Prospective and Retrospective Provenance Queries: Week 9 – Wrapped up week, internship final report & paper producing!

Hi everyone,

It’s Linh from project 3 again. This is my last week at DataONE as a summer intern. Most of the time, I spent on wrapping up our works, including: reorganize the GitHub repository, writing the internship final report simultaneously with a workshop paper. Our team intend to submit a workshop paper representing our works of this summer at International Semantic Web Conference 2017. This is a very high ranked conference in Semantic Web & Linked Data community and the attached workshops are also in great quality. We are in the stage of finalizing our paper and expect to submit it over this weekend! We hope this would be a nice wrap-up for our internship.

To summarize our internship works, there are three major tasks are done:

(1) Refining the existing YesWorkflow conceptual model and creating YW vocabularies: In this step, we first followed ProvONE and tried to revise the YesWorkflow conceptual model to make it compatible with ProvONE model. After that, we created YW namespace vocabularies based on the model, which would help us to represent YW components in RDF documents.

(2) Implementing an RDF document for a particular example of YW based on the model and vocabularies: In this step, we implemented an example of YW in RDF triples in order to further confirm the rationality and feasibility of the YesWorkflow conceptual model. There are two RDF in Turtle is used for implementing the YW model: one for prospective provenance and the other for retrospective provenance.

(3) Implementing SPARQL queries for the RDF document and examining the results: In this step, we implemented a series of SPARQL queries (total 50 queries created and tested) in order to explore YW querying capabilities.We used Virtuoso [citation here] and Jena ARQ  as the two SPARQL tools to implement the queries simultaneously in order to be able to re-examine the query results.

All of our works are published in the internship GitHub repository here. With this short term research, we all hope that the results would help us one step closer to enable prospective and retrospective provenance in YW, thus making YW and its provenance to be more useful and actionable.

It was my pleasure to work with such a great team! Thanks to my advisors, Bertram and Tim, for all of the supports and great advices! Also thanks to my co-intern, Hui, for being a supportive and hard-working colleague! I hope to have other opportunities to work with you in the future!

Good luck!


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