Linked Data - A Paradigm Shift for Geographic Information Science

The Linked Data paradigm has made significant inroads into research and practice around spatial information and it is time to reflect on what this means for GIScience. Technically, Linked Data is just data in the simplest possible data model (that of triples), allowing for linking records or data sets anywhere across the web using controlled semantics. Conceptually, Linked Data offers radically new ways of thinking about, structuring, publishing, discovering, accessing, and integrating data. It is of particular novelty and value to the producers and users of geographic data, as these are commonly thought to require more complex data models. The paper explains the main innovations brought about by Linked Data and demonstrates them with examples. It concludes that many longstanding problems in GIScience have become approachable in novel ways, while new and more specific research challenges emerge.

[1]  Diego Reforgiato Recupero,et al.  Geolinked Open Data for the Municipality of Catania , 2014, WIMS '14.

[2]  Dean Allemang,et al.  Chapter 2 – Semantic Modeling , 2008 .

[3]  Krzysztof Janowicz,et al.  spatial@linkedscience - Exploring the Research Field of GIScience with Linked Data , 2012, GIScience.

[4]  Amit P. Sheth,et al.  Don't like RDF reification?: making statements about statements using singleton property , 2014, WWW.

[5]  Krzysztof Janowicz,et al.  The role of space and time for knowledge organization on the Semantic Web , 2010, Semantic Web.

[6]  Aldo Gangemi,et al.  Ontology Design Patterns for Semantic Web Content , 2005, SEMWEB.

[7]  Dean Allemang,et al.  Semantic Web for the Working Ontologist - Effective Modeling in RDFS and OWL, Second Edition , 2011 .

[8]  Daniel Lathrop,et al.  Open Government: Collaboration, Transparency, and Participation in Practice , 2010 .

[9]  Catherine Dolbear,et al.  Linked Data: A Geographic Perspective , 2013 .

[10]  Yaser A. Bishr,et al.  Overcoming the Semantic and Other Barriers to GIS Interoperability , 1998, Int. J. Geogr. Inf. Sci..

[11]  James Cheney,et al.  PROV-O: The PROV ontology:W3C recommendation 30 April 2013 , 2013 .

[12]  Tomi Kauppinen,et al.  Linked Brazilian Amazon Rainforest Data , 2014, Semantic Web.

[13]  Christoph Stasch,et al.  Future SDI - Impulses from Geoinformatics Research and IT Trends , 2012, Int. J. Spatial Data Infrastructures Res..

[14]  Simon Scheider,et al.  Encoding and Querying Historic Map Content , 2014, AGILE Conf..

[15]  Dave Kolas,et al.  Enabling the geospatial Semantic Web with Parliament and GeoSPARQL , 2012, Semantic Web.

[16]  Werner Kuhn,et al.  Linked Data and Time - Modeling Researcher Life Lines by Events , 2013, COSIT.

[17]  Karl Aberer,et al.  Enabling Query Technologies for the Semantic Sensor Web , 2012, Int. J. Semantic Web Inf. Syst..

[18]  Barry Smith,et al.  Sixteen days. , 2003, The Journal of medicine and philosophy.

[19]  G. Damschen,et al.  Sixteen days? A reply to B. Smith and B. Brogaard on the beginning of human individuals. , 2006, The Journal of medicine and philosophy.

[20]  Eero Hyvönen,et al.  Modeling and Reasoning About Changes in Ontology Time Series , 2007, Ontologies.

[21]  David M. Shotton,et al.  Provenance and Linked Data in Biological Data Webs , 2008, LDOW.

[22]  J. Goodwin,et al.  Geographical Linked Data: The Administrative Geography of Great Britain on the Semantic Web , 2008 .

[23]  Simon Scheider,et al.  Making the Web of Data Available Via Web Feature Services , 2014, AGILE Conf..

[24]  Max J. Egenhofer,et al.  Changes in Topological Relations when Splitting and Merging Regions , 2006 .

[25]  David M. Shotton,et al.  CiTO, the Citation Typing Ontology , 2010, J. Biomed. Semant..

[27]  Deborah L. McGuinness,et al.  When owl: sameAs Isn't the Same: An Analysis of Identity in Linked Data , 2010, SEMWEB.

[28]  Deborah L. McGuinness,et al.  PROV-O: The PROV Ontology , 2013 .

[29]  Werner Kuhn,et al.  Trust and Reputation Models for Quality Assessment of Human Sensor Observations , 2013, COSIT.

[30]  Stefania Bandini,et al.  Determining relevance of imprecise temporal intervals for cultural heritage information retrieval , 2010, Int. J. Hum. Comput. Stud..

[31]  Claudio Gutiérrez,et al.  Temporal RDF , 2005, ESWC.