Presentation slides are here Media:Kyzirakos-presentation.pdf
Minutes:
12 people were present at conceptual Friday, 11 april 2014:
Kostis Kyzirakos was present as guest speaker on spatial-temporal aspects of linked data. His PhD was about representing and querying spatial-temporal information in the semantic web. Currently he is working as a postdoc at CWI (UvA).
GeoSPARQL is very good for representing geographic information. So the spatial part is covered. It has been well described by OGC who have been working on standardization of geospatial information since 20 years. The work on temporal standardization however is only about 2 years old.
Temporal aspects:
There are many approaches for describing time, with may different requirements underlying them. There s not yet one standardized approach. W3C may make effort to standardize the Time ontology or something else; a working group on time is being created.
With regards to time there is a granularity problem: some contexts require recording of time in microseconds versus other contexts requiring prehistoric dating, geological periods. A suggestion of Kostis is that perhaps the solution lies in a general temporal vocabulary, like GML for the spatial aspect, and which can be extended with more specific application profiles, or more narrow / simple subsets, etc.
Kostis presents stRDF: spatial-temporal RDF, an extension of RDF. It supports spatial literals (WKT and GML, both already standardized encodings of geometry) and a temporal literal strdf:period. The temporal aspect is modeled as the fourth component of each triple: each triple has a period in which it is valid. These 'quads' are used and stored for convenience, but you can express them as triples as well.
In addition to stRDF there is also stSPARQL with extension query functions for spatial and temporal aspects of linked data. It has more functions than, for example, GeoSPARQL. In stSPARQL you can ask for geometries in a specific CRS, for example. In addition to spatial queries you can query using temporal keywords such as 'before', 'during'. Also, in stSPARQL you can add a time instant as a fourth query component to the WHERE clause, allowing you to ask only for triples that were valid at the time you specified.
stRDF and stSPARQL were used in an appliation for fire monitoring. For example, it lets you find all burned forest within 10km of a city.
stRDF and stSPARQL are implemented in Strabon. Strabon is an extension of Sesame and storage is handled with PostgreSQL and MonetDB. The system stores stRDF graphs; either stSPARQL or GeoSPARQL queries are possible. The output can be SPARQL results, KML, and GeoJSON. Performance is good compared to other current systems.
Sextant is an interesting component for visualizing time-evolving geometries.
Examples: http://bit.ly/sextant-rapid-mapping-attica http://bit.ly/FiresInGreece
The use case here is fire monitoring. The web application combines sensing data (satellite images etc) with other linked data such as data on hospitals, roads, and so on. Both the current situation and the changes over time of forest fires are available. Emergency response people thus have the data they need immediately. Combining all this data on a map also led to improvement of accuracy of the data. Errors in the data became visible and could be corrected.
A small ontology for fire data was created (with terms like 'hotspot') and combined with SWEET (an interesting ontology by NASA, with temporal aspects). The data was linked with GeoNames, OpenStreetMap, CORINE land use / land cover.
Resource Description Framework (RDF) is een standaardmodel voor gegevensuitwisseling op het web. RDF heeft functies die het samenvoegen van gegevens vergemakkelijken, zelfs als de onderliggende schema's verschillen, en het ondersteunt specifiek de evolutie van schema's in de loop van de tijd zonder dat alle gegevensgebruikers moeten worden gewijzigd.
Door middel van reasoning, redeneren met data (feiten) en regels, probeer je nieuwe feiten te achterhalen met de verzameling feiten en regels die je op een bepaald moment hebt. Met OWL en RDF Schema kun je redeneren, maar dat heeft zijn beperkingen. Binnen de PLDN community is er interesse in SHACL en SPIN om te bekijken in hoeverre deze de beperkingen van OWL en RDFS kunnen oplossen.
Een Uniform Resource Locator (afgekort URL) is een gestructureerde naam die verwijst naar een stuk data. Voorbeelden zijn het unieke adres waarmee de locatie van een webpagina op internet wordt aangegeven of een e-mailadres. In de naam is alle informatie opgenomen over de benodigde techniek om de betreffende gegevens te bereiken. De URL is een bijzondere vorm van de URI.
De activiteiten van Platform Linked Data Nederland (PLDN) worden mede mogelijk gemaakt dankzij het Kadaster, TNO, Big Data Value Center (BDVC), ECP, Forum Standaardisatie, Kennisnet, SLO, Waternet, Taxonic, MarkLogic, Triply, Franz Inc., SemmTech, Rijksdienst voor het Cultureel Erfgoed (RCE), Beeld en Geluid, EuroSDR, de KVK en ArchiXL
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