagen) congress:
"Collaborative platform based on standard services for the semi-automated generation of the 3D city model on the cloud"
Big data and transport - where can it take us? Paul KompfnerBigData_Europe
Big data has the potential to provide surprising insights into mobility if used purposefully to answer specific questions. Sources of big transport data include vehicle sensors, infrastructure sensors, mobile devices, social media, and associated transaction systems. In the future, mobility-as-a-service platforms will depend heavily on big data handling to broker demand, understand customer journey plans, and efficiently fulfill transport services through extensive data processing and analysis. Key open questions include who will be the customers and owners of these big data systems and what their long-term business models will be.
The document discusses key concepts in data visualization including interactivity, multidimensionality, and mapping. It outlines advantages such as dynamism, flexibility, interactivity, editability and exportability. Examples of data visualization projects are provided.
This document describes a pilot project called the Digital Democracy and Common Data Commons (DDDC) pilot that will take place in Barcelona from October 2018 to April 2019. The pilot will use DECODE and Decidim technology to enable citizens to make policy proposals and collectively govern data commons. It will involve a series of engagement events focused on governance, legal and economic issues relating to data and digital democracy. The goal is to experiment with technologies that empower citizens to transparently and privately propose, debate, and decide on data issues.
This document discusses open data and APIs. It introduces the CitySDK project, an open data platform used by eight European cities to make their data available. Developers can use the CitySDK API to access mobility and tourism data. The document also discusses using social media APIs like Twitter to collect and analyze geotagged tweets. It provides examples of applications that combine multiple API data sources and instructions for how to use the Twitter API to retrieve trending topics and geotagged tweets from Amsterdam.
Overview presentation of the CPaaS.io project given at the first year review meeting in Tokyo on October 5, 2017.
Disclaimer:
This document has been produced in the context of the CPaaS.io project which is jointly funded by the European Commission (grant agreement n° 723076) and NICT from Japan (management number 18302). All information provided in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. For the avoidance of all doubts, the European Commission and NICT have no liability in respect of this document, which is merely representing the view of the project consortium. This document is subject to change without notice.
Interoperability challenges & solutions in the EW-Shopp H2020 innovation action: tool-supported interoperability; exchange of event data and custom event ontology for data analytics; reconciliation across systems of spatial identifiers.
SocIoTal: Creating a Citizen - Centric Internet of ThingsDunavNET
Contrary to the general approach of creating Internet of Things
(IoT) services from a business perspective, the project addresses the design of citizen centered IoT solution.
The document discusses open data and its impacts. It notes that open data must be freely accessible, in reusable formats, and under an open license. Open data can impact politics, society, and the economy by enabling open innovation and business opportunities. Implementing an open data policy faces challenges regarding policy, regulation, capacity, and technology. The Open Data Charter provides principles for open data policies. OpenDataSoft is a company that helps make data scale and create value through visualizations, APIs, and enabling data reuse. It discusses using open data in areas like transportation, smart cities, and performance management.
La telefonía móvil como fuente de información para el estudio de la movilidad...Esri España
Existe una multitud de sectores donde es necesario disponer de datos que permitan entender los patrones de comportamiento de la población: la planificación y la operación de los sistemas de transporte requiere información precisa, fiable y actualizada sobre la demanda de viajes; los patrones de actividad y movilidad de los turistas tienen profundas implicaciones para la planificación de infraestructuras, el desarrollo de la oferta turística y las estrategias de marketing turístico; entender el comportamiento espacial de los clientes es clave para optimizar las estrategias de distribución, comercialización y publicidad, determinar la localización de un nuevo comercio o punto de venta, o maximizar el retorno de la inversión en acciones de marketing. Las fuentes de datos tradicionales, basadas fundamentalmente en encuestas y registros administrativos, proporcionan información muy valiosa, pero no están exentas de inconvenientes. En general, las encuestas resultan caras y lentas de realizar, lo que limita el tamaño de la muestra y la frecuencia de actualización de la información, a lo que hay que añadir otras limitaciones intrínsecas, como las respuestas incorrectas e imprecisas, o la dependencia de la disposición a responder de los entrevistados. En los últimos años, la generalización del uso de dispositivos móviles ha abierto nuevas oportunidades para superar muchas de estas limitaciones. La posibilidad de recoger datos geolocalizados sobre la actividad de las personas, de manera dinámica y a un coste sensiblemente inferior al de los métodos tradicionales, abre la puerta a infinidad de aplicaciones. Las más evidentes son quizá las relacionadas con el transporte y la movilidad, pero el abanico es mucho más amplio, abarcando casi cualquier área que requiera información sobre los patrones de actividad y movilidad de la población. Las nuevas fuentes de datos plantean asimismo importantes retos, desde la necesidad de desarrollar nuevas metodologías de análisis, hasta la protección de la privacidad.
Vídeo de la ponencia: https://youtu.be/5PKC5Qm0eHM
Presentation given by Jaime Ventura, Porto Digital, at Open & Agile Smart Cities' annual Connected Smart Cities & Communities Conference 2020 on 23 January in Brussels, Belgium.
Explanatory presentation of my final project for Technicity course. It consists of an analisys about what are the general conditions to take into account when setting up a framework for an Intelligent City project. These general conditions form the meta-framework.
To develop the present work, I hav econsidered a concrete example: that of i-Coruña, the Intelligent City Project for A Coruña (North-Western Spain)
Open Land Use - the Current Status and Steps Forwardplan4all
The document discusses the Open Land Use Map initiative which aims to create a detailed and freely available land use map of Europe. It summarizes the current status of the Open Land Use Map, which integrates heterogeneous land use data sources into a harmonized and INSPIRE compliant dataset. It also discusses plans to create an Open Land Use Map for Africa using satellite imagery and machine learning techniques to classify land use at the municipal level across Africa.
Snap4City November 2019 Course: Smart City IOT Data Ingestion Interoperabilit...Paolo Nesi
• Data Ingestion Capabilities
• Data Ingestion Strategy
• Setting Up the Road Graph on Knowledge Base
• Data Set Load via Data Gate (plus how to load triples into Knowledge base)
• Data Ingestion and Transformation via ETL Processes
• Data Ingestion via IOT Brokers
• IOT Network: recall of basic concepts
• IOT Directory
• IOT Devices and IOT Brokers Registration
• Data Ingestion via IOT Applications
• Data Ingestion from API, External Services, Custom MicroServices
• Data Ingestion via Web Scraping
• Data Streams from Smart City API, participatory
• Data Streams from Mobile Devices
• Data Streams from Dashboards
• GIS Data Import and Export
• Social Media data collection and exploitation
• Acknowledgements
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
Snap4City November 2019 Course: Smart City IOT Data AnalyticsPaolo Nesi
• Data Analytics: Examples from Snap4City
o Smart parking: Predictions
o User Behavior Analysis, via Wi-Fi, OD, Trajectories
o Recognition of Used Transportation means
o Traffic Flow Reconstruction, from Traffic Sensors Data
o Quality of Public Transport Service
o Origin Destination Matrices from: Wi-Fi, Mobile Apps, etc.
o Demand of Mobility vs Offer of Transportation
o Modal and Multimodal Routing for Navigation and Travel Planning
o Environmental Data Analysis and Predictions, early Warning
o Prediction of Air Quality Conditions
o Anomaly Detection
o What-IF Analysis
• Data Analytics: Enforcing and Exploiting
o Real Time Data Analytics: using R Studio Exploitation in IOT Applications
• Decision Support Systems, Smart DS and Resilience DS
• Twitter Vigilance: Social Media Analysis: Early Warning, Predictions
Km4city: Open Urban Platform for a Sentient Smart CityPaolo Nesi
1) Km4City is an open urban platform that aggregates data from IoT sensors and city services to create a smart city ecosystem.
2) The platform includes tools for real-time monitoring, data analytics, influencing citizen behavior, and transforming data into new smart city services.
3) Example tools include smart city dashboards, predictive models, mobile apps, and Twitter analysis to gain citizen input and assess sentiment.
CITY DATA EXCHANGE – A MARKETPLACE FOR PUBLIC AND PRIVATE DATA - PETER BJØRN ...Big Data Week
Peter joined Hitachi Consulting in August 2015 as the leader of the City data Exchange in Copenhagen. Peter is no stranger to the initiative as he was leading the tender process from the client side where he was the Smart City Manager at the triple helix organisation CLEAN.
He is a well know smart city expert and has presented at several large international events including the Barcelona Smart City Expo, Smart to Future Cities in London and at the EU-China Smart City collaboration event in Beijing where he represented the City of Copenhagen. Peter also have more than 10 years of international consultant experience from the EU Commission, EU Parliament, OECD, Nordic Innovation Center and Danish government institutions. His expertise is in regional innovation systems, sector competitiveness studies and smart cities.
Wikipedia Cultural Diversity Dataset - ICWSM 2019David Laniado
In this paper we present the Wikipedia Cultural Diversity dataset. For each existing Wikipedia language edition, the dataset contains a classification of the articles that represent its associated cultural context, i.e. all concepts and entities related to the language and to the territories where it is spoken. We describe the methodology we employed to classify articles, and the rich set of features that we defined to feed the classifier, and that are released as part of the dataset. We present several purposes for which we envision the use of this dataset, including detecting, measuring and countering content gaps in the Wikipedia project, and encouraging cross-cultural research in the field of digital humanities.
Visualizing social interactions in Wikipedia - WikiCorp 2018David Laniado
This document describes research on visualizing social interactions and controversies on Wikipedia. Key points:
- Researchers developed Contropedia, a tool to analyze controversial elements within Wikipedia articles over time using edit histories. It identifies controversial topics, when they were most disputed, and perspectives from different language versions.
- Controversiality is measured by counting disagreeing edits involving specific topics. The tool represents discussions as trees and networks to analyze complexity.
- Analysis found political interactions on articles are neutral, while personal talk pages show homophily. Women express more positive emotions and are more relationship-oriented in discussions.
- Contropedia aims to increase transparency on knowledge negotiations and perspectives behind published content on Wikipedia.
Contropedia: Critical learning through Wikipedia's edit historyDavid Laniado
Presentation at the Euroclio Annual Conference "Mediterranean Dialogues" in Marseille, France, April 24, 2018
Wikipedia is not only the largest and most popular encyclopedia, it is also one of the largest collaborative platforms that involves a worldwide community spread over more than 200 different language editions. Its articles are not static pieces of knowledge, but can be edited (almost) anytime by anyone.
The value of Wikipedia content is guaranteed less by absence of errors than by their constant "improvability". Wikipedia’s core principle, "neutral point of view" (NPOV), allows editors with different viewpoints to correct each other by rewriting an article so that all significant viewpoints are represented with due weight. The quality of Wikipedia, in other words, is made possible by the struggle over its content.
Such conflict over content often also reflect societal debates on the corresponding topics, although they are difficult to inspect through Wikipedia's interface. Contropedia provides a visual interface for making such information easily accessible and allows users to identify the elements that aroused most dispute and activity, as well as the topical development of an article. As the tool is language-agnostic it can be applied to any language edition, and allows for cross-cultural comparisons of viewpoints and societal debates. A demo of the tool is available at: http://contropedia.net/demo/
Contropedia can help history teachers to foster critical thinking by exposing knowledge as a collective construction, as the fruit of confrontation among different points of view that may vary across cultures and over time, rather than as something absolute and immutable.
Gender Gap in Collaborative Platforms: Language and emotions in Wikipedia Dis...David Laniado
Slides presented at UPF:
https://www.upf.edu/web/mdm-dtic/gender-and-wikipedia_2017
https://www.upf.edu/en/web/guest/home/-/asset_publisher/UI8Z8VAxU47P/content/id/7282941/maximized#.WIjEE2dA-Ba
The presentation focuses on two studies that investigate differences in language used by men and women on Wikipedia talk pages. Automatic message analysis reveals that women participate more in discussions that have a positive tone, and use a language that promotes more relationship and emotional connection compared to men. We also observe a gender difference in the leadership style: while men administrators tend to maintain an impersonal tone compared to other users, women administrators are indistinguishable from other women, and use a markedly emotional and relationship-oriented language. The results suggest the importance of communication style to address gender gap in online collaboration platforms, and to favor more welcoming environments capable of attracting and retaining users.
Visualising Wikipedia Controversies: a look inside ContropediaDavid Laniado
This document introduces Contropedia, a tool that visualizes controversies within Wikipedia articles. It analyzes edit histories to identify the most disputed concepts, locations within articles where controversies are concentrated, and the timeline of disputes. Contropedia represents this data through layer views, dashboards, and detailed edit histories to increase transparency and foster understanding of debates. It aims to help researchers, Wikipedians, teachers and citizens better comprehend controversial topics and participation on Wikipedia.
Gender patterns on a large social network (SocInfo 2014)David Laniado
This document analyzes gender patterns in a large online social network with over 10 million users. It finds that both men and women exhibit homophily or a preference for same-gender connections, though this tendency is stronger for women, especially in the early stages of joining the network. Both genders' friend networks and interactions tend to form more single-gender triangles than would be expected by chance. However, users with many friends show a tendency toward heterophily or connecting with other genders. The findings suggest women perceive the presence of other women as important for entering a new online social space, which could explain challenges in addressing the gender gap.
Emotions under Discussion: Gender, Status and Communication in WikipediaDavid Laniado
I present a large-scale analysis of emotional expression and communication style of editors in Wikipedia discussions. The presentation focuses especially on how emotion and dialogue differ depending on the status, gender, and the communication network of the about 12000 editors who have written at least 100 comments on the English Wikipedia's article talk pages. The analysis is based on three different predefined lexicon-based methods for quantifying emotions: ANEW, LIWC and SentiStrength. The results unveil significant differences in the emotional expression and communication style of editors according to their status and gender, and can help to address issues such as gender gap and editors' decline.
Dinámicas de Discusión en Red: Conflicto, Deliberación, Consenso y RolesDavid Laniado
Presentación en la UOC sobre lineas futuras de investigación para estudiar el movimiento 15m a través de conversaciones en red. http://datanalysis15m.wordpress.com/
Emotions and dialogue in a peer-production community: the case of WikipediaDavid Laniado
Slides presented at WikiSym 2012.
This paper presents a large-scale analysis of emotions in conversations among Wikipedia editors. Our focus is on the emotions expressed by editors in talk pages, measured by using the Affective Norms for English Words (ANEW).
We find evidence that to a large extent women tend to participate in discussions with a more positive tone, and that administrators are more positive than non-administrators. Surprisingly, female non-administrators tend to behave like administrators in many aspects.
We observe that replies are on average more positive than the comments they reply to, preventing many discussions from spiralling down into conflict. We also find evidence of emotional homophily: editors having similar emotional styles are more likely to interact with each other.
Our findings offer novel insights into the emotional dimension of interactions in peer-production communities, and contribute to debates on issues such as the flattening of editor growth and the gender gap.
When the Wikipedians talk: network and tree structure of Wikipedia discussion...David Laniado
Talk pages play a fundamental role in Wikipedia as the place for discussion and communication. In this work we use the comments on these pages to extract and study three networks, corresponding to different kinds of interactions. We find evidence of a specific assortativity profile which differentiates article discussions from personal conversations. An analysis of the tree structure of the article talk pages allows to capture patterns of interaction, and reveals structural differences among the discussions about articles from different semantic areas.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Build applications with generative AI on Google CloudMárton Kodok
We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
"Financial Odyssey: Navigating Past Performance Through Diverse Analytical Lens"sameer shah
Embark on a captivating financial journey with 'Financial Odyssey,' our hackathon project. Delve deep into the past performance of two companies as we employ an array of financial statement analysis techniques. From ratio analysis to trend analysis, uncover insights crucial for informed decision-making in the dynamic world of finance."
3. Customized visualizations
● The tool allows users to:
○ Display data using markers or heatmaps
○ Display animations of temporal data
○ Display temporal trends graphs
○ Display information associated with a given marker
○ Aggregate data with different temporal and geo granularities
○ Filter data based on keywords and time ranges
○ Combine two or more data sources on different layers
7. Geographical aggregation by district
The dashboard allows to…
● Visualize data from diverse public sources:
○ Airbnb InsideAirbnb
○ Aplicatiu de Sistemes Integrats d’Atenció ASIA
○ Incidències, Reclamacions i Suggeriments IRIS
○ Open Data Infrastructure ODI
○ Sentilo
○ Smart Citizen
● Create visualizations customized by the user:
○ Display data using markers or heatmaps
○ Aggregate with temporal and geo granularities
○ Filtering based on keywords and time ranges
○ Combine two or more visualizations to discover patterns
8. Combining data sources on different layers
Noise sensors (markers) and complaints about noise (heatmap)
9. Sharing and co-creation
The tool allows users to:
● Create, combine and share visualizations:
○ Combine several visualizations (widgets) into a
dashboard
○ Move widgets between dashboards
○ Share the link to a widget or dashboard
→ users can share and spread their results
→ other users can build on a visualization and modify it
10. Currently integrated data sources
● Open data from public sources:
○ City events: ASIA (Aplicatiu de Sistemes Integrats d’Atenció)
○ Citizen complaints: IRIS (Incidències, Reclamacions i
Suggeriments)
○ Bikesharing data from the Municipality Open Data: ODI
(Open Data Infrastructure)
○ Sensor data: Sentilo
○ CityOS (under development with IMI)
○ Decidim public data through the API (next step!)
● and from some external sources:
○ Sensor data: Smart Citizen
○ Scraped Airbnb data: InsideAirbnb
12. Data record common structure
● A data collector for each data source
○ to turn data from the original data format into a common format
○ payload field includes data that are different for each data source
14. Work in progress
● Improve backend
○ Revise data architecture to improve performance and scalability
● Improve frontend
○ Improve performance, widget customization
○ Show daily/weekly/monthly trends for time series
○ Introduce other kinds of visualizations
● Integrate other public data sources
○ CityOS
○ Decidim public API
○ More data from ODI (demographic data, housing price data...)
15. Crowd-sourced
(public/private)
data
Integration with Barcelona pilots
IDIGITAL / BCNOW
PLATFORM
BCNNOW DASHBOARD
IOT PILOT INVOLVING
#CITIZENSENSE
Open
Democra
cy
Citizen
Sensing /
IoT
Privacy-aware
personalized
visualizations
Petition count + validation
Demographic
information
Data sovereignitiy
DATA COMMONS
16. References
Mirko Marras, Matteo Manca, Ludovico Boratto, Gianni Fenu, David Laniado (2018).
BarcelonaNow: Empowering Citizens with Interactive Dashboards for Urban Data Exploration.
In Proceedings of The Web Conference (WWW’18), Lyon, France, April 2018.
Online demo:
http://bcnnow.decodeproject.eu/
Contacts:
mirko.marras@ce.eurecat.org
david.laniado@eurecat.org
University
of Cagliari