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

Prospective and Retrospective Provenance Queries: Week 7 – Fine-tuning YW Model & SPARQL queries

Hi all, It’s Linh Hoang, the intern from project 3 (again 🙂 ). Time flies! And we are reaching the last few weeks of the internship! This week, we mainly spent time for fine-tuning our YW Model. Some minor changes were made for naming convention purposes. Also documentations of the model including Continue reading Prospective and Retrospective Provenance Queries: Week 7 – Fine-tuning YW Model & SPARQL queries

Prospective and Retrospective Provenance Queries: Week 6 – Mapping YW & ProvONE model, explore RDF & SPARQL limitations

Hi everyone, It’s Linh Hoang, the intern from project 3. This week, along with our supervisors, my co-intern and I tried to finalize the YW model with our own vocabulary. We also created an UML diagram to represent the model. This is a good way for outsiders to conceptualize and understand Continue reading Prospective and Retrospective Provenance Queries: Week 6 – Mapping YW & ProvONE model, explore RDF & SPARQL limitations

Prospective and Retrospective Provenance Queries: Week 5 – YW Data Model & SPARQL queries (cont.)

Hello everyone, It’s Linh Hoang, the intern from project 3. This week, my co-intern and I continue to focus on revising our YesWorkflow Data Model with our own vocabulary. Besides that, we also created an UML diagram to represent components of the model and how they connects to each other. The diagram is Continue reading Prospective and Retrospective Provenance Queries: Week 5 – YW Data Model & SPARQL queries (cont.)

Prospective and Retrospective Provenance Queries: Week 4 – YesWorkflow Data Model

Hi everyone, I’m Linh Hoang, from project 3. This week, my co-intern and I focused on creating a YesWorkflow Data Model with our own vocabulary. Previously, we used ProvONE Data Model (which is an extension of the standard Provenance Data Model recommended by W3C) to represent items of YesWorkflow. However, Continue reading Prospective and Retrospective Provenance Queries: Week 4 – YesWorkflow Data Model

Prospective and Retrospective Provenance Queries: Week 3 – SPARQL Recursive Queries

Hi everyone, It’s Linh Hoang from Project 3. This week, I spent most of my time to read papers and also ran some experiments to explore SPARQL recursive queries capability. The objective is to be able to run standard recursive queries in SPARQL. We found “property path” is a way Continue reading Prospective and Retrospective Provenance Queries: Week 3 – SPARQL Recursive Queries

Prospective and Retrospective Provenance Queries: Week 2 – SPARQL Provenance Query

Hi all, It’s Linh Hoang from Project 3. This week, I am working on exploring SPARQL querying capabilities in YesWorkflow. The objective is to testing how well SPARQL can query YW outputs, which are represented in RDF format. First, I completed installing Virtuoso on my machine and wrote a manual of Continue reading Prospective and Retrospective Provenance Queries: Week 2 – SPARQL Provenance Query

Prospective and Retrospective Provenance Queries: Get to know YesWorkflow

My first week internship at DataOne started with a meeting with my mentors Prof. Bertram Ludaescher, Timothy McPhillips and Paolo Missier and my co-intern Hui Lyu. We discussed about what are the objectives of the internship and came up with a list of tasks for the next following weeks. Overall, the objective of the internship is to reimplement existing Continue reading Prospective and Retrospective Provenance Queries: Get to know YesWorkflow