Special Issue on Linked Data for Science and Education
The Semantic Web Journal has posted a call for papers on linked data for science and education.
Important dates:
Deadline for submissions: May 31 2011
Reviews due: July 15 2011
Final versions of accepted papers due: August 12 2011
Apologies, I missed this announcement when it came out in early February, 2011.
From the call:
The number of universities, research organizations, publishers and funding agencies contributing to the Linked Data cloud is constantly increasing. The Linked Data paradigm has been identified as a lightweight approach for data dissemination and integration, opening up new opportunities for the organization, integration, archiving and retrieval of research results and educational material. Obviously, this novel approach also raises new challenges regarding the integrity, adoption, use and sustainability of contents. A number of case studies from universities and research communities already demonstrate that Linked Data is not merely a novel way of exposing data on the Web, but that its principles help integrating related data, connecting scientists working on related topics, and improving scientific and educational workflows. The next challenges in creating a true Web of scientific and educational data include dealing with provenance, mapping vocabularies (i.e., ontologies), and organizational issues such as assessing costs and ensuring persistence and performance. In this special issue of the Semantic Web Journal, we want to collect the state of the art in Linked Data for science and education and identify upcoming challenges, focusing on technological aspects as well as social and legal implications.
Well, I like that:
The next challenges in creating a true Web of scientific and educational data include dealing with provenance, mapping vocabularies (i.e., ontologies), and organizational issues such as assessing costs and ensuring persistence and performance.
Link data together and then hope we can sort it out on the other end.
Doesn’t that sound a lot like Google?
Index data together and then hope we can sort it out on the other end.