Smart City Semantics - Data Analytics and Human Computation to understand the Living Land Use
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The document discusses the application of data analytics and human computation in smart cities to enhance understanding of land use through diverse data sources. It highlights the need for integrating geospatial data, using citizen science for data curation, and identifying correlations between different datasets. Key research questions focus on the effectiveness of combining human and computer efforts in geospatial data processing and empirical methods to detect real-time changes in urban environments.
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Smart City Semantics - Data Analytics and Human Computation to understand the Living Land Use
- 1. Smart City Semantics Data Analytics and Human Computation to understand the Living Land Use Irene Celinoand Gloria Re Calegari CEFRIEL Comitato Italo-Svizzero per la Geoinformatica – Como, 30-31/10/2014
- 2. Our Research GroupData Science "extraction of knowledge from data" Data modelling Data processing Data analytics Data visualizationWeb Science "interplay between Web and people" Data on the Web Human Computation Web-based ecosystems Mobile Web CEFRIEL Data / Web Science Research Group 2 Como, 2014/10/30 © CEFRIEL 2014 with specific expertise and skills in Semantic Web standards and technologies
- 3. Research applied to Smart City / Territory CEFRIEL Data / Web Science Research Group 3 Como, 2014/10/30 © CEFRIEL 2014 Data Science "extraction of knowledge from data" Geospatial data ontological modelling Geospatial data integration and interlinking Geospatial data retrieval Geospatial Data Analytics Geospatial data visualizationWeb Science "interplay between Web and people" Publication of geospatial data on the Web as Linked Data Location-based GWAPs (Human Computation approach) for geospatial data curation Location-based recommender systems
- 4. Smart City Semantics –Data Analytics Research question: Do diverse and heterogeneous data sources (referring to the same geospatial context) give the same “picture” of the city/territory? Methods: compare & contrast those data sources to discover “intrinsic” correlations with descriptive/predictive analytics CEFRIEL Data / Web Science Research Group 4 Como, 2014/10/30 © CEFRIEL 2014 Strong and statistically significant correlation between density of POIs (from Milano’s open data) and CORINE land cover (111 urban fabric) Spearman’s correlation=0,78 p-value=2e-16 Strong clustering similarity between call data records (from Telecom) and population distribution (from ISTAT) Rand index=0,77 Cohen’s kappa=0,81
- 5. Living Land Use: detecting/eliciting changes in an outdated dataset based on an up-to-date or real-time (big) dataset recording human activity "traces" Purpose: update an expensive dataset by using a cheaper datasetSample application: Living Land Use CEFRIEL Data / Web Science Research Group 5 Como, 2014/10/30 © CEFRIEL 2014 http://livinglanduse.cefriel.com
- 6. Smart City Semantics –Human Computation Research question: can citizen be successfully involved in a mixed human-computer geospatial data curation, processing and integration workflow? Methods: citizen involvement through Human Computation or Citizen Science to collect and validate geospatial datasets CEFRIEL Data / Web Science Research Group 6 Como, 2014/10/30 © CEFRIEL 2014
- 7. Sample applications: Urban Games Urban Games: collection and quality assessment of urban data through location-based Games with a Purpose CEFRIEL Data / Web Science Research Group 7 Como, 2014/10/30 © CEFRIEL 2014 http://bit.ly/u-website http://bit.ly/urbanmatch
- 8. Semantics… what? Smart City / Territory Semantics Big Data sense-makingabout a geospatial context Spatio-temporal characteristics of data as integration points between diverse and heterogeneous sources Understanding the different “pictures” of the city hidden in data Detecting the living land use from real-time/streaming data Fostering a Citizen Computation approach to interleave open data, closed data and volunteered geographic information Some “semantic” challenges: Data heterogeneity(formats and granularity) Data interoperability(standards, models and ontologies) 4 V’s of Big Data (Volume, Velocity, Variety and Veracity) Geospatial decision-makingsupport CEFRIEL Data / Web Science Research Group 8 Como, 2014/10/30 © CEFRIEL 2014
- 9. References Irene Celino: "Geospatial dataset curation through a location-based game", Semantic Web Journal, DOI: 10.3233/SW-130129, IOS Press, (to appear). Irene Celino and Gloria Re Calegari: "Geo-statistical Exploration of Milano Datasets", 2nd International Workshop on Semantic Statistics (SemStats), co-located with the 13th International Semantic Web Conference (ISWC), 2014. Irene Celino and Alessio Carenini: "Towards a Semantic City Service Ecosystem", in: Proceedings of the 5th Workshop on Semantics for Smarter Cities, co-located with the 13th International Semantic Web Conference (ISWC), 2014. Irene Celino and Spyros Kotoulas: “Smart Cities”, Guest Editors’ Introduction, Special Issue on Smart Cities, IEEE Internet Computing, Volume 17, Issue 6, pp.8-11, DOI: 10.1109/MIC.2013.117, 2013. Irene Celino: "Human Computation VGI Provenance: Semantic Web-based Representation and Publishing", IEEE Transactions on Geoscience and Remote Sensing, Volume 51, Issue 11, pp. 5137-5144, DOI: 10.1109/TGRS.2013.2252015, 2013. Irene Celino: "Location Based Games for Citizen Computation", in: Handbook of Human Computation, DOI: 10.1007/978-1-4614-8806-4_25, Springer, 2013. Irene Celino, Simone Contessa, Marta Corubolo, Daniele Dell'Aglio, EmanueleDella Valle, Stefano Fumeo and Thorsten Krüger: “Linking Smart Cities Datasets with Human Computation –the case of UrbanMatch”, Proceeding of the 11th International Semantic Web Conference, ISWC 2012, Part II, Springer LNCS 7650, pp. 34–49, 2012. Irene Celino, Dario Cerizza, Simone Contessa, Marta Corubolo, Daniele Dell'Aglio, EmanueleDella Valle and Stefano Fumeo: "Urbanopoly –a Social and Location-based Game with a Purpose to Crowdsourceyour Urban Data", Proceedings of the 4th IEEE International Conference on Social Computing, Workshop on Social Media for Human Computation (SoHuman), pp. 910-913, DOI: 10.1109/SocialCom-PASSAT.2012.138, 2012. CEFRIEL Data / Web Science Research Group 9 Como, 2014/10/30 © CEFRIEL 2014
- 10. Thanks! Questions? Irene Celino –CEFRIEL, Politecnico di Milano email: [email protected]–web: http://swa.cefriel.it Comitato Italo-Svizzero per la Geoinformatica – Como, 30-31/10/2014