Krzysztof Janowicz's blog

Call for papers: Special issue of the Semantic Web journal on Semantics for Big Data

Call for papers: Special issue of the Semantic Web journal on Semantics for Big Data

http://www.semantic-web-journal.net/blog/call-papers-special-issue-semantic-web-journal-semantics-big-data

One of the key challenges in making use of Big Data lies in finding ways of dealing with heterogeneity, diversity, and complexity of the data, while its volume and velocity forbid solutions available for smaller datasets as based, e.g., on manual curation or manual integration of data. Semantic Web Technologies are meant to deal with these issues, and indeed since the advent of Linked Data a few years ago, they have become central to mainstream Semantic Web research and development. We can easily understand Linked Data as being a part of the greater Big Data landscape, as many of the challenges are the same. The linking component of Linked Data, however, puts an additional focus on the integration and conflation of data across multiple sources.

The Reginald Golledge Distinguished Lecture in Geography (March 14, 2013 )

The Reginald Golledge Distinguished Lecture in Geography

March 14, 2013 - 3:30-4:30 - Buchanan 1930, UCSB

“On Mental Clocks and Mental Maps: Contributions of Behavioral Geography
to a Theory of Geospatial Change”

Gilberto Câmara
National Institute for Space Research, Brazil

Place and Location on the Web of Linked Data

Geodata or more specifically places and locations play a key role on the Web of Linked Data by serving as nexuses that interconnect different data and data sources. Geonames, for instance, is one of the most linked hubs. In fact, most Linked Data are either directly or indirectly linked through various spatial and non-spatial relations to locations. Thus, it makes sense to dive deeper into investigating the role that place and location play, how many degrees (links) it takes before all Linked Data is connected to some sort of geo-feature, how these geo-features are represented, how their density is distributed, how to clean them up, and so forth. We started to do research on these topics some time ago and are preparing a paper. In the meantime we would like to show you some maps that illustrate the current state of locations on the Linked Data Web and the amount and types of errors we encountered. It turns out that more than 10% of these data has wrong or even impossible locations. We have found systematic errors and are beginning to figure out methods for cleaning them up. In case you are interested in Geospatial Semantics, Linked Spatiotemporal Data, and Geo-Ontologies you may also check out this short overview as starting point.