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A general introduction of GeoKnow European Project

A general introduction of GeoKnow European Project

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  • 1. Creating Knowledge out of Interlinked Data GeoKnow Making the Web an Exploratory Place for Spatial Data Collaborative Project 2012-2015 in Information and Communication Technologies Project No. 318159 Start Date 01/12/2012 EU-FP7 LOD2 Project Overview . 02.09.2010 . Page 1 http://geoknow.eu http://lod2.eu
  • 2. Making the Web an Exploratory Place for Geospatial Data The Spatial Data Web: Achievements and Challenges  Web - a global, distributed platform for data, information and knowledge integration  Exposing, sharing, and connecting pieces of data on the Semantic Web using RDF  Large Spatial Databases (OpenStreetMaps, Google Maps etc.) integrated in many applications Achievements Challenges 1. Extension of the Web with a data commons (currently amounting to 25 Bn. facts) 2. Vibrant, global RTD community 3. Industrial uptake begins (e.g. BBC, Thomson Reuters, Eli Lilly) 4. Emerging governmental adoption in sight 5. Establishing Linked Data as a deployment path for the Semantic Web. EU-FP7 GeoKnow. 21.01.2013 . Page 2 1. Big Data: Large volumes of frequently updated data 2. Coherence: Relatively few, expensively maintained links 3. Quality: partly low-quality data and inconsistencies 4. Data Consumption: largescale processing, schema mapping and data fusion for enterprises 5. Simplicity: easily create and deploy spatial semantic web applications http://geoknow.eu
  • 3. Making the Web an Exploratory Place for Geospatial Data GeoKnow in a Nutshell WP5 Metrics Supply Chain Management Data WP3 Spatial Linked Data Linked Data WP6 Spatial Authoring / Browsing Tools Fusing E-Commerce Data Faceted Browsing Interlinking … further use cases … Spatial Widgets protected public Adaptive Authoring Aggregation Open Data / LOD Cloud WP4 SPARQL / GeoSPARQL WP1 Linked Data Access GeoKnow Generator Spatial Knowledge Store & Co-Evolution WP2 Triples Stores RDF Views GIS Databases EU-FP7 GeoKnow. 21.01.2013 . Page 3 http://geoknow.eu
  • 4. Making the Web an Exploratory Place for Geospatial Data Work Packages WP7: Dissemination community building Exploitation & standards, fertili sation WP2: Semantics based geospatial data management WP3: Spatial knowledge aggregation, fusing & quality assessment WP4: Spatial-semantic exploration, visualization, an alysis & authoring interfaces WP8: Project Management WP1: Requirements, design, prototyping, interfaces definition, component integration and GeoKnow Generator WP5:GeoKnow for Supply chain management EU-FP7 GeoKnow. 21.01.2013 . Page 4 WP6:GeoKnow for E-Commerce http://geoknow.eu
  • 5. Making the Web an Exploratory Place for Geospatial Data Consortium Institute for Applied Informatics Germany OpenLink Software United Kingdom Brox Germany Ontos Switzerland Unister Germany Athena Research and Innovation Center Greece EU-FP7 GeoKnow. 21.01.2013 . Page 5 http://geoknow.eu
  • 6. Making the Web an Exploratory Place for Geospatial Data WP1: Requirements, Design, Benchmarking, Component Integration     Requirements collection and analysis Continuous Benchmarking GeoKnow Generator design and development Component integration GeoKnow Generator  Different data sources: private, pubic, RDF, nonRDF, static, streams.  Performance monitoring and Secured data in all layers  Data enrichment and continuous quality assurance  New visualisation paradigms EU-FP7 GeoKnow. 21.01.2013 . Page 6 http://geoknow.eu
  • 7. Making the Web an Exploratory Place for Geospatial Data WP2: Semantics-Based Geospatial Information Management Objective: Develop the storage, query execution and optimization capabilities of the storage engine to meet the Geospatial requirements of the project. Tasks: • Geospatial query optimization - The cost model for geospatial queries will merge query optimization and execution by partially executing joins during optimization • Geospatial clustering - adds geospatial clustering support for rearranging physical storage according to geospatial criteria • Distributed geospatial capabilities – Showcase advances in scale-out capabilities with large geospatial data, e.g. all of OSM, with heavy online query load and concurrent updates. • Geospatial problem solving – Implementation of complex application logic coresident with the data, required for supply chain route planning. • Exposing INSPIRE data as Linked Data - provide technical solutions and tools to expose INSPIRE data and metadata as geospatial Linked Data. EU-FP7 GeoKnow. 21.01.2013 . Page 7 http://geoknow.eu
  • 8. Making the Web an Exploratory Place for Geospatial Data WP3: Spatial Knowledge Aggregation, Fusing & Quality Assessment Combine crowdsourced /open and closed spatial RDF data to produce data of increased coverage, accuracy, semantic enrichment, timeliness and value Leverage the wisdom of crowds in the geospatial Data Web 1. Spatial knowledge mapping Motivation: How do we interlink spatial and non-spatial RDF data? Goal: Lift implicit geographic references in RDF data and interlink with spatial and non-spatial data, transform geospatial data to RDF with emphasis on big, evolving, geospatial data  e.g. interlink RDF data with DBpedia, Geonames  e.g. transform typical shapefiles to RDF and interlink with other data  e.g. continuously process and transform OpenStreetMap data (earth-scale, thousands revisions/day) to RDF EU-FP7 GeoKnow. 21.01.2013 . Page 8 http://geoknow.eu
  • 9. Making the Web an Exploratory Place for Geospatial Data WP3: Spatial Knowledge Aggregation, Fusing & Quality Assessment 2. Spatial knowledge fusion Motivation: How do we combine different spatial RDF data, with differences in RDF representation, metadata and geometries for the same geographical features? Goal: Develop algorithms to fuse geospatial RDF data: map different RDF representations of geometry, merge metadata associated with spatial objects, combine representations of relations between spatial objects  e.g. identify same POIs from different data sets with differences in location (e.g. coordinates), metadata (e.g. name, working hours), and relations (e.g. within a mall, south of a square) 3. Quality-aware spatial knowledge aggregation Motivation: Volunteers produce valuable spatial knowledge in the Web. How can we guide them towards purposeful contributions without restricting them, and consolidate their efforts? Goal: Develop algorithms to semantically consolidate categories and produce a community-driven consolidation process  e.g. category cretan_cuisine becomes a subcategory of greek_cuisine  e.g. OpenStreetMap users consolidate greek_cuisine with greek_restaurant and cretan_menu EU-FP7 GeoKnow. 21.01.2013 . Page 9 http://geoknow.eu
  • 10. Making the Web an Exploratory Place for Geospatial Data WP3: Spatial Knowledge Aggregation, Fusing & Quality Assessment 4. Metrics for volunteered (crowdsourced) geographic information Motivation: Crowdsourced geoinformation can surpass the quality of official/commercial /closed maps. How do we apply and leverage this knowledge source? Goal: Define metrics to compare different maps from user-contributed geospatial information modeled in RDF (coverage, precision, pertinence, timeliness)  E.g. compare coverage of a specific category between two regions of a city 5. Quality assessment for geoinformation Motivation: We have fused crowdsourced geoinformation with official/commercial/closed maps. How do we measure the quality of this value added data source? Goal: Define, extend, adapt quality metrics for spatial RDF, and develop methods to detect/repair errors and enrichment.  E.g. produce a map with more/accurate POIs based on OSM data EU-FP7 GeoKnow. 21.01.2013 . Page 10 http://geoknow.eu
  • 11. Making the Web an Exploratory Place for Geospatial Data WP4: Spatial-semantic Browsing, Visualization, Authoring Interfaces 1. Spatial-semantic visualization and exploration Motivation: Given spatial RDF datasets, how to quickly generate previews and easily turn them into interactive, user friendly, visualizations and widgets (making use of vector and raster data)? Goal: Develop reusable user interface components for display of geographic feature information on a map and as forms. Leverage re-use of vocabularies by means of default and customizable presentations (e.g. for hotels, events, routes, SC network, …) Furthermore develop library components for dealing with different RDF representations and level of detail of geographic data. Offer keyword and facetted search. EU-FP7 GeoKnow. 21.01.2013 . Page 11 http://geoknow.eu
  • 12. Making the Web an Exploratory Place for Geospatial Data WP4: Spatial-semantic Browsing, Visualization, Authoring Interfaces 2. Adaptive spatial-semantic authoring and curation Motivation: There are many reasons for the need to edit RDF data, however without the right tool this is often very cumbersome; Examples: • After displaying recently geocoded data on a map errors become obvious. • A use case requires introducing new labels to POIs that include country and ZIP code Goal: Develop re-usable and composable widgets for supporting single editing, batch editing as well as reconciliation of spatial RDF data. The requirement for authoring can often stem from data quality issues. As such there will also be UI components offering access to (some) of the functionality provided by the quality assurance tools. 3. Spatial social networking Motivation: Social networking is ubiquitous. Users and organisations need to be able to register for relevant updates. This applies to both projects managed in the GeoKnow Generator itself, as well as generated applications. Goal: Enhance the GeoKnow Generator with subscription, filtering, and notification mechanisms based on the Open-Social standard. Furthermore, implement adapters to popular social networks, such as Facebook, Google+, Twitter, LinkedIn. EU-FP7 GeoKnow. 21.01.2013 . Page 12 http://geoknow.eu
  • 13. Making the Web an Exploratory Place for Geospatial Data WP4: Spatial-semantic Browsing, Visualization, Authoring Interfaces 4. Public-private spatial data co-evolution Motivation: Example: A tourism portal combines a private hotel database with public OpenStreetMap data for becoming capable of answering queries such as “find all hotels near beaches”. For convenience, users can fix mistakes on the portal. However, when the hotel database or OpenStreetMap evolves (re-import or incremental updates), how can the prior fixes be retained? Goal: Identify types of enterprise RDF data synchronization workflows, define and implement tools that support them. This will include ETL processes, query federation, transformation/patching of data and change set propagation. EU-FP7 GeoKnow. 21.01.2013 . Page 13 http://geoknow.eu
  • 14. Making the Web an Exploratory Place for Geospatial Data WP5: Spatial Linked Data in the Supply Chain • Logistics companies face big-data challenges when dealing with complex international tiered structures • Information integration is critical for effective enterprise processes • Geospatial linked data may help to derive a unified collaborative spatial view on important parts of a logistic process • Linked data applications make different private supply chain data points available and connect these layers with intelligent and secure APIs • Close to real time observation of information flows (e.g. materials, products, other supply chain assets) • May improve supply chain performance • Quick integration of additional supply chain partners and information layers EU-FP7 GeoKnow. 21.01.2013 . Page 14 http://geoknow.eu
  • 15. Making the Web an Exploratory Place for Geospatial Data WP6: GeoKnow for E-Commerce Same Challenges of E-Commerce Applications and Semantic Web Community • independent, different data providers • integration of entities without unique identifiers • data sets are growing rapidly • match user demand with technology push  Validation of GeoKnow results within e-Commerce scenario: this use case is the perfect match for evaluation and research on semantic web challenges Objectives: Answer central questions: • What kind of new products is my customer likely willing to buy? • Which geographical regions are most suitable for a special event? • How to integrate internal data with the open linked data by interlinking with geographical data, social network structures from many different sources? • How to provide the information to a user via search applications? EU-FP7 GeoKnow. 21.01.2013 . Page 15 http://geoknow.eu
  • 16. Making the Web an Exploratory Place for Geospatial Data WP7: Dissemination, Community Building, Exploitation & Standards Dissemination • www.geoknow.eu • Flyer and stickers • Social Networks • Community Groups • Conference presenting • Web-based showcases Exploitation • Open source • GeoKnow generator exploitation in further use cases Standardization • W3C SPARQL Working Group • W3C Relational Data Bases to RDF Working Group • W3C Semantic Web Deployment Working Group EU-FP7 GeoKnow. 21.01.2013 . Page 16 http://geoknow.eu
  • 17. Making the Web an Exploratory Place for Geospatial Data WP8: Project Management Project  Instrument: Collaborative Project (STREP)  Objective: Intelligent Information Management  Call: FP7-ICT-2011.4.4  Duration: 12/2012 – 12/2015 Means  Total Budget: 4,1 M€  Total Funding: 2,95 M€  Total Resources: 495 PM  Partners: 6 EU-FP7 GeoKnow. 21.01.2013 . Page 17 http://geoknow.eu
  • 18. Making the Web an Exploratory Place for Geospatial Data Contact Address Coordinator Institute for Applied Informatics University of Leipzig Neumarkt 20 04109 Leipzig Germany Dr Jens Lehmann Scientific Project Leader Phone:+49 (341) 97-32260 Fax: +49 (341) 97-32329 Email: lehmann@informatik.uni-leipzig.de Web: http://jens-lehmann.org Phone: +49 341 3928738 0 Fax: +49 341 3928738 9 Sandra Prätor Project Manager Phone:+49 (341) 97-32332 Fax: +49 (341) 97-32329 Email: praetor@informatik.uni-leipzig.de http://aksw.org/SandraPraetor.html Thanks for your attention! LOD2 Title . 02.09.2010 . Page 18 http://geoknow.eu http://lod2.eu