|To:||Ontology Summit 2013 discussion <ontology-summit@xxxxxxxxxxxxxxxx>|
|From:||Victor Agroskin <vic5784@xxxxxxxxx>|
|Date:||Tue, 4 Feb 2014 14:28:22 +0400|
- people with their own tools and approaches interested in the scenario described above.
- people ready to test our tools (Python knowledge is required to work in dot15926 Editor environment, current version supports only part of the required functionality, access to new beta version of the software will be provided);
- people with data sets and relevant domain knowledge interested in bringing these data to Linked Data world (engineering data sets are a priority for us, as we're working with ISO 15926 ontology);
We are looking for:
One of the key tasks for our team is to explore extendibility of this approach. We'd be happy to see tools which will allow step-by step development of data presentation as new and varying data sources are added to the project and new relevant patterns are identified.
3. Make software prototype for the whole data-transformation chain or a part of it: raw data - mapping - ontology-linked data - pattern search - Linked Data web page presentation.
2. Define convenient presentation form for humans in terms of ontology patterns representing domain knowledge.
To bring a content of a data source into the world of Linked Data can pose a significant challenge. Especially if the data set is not uniform, has a high degree of variety and data model for it can not be easily obtained. In such cases help can come from an ontology where these data can be seen as instances.In the course of our software tool development we became very interested to test this approach. We've started integration of our dot15926 Editor (http://techinvestlab.ru/dot15926Editor) with a web framework to allow easy and extendible definition of web page templates for presentation of complex interlinked ontology concepts.
We are proposing the following hackathon scenario for teams with similar interests:
1. Select a data source which is either already connected to some ontology (some RDF data set, for example), or whose meta-data (data model, table headings, etc.) can be mapped to one.
Our team will be virtureal, working online and in our real office in Moscow, Russia.
Come on board!
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