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Team 05 linked data generation

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TEAM 05

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Team 05 linked data generation

  1. 1. TEAM 2.5: Publication of linked data from pan- European geospatial datasets INSPIRE Conference, Kehl, 5th Sept 2017
  2. 2. TEAM MEMBERS • Dr. Raul Palma : coordinator of Semantic Technologies in the Network Services division at Poznan Supercomputing and Networking Center (PSNC), Poland. • Soumya Brahma: data analyst in the Network Services division at PSNC Technical support, use cases analysis and monitoring, data analysis and integration. • Dmitrij Kozuch • Raitis Berzins • Acknowledments to Dr. Peter Haase, and Dr. Johannes Trame (Metaphacts) INSPIRE Conference, Kehl, 5th Sept 2017
  3. 3. SUPPORTING PROJECTS • Databio - Data-Driven Bioeconomy The main goal of the DataBio project is to show the benefits of Big Data technologies in the raw material production from agriculture, forestry and fishery for the bioeconomy industry to produce food, energy and biomaterials responsibly and sustainably. DataBio proposes to deploy a state of the art, big data platform on top of the existing partners’ infrastructure and solutions. • One of the main tasks of DataBio relates to Big Data Variety Management, Storage, Linked Data and Queries INSPIRE Conference, Kehl, 5th Sept 2017 H2020 - ICT-15-2016-2017; Big Data PPP: Large Scale Pilot actions in sectors best benefitting from data-driven innovation.
  4. 4. INPUT DATA • Open Land Use (open dataset): is a composite dataset intended to create detailed land- use maps of various regions based on certain pan-Europen datasets such as CORINE Landcover, UrbanAtlas enriched by available regional (http://sdi4apps.eu/open_land_use/) • Open Transport Map (open dataset): Allows routing and visualization of traffic volumes of the whole EU. The underlying data come from OpenStreetMap and are accessible in a scheme compatible to INSPIRE Transport Network (http://opentransportmap.info/ ) • Smart Point of Interest (open dataset): Open and seamless SPOI data set, which is based on Linked data principles, contains over 27 million Points of Interest important for tourism from around the world. (http://sdi4apps.eu/spoi/ ) • Other datasets include: Urban atlas, Corine, Hilucs INSPIRE Conference, Kehl, 5th Sept 2017
  5. 5. INPUT DATA INSPIRE Conference, Kehl, 5th Sept 2017
  6. 6. USED SOFTWARE/TOOLS • D2RQ for transforming Relational Databases as Virtual RDF Graphs • RDF for the representation of data • Ontologies providing the underlying vocabulary and relations • Virtuoso for storing the semantic datasets • Sparql for querying semantic data • Silk for discovery of links • Hslayers NG for visualisation of data • Metaphactory for visualisation of data INSPIRE Conference, Kehl, 5th Sept 2017
  7. 7. PROJECT IDEA AND RESULTS • The project idea was to integrate relevant datasets and publish them as linked data. The following tasks were performed: • Massive transformation of data into semantic format (RDF) and collection of exiting ones • Loading datasets in Virtuoso • Linking of datasets • Query building • Visualisation of data • Results summary: • Creation of ontologies (open) • Virtuoso instance with over 700 million triples (open) • Sparql endpoint (open) • Three different interfaces for navigating and visualising the dataINSPIRE Conference, Kehl, 5th Sept 2017
  8. 8. NEW DATASETS * Selected subsets INSPIRE Conference, Kehl, 5th Sept 2017 Dataset Name Graph in FOODIE endpoint Source Triples OLU** http://w3id.org/foodie/olu# Transformed from PostgreSQL 127,925,971 SPOI http://www.sdi4apps.eu/poi.rdf Source provided by WRLS, modified and fixed before loading 381,393,555 NUTS http://nuts.geovocab.org/ Open Source 316,238 OTM*** http://w3id.org/foodie/otm# Transformed from PostgreSQL 154,340,611 Dataset Name Graph in FOODIE endpoint Source Triples Hilucs classification http://w3id.org/foodie/hilucs# Transformed from PostgreSQL 397 Urban Atlas* http://w3id.org/foodie/atlas# Transformed from PostgreSQL 19,606,025 Corine* http://w3id.org/foodie/corine# Transformed from PostgreSQL 16,777,533 Eurovoc http://foodie-cloud.org/eurovoc Open Source 425,667 Emergel http://foodie-cloud.org/emergel CTIC 256,239 The ontologies generated are (available from https://github.com/FOODIE-cloud/ontology
  9. 9. Interfaces • Sparql endpoint: https://www.foodie-cloud.org/sparql INSPIRE Conference, Kehl, 5th Sept 2017
  10. 10. Interfaces • Faceted search browser: http://www.foodie-cloud.org/fct/ INSPIRE Conference, Kehl, 5th Sept 2017
  11. 11. Interfaces • Map visualisation: http://ng.hslayers.org/examples/olu_spoi/?hs_panel=info&hs_x=1607799.902082933&hs _y=6462976.717926565&hs_z=16&visible_layers=Base%20layer;Land%20use%20parcels INSPIRE Conference, Kehl, 5th Sept 2017
  12. 12. Interfaces • Map visualisation: http://ng.hslayers.org/examples/olu_spoi/?hs_panel=info&hs_x=1607799.902082933&h s_y=6462976.717926565&hs_z=16&visible_layers=Base%20layer;Land%20use%20parcels INSPIRE Conference, Kehl, 5th Sept 2017
  13. 13. Interfaces • Metaphactory (https://foodie.grapphs.com/resource/Start ) INSPIRE Conference, Kehl, 5th Sept 2017
  14. 14. Interfaces • Metaphactory (https://foodie.grapphs.com/resource/Start ) INSPIRE Conference, Kehl, 5th Sept 2017
  15. 15. INSPIRE/GEOSS/COPERNICUS/ RELEVANCE • This work demonstrate the potential usages and benefits of linked data with geospatial dimension • The work exploits results from Copernicus and INSPIRE • The datasets generated are compliant with INSPIRE INSPIRE Conference, Kehl, 5th Sept 2017
  16. 16. REUSE • The results of the work will be exploited in DataBio project, and will serve as showcase for pilots on the potential usage of linked data, and how it could be integrated and used with their pilot data • The approach, and results of this work will be leveraged and extended for task related to Big Data Variety Management, Storage, Linked Data and Queries • The generated datasets could be reused in other projects dealing with geospatial related data and semantic technologies INSPIRE Conference, Kehl, 5th Sept 2017
  17. 17. BUSINESS • In future the applications on top of the linked datasets can become commercial services for different stakeholders. For instance • Real estate agencies could use the datasets to show the land parcels that you are on sale, that lie near big highways and have school nearby • Tourist agencies can show hotels that lie near some point of interest and have direct connection to airports or train stations • Farmers can see the most dense land parcels nearby to offer their products INSPIRE Conference, Kehl, 5th Sept 2017
  18. 18. FOLLOW-UP • We are ready to continue with follow up actions. • We had people interested from the Institute for Applied Informatics in Leipzig • We will transform and link datasets from pilots of FOODIE project, to demonstrate how farming data compliant with FOODIE data model (that in turn is compliant with INSPIRE) can be also linked with these datasets. This work will be presented in the Linked Data Workshop in Agriculture in Berlin. INSPIRE Conference, Kehl, 5th Sept 2017

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