A vast amount of information is locked away inside visual content. We can see it but not search it. We can apply metadata to the whole image but not access its interior content. OASIS is a new way to access the visual features and conceptual ideas inside images, including ultra high definition images, using Linked Data. This session can include a quick demo of how the system works and a discussion of the technologies and standards used and challenges encountered and overcome in the process. The following link has 6 screen shots to illustrate: Deep Image Indexing as Linked Data
One of the bottlenecks to get museum data in the Linked Data Cloud is that it is hard to do it. The Europeana and CRM ontologies are large and complicated, and it is difficult to map data from the museum databases to these ontologies. For the last few years we’ve been working on tools to help people map their data to ontologies without programming or without writing scripts in languages such as xpath and XSLT. The tool is called Karma, and you can download it from http://isi.edu/integration/karma.
We would like to propose a session to show Karma. We have used it with datasets from several museums, and would like to show how we mapped the data from the Smithsonian American Art museum to the Europeana ontology (41,000 objects and 8,000 artists) and how we did linking to DBpedia, the NY Times and several other datasets. We think that Karma makes the process much easier than using other tools, and we’d love to hear what you think, and hopefully provide you tools to help you.
We presented a paper about this last month at the Extended Semantic Web Conference (ESWC) in Montpellier. You can get the paper at http://bit.ly/11X5YPo and the slides at http://slidesha.re/18vxMnn. I am very proud to say that we received the best in-use paper award for this work, and makes me very happy that our work with the Smithsonian museum was recognized at the conference.
You can also browse the data on the SPARQL endpoint. We are using Pubby (same thing as DBpedia), but looking forward to getting better tools from you. So check it out, here is the page for John Singer Sargent.
As an organizer of Open Data Bay Area, I thought I could usefully seed some ideas by sharing some of the suggestions we’ve received for our meetings. Here’s some of the topics about which people have expressed interest to us, and bear in mind that we’re coming from tech-heavy San Francisco:
Toolsets for working with Linked Open Data
Your first SPARQL query
Ontologies for beginners
Visualizing Linked Open Data
Getting from data to LOD
Looking forward to seeing old and new faces in Montreal!