Collaboration Discovery, A Linked Data Approach

Linked Data is a modern paradigm for data publishing, which leverages the inherent linking capabilities of the Web and provides semantics for the relationships between “things” on the Web. These “things” may be digital objects, such as publications and science data, or they may be representative of real-world entities, including people, organizations, and events. Recent Funding Friday projects and Summer Meeting sessions have demonstrated ESIP’s interest in Linked Data as well as modeling of organizations, people, and events that shape the ESIP network. At present, these two efforts have been pursued independently. We believe that the Linked Data paradigm is ideal for capturing and publishing information on the ESIP community and doing so would demonstrate the collaborative nature within ESIP.

This work will provide a scalable, open platform for current and future efforts to analyze and extend the community models in various ways. Through our previous efforts on a Funding Friday project, we have started to capture the ESIP research network as Linked Data. This project will further that effort by

1. providing a collaborative development environment
2. enabling a service that all of ESIP can access and
3. extending our current Linked Data sources

Specifically, we will deploy a service on the ESIP Amazon Web Services that gives users the ability to:

1. search for collaborators
2. and discover relationships between ESIP and AGU/NSF projects

We will also focus on developing an ESIP platform for contributing to these datasets; we will seek out contributions from ESIP clusters which may include, but are not limited to

1. interfaces for minor edits
2. equivalence assertions
3. batches uploads of new data

Current Status