Linked Data Practices for the Geospatial Community

Linked Data Practices for the Geospatial Community

Talk subtitle

Presented at GEOSS Workshop on ClimateBoulder Colorado, 23 September 2011Stephan Zednik, [email protected] / Tetherless World Constellation

Value Proposition of Linked Data

• Discover– Web resources ‘easy’ to generate and link to

• Access– Leverage HTTP methods

• Integrate– RDF is a standard mechanism for specifying the existence

and meaning of connections between items described in the data

• Use– Web standards for data access and representation simplify

data consumption while providing (extreme) expressivity

Principles of Linked Data

There are 4 principle expectations (rules) for Linked Data

1. Use URIs as names for things

2. Use HTTP URIs so that people can look up those names

3. When someone looks up a URI, provide useful information, using the standards (RDF*, SPARQL)

4. Include links to other URIs, so that they can discover more things

World Wide Web of Data!

Linked Data Languages

• SKOS (Simple Knowledge Organizational System)– Thesauri, Taxonomies, Topical Hierarchies

• RDFS (RDF Schema)– Vocabularies

• OWL (Web Ontology Language)– Ontologies

• RDFS+– RDFS + Subset of OWL

Reuse

• Key factor in re-usability of data: structure

• Regular and structured is– Easier to find– Easier to make tools for– More likely to be referenced

• and therefore beneficiary of network effect

Re-use Concerns

• Usage & Uptake• Maintenance & Governance• Coverage• Expressivity• Modularity

Example: SWEET 2 Dependency Graph

Finding Vocabularies

• No current definitive directory to find existing vocabularies– SchemaWeb, SchemaCache, Swoogle

• Statistics on usage of vocabularies in the wild– Section 2.3 of the State of the LOD Cloud– http://lod-cloud.net/state#terms

Using Vocabularies

• If suitable terms are found, they should be re-used– Maximizes potential for consumption– Network effect on re-used vocabulary

• New terms should be mapped to well-established existing vocabularies– Standards bodies useful to establish &

promote vocabularies – Network effect long-term driving factor

• Example: FOAF

W3C Geo Vocabulary

• Basic RDF vocabulary that provides a namespace for representing latitude, longitude, and other spatially located things using WGS84 as a reference datum– http://www.w3.org/2003/01/geo/– Wide usage, but far too simple for GIS tools

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#"> <geo:Point> <geo:lat>55.701</geo:lat> <geo:long>12.552</geo:long> </geo:Point></rdf:RDF>

OGC GeoSPARQL

• Includes– RDF/OWL Vocabulary for representing

spatial information– A set of functions for spatial computations– A set of query transformation Rules

• Expressivity for GIS tool requirements• http://www.opengeospatial.org/projects/

groups/geosparqlswg

OGC GeoSPARQL RDF

Discovering Linked Data

• ‘Standard’ discovery of linked data is via other linked data…

• OpenSearch– Version 1.1 Geo extension (very basic)– Semantics?

• DataCasting– ProductCasting– InventoryCasting

• ServiceCasting

Querying Linked Data

• SPARQL Endpoint– Requires understanding of structure– Generally domain agnostic

• Faceted Browsing– Pelorus

• http://clarkparsia.com/pelorus– S2S

• http://tw.rpi.edu/web/project/sesf/workinggroups/s2s

• Supports Widgets

SPARQL Endpoint Web Browser

Pelorus

S2S Faceted Browser

Services & Linked Data• SOAP Web Services and Linked Data are not

complementary– Document exchange vs Web of Data– SOAP ignores HTTP access semantics

• REST (Representational State Transfer)– HTTP as a mechanism for retrieval of resource

representations exposed via URIs– Resource Orientated Architecture (ROA)– Stateless interactions

• Linked Data and RESTful services can be complementary– Will take care in design

Questions?

• Stephan Zednik, [email protected]

References• Tom Heath and Christian Bizer (2011) Linked Data: Evolving

the Web into a Global Data Space (1st Edition) Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool.– DOI: 10.2200/S00334ED1V01Y201102WBE001– http://linkeddatabook.com/editions/1.0/

• GeoSPARQL SWG– http://www.opengeospatial.org/projects/groups/geosparqlswg

• JPL Datacasting– http://datacasting.jpl.nasa.gov/

• Pelorus– http://clarkparsia.com/pelorus

• S2S– http://tw.rpi.edu/web/project/sesf/workinggroups/s2s