Towards Linked Data and ontology development for the semantic enrichment of volunteered geo-information

Transcription

1 AGILE Link-VGI workshop, Helsinki 14 June 2016 Towards Linked Data and ontology development for the semantic enrichment of volunteered geo-information Rob Lemmens University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC) Enschede, The Netherlands Gilles Falquet, Claudine Métral University of Geneva, Faculty of economics and social sciences, Geneva, Switzerland {Gilles.Falquet; 1

2 ENERGIC Project Objectives - The ENERGIC project (European Network Exploring Research into Geospatial Information Crowdsourcing: software and methodologies for harnessing geographic information from the crowd; COST Action IC1203) Finding new solutions for the exploitation, integration and application of user generated geo-information. Working groups: 1. Societal and human aspects of VGI, 2. Spatial data quality and infrastructures and 3. Data mining, semantics and VGI. Links to COST Action TD1202 Mapping and the citizen sensor Deliverable: Open and updatable repository of VGI analysis and integration tools and methods, literature and case studies. Ontology serves as semantic backbone. 2

3 Informal and formal semantic reference spaces From: Rob Lemmens, Gilles Falquet, Stefano De Sabbata, Bin Jiang, Benedicte Bucher (2016) Querying VGI by semantic enrichment. Chapter in: Capineri, C. et al. (Eds.) European handbook of crowdsourced geographic information. Ubiquity Press.

4 From informal to formal Keywords (Tags) Ontologies stadium Stade Sylvio Cator football shelter Co-occurence disaster Ouest damage palace Haiti Frorse river river road country Geographic feature government office department building stadium disaster damage shelter Port-auprince Carrefour city

5 Semantic enrichment with ENERGIC VGI ontology VGI system: OpenStreetMap Is of Type VGI publication 5

6 Linked Data RDF triples From: Kelvin Mutunga MSc thesis, Univ of Twente, March 2016

7 Linked Open Data cloud 7

8 Ontologies & Linked Data From: Dongpo Deng Terra Incognita 2011

9 ENERGIC VGI Ontology - Objectives 1. Common understanding of VGI concepts (e.g., for research, outreach and education) delimiting the field - broad coverage, human-readable definitions 2. Create applications and database schema for the development of new VGI applications - centered on VGI data structures 3. Usage of ontology of tasks for evaluating of data quality - centered on tasks 4. Semantic enrichment of VGI-based systems and indexing literature for VGI source discovery and integration - rich set of properties to describe resources 5. Create relationships between VGI and other domains, such as GIS, SDI, etc. 9

10 ENERGIC VGI Ontology ENERGIC Book (all project partners) Manual keyword marking (team) Cleaning & Sorting (organisers) Workflow Comparison Automated keyword generation (organisers) Creation of toplevel concepts with WebProtege (organisers) Addition of lowlevel concepts with WebProtege (team) Ontology instantiation exercise with yed graph editor (Lisbon participants) Proposals for ontology tuning with yed graph editor (Lisbon participants) Ontology instantiation by creating linked data with XSLT (organisers) Ontology tuning with WebProtege (organisers) Demonstration of use by linked data query and exploration (organisers) 10

11 ENERGIC VGI Ontology Cleaned keyword list 11

12 From key terms to organized concepts remove single-word terms (e.g. ajax) normalize the terms (replace "of", "ing" forms) > 700 classes remove n-word terms when the last word appears only once group the n-word terms under their last word Thing 700 -> 120 classes content subclassof user_generated_content referenced_content georeferenced_content etc. quality subclassof air_quality spatial_data_quality intrinsic_quality self-produced_content 12

13 From key terms to organized concepts align with WordNet concepts add common superclasses from WordNet WordNet Thing 120 -> ~40 classes attribute method activity accuracy consistency... heterogeneity crowdsourcing. mining.... extraction observation 13

14 ENERGIC VGI Ontology Collaborative editing with WebProtege 14

15 ENERGIC VGI Ontology Instantiation with yed graph editor 15

16 From E-R diagrams to RDF... 16

17 Linked Open Data cloud 17

18 Visualization with WebVOWL 1

19 Visualization with AllegroGraph - Gruff 1

20 Exploratory querying with Linked Data 2

21 ENERGIC Datathon - Demonstrate the potential of transformations of data to knowledge: Challenges: 1. Analyse spatio-temporal VGI sources (Telecom, Tourist, Transport) with other VGI and authoritative data 2. Expanding and test ENERGIC ontology a. Create relevant VGI system descriptions and detailed VGI publication references based on the ENERGIC ontology and publish these descriptions online. b. Create and execute (Geo)SPARQL queries. 3. Align the ENERGIC ontology with other ontologies, such as Geonames, OSM and DBPedia -> create a triple store execute (Geo)SPARQL queries. 4. Triplify VGI and connect to other Linked Data. Input: VGI ontology and other ontologies, VGI sources Deliverable (31 July 2016): Report and recorded pitch on results, sources, methods, novelty. Prize: Trip to the final COST Energic meeting in London on October

22 VGI Reuse 22

23 VGI Reuse Findable Downloadab le/scrapable Available via webservice or API Semantically enriched with VGI ontology Metadata is aggregated via a VGI portal * ** *** **** 23

24 AGILE Link-VGI workshop, Helsinki 14 June 2016 Towards Linked Data and ontology development for the semantic enrichment of volunteered geo-information Rob Lemmens University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC) Enschede, The Netherlands Gilles Falquet, Claudine Métral University of Geneva, Faculty of economics and social sciences, Geneva, Switzerland {Gilles.Falquet; 24

25 Instances live in classes haspart living_room_4 working house_1 hascolor bedroom_22 eating sleeping house_6 haspart room_3 hasfunction House yellow blue red Room Activity Color 25

26 Another notation haspart Room living_room_4 Activity working House house_1 House house_6 Color yellow hascolor haspart Color blue Color red Room bedroom_22 Room room_3 hasfunction Activity eating Activity sleeping 26

27 Classes form an inclusion hierarchy Activity thinking sleeping drinking Thing subclassof Activity football subclassof subclassof Sport hiking Sport Artistic Activity subclassof Outdoor Sport 27

28 Individuals and classes reside at different, clearly separated, levels Activity Sport Outdoor Sport subclassof subclassof type CLASSES a difficult ontology design decision: where to put this limit? type skiing handball type INSTANCES 28

29 Usability analysis 2

30 Usability analysis 3