We will investigate graph-based methods of connecting data with the uses made and the knowledge gained from those data, from science research to applications to strategic planning. We will examine the diverse capabilities enabled by connecting uses with data for a variety of stakeholders, and explore how to connect existing knowledge graphs together to scale out across the ESIP federation and related communities toward an inter-connected mega-graph.
0-5 min: Chris Lynnes (NASA):
Documenting how data matters...
5-15 min: Doug Newman (NASA): EOSDIS Knowledge Graph
https://doi.org/10.6084/m9.figshare.11561805.v115-25 min: Reid Sherman (GCIS): Global Change Information System
https://doi.org/10.6084/m9.figshare.11560011.v125-35 min: Dave Blodgett (USGS): SELFIE
https://doi.org/10.6084/m9.figshare.11559093.v135-45 min: Joe Conran (NOAA): Interagency Coordination of Satellite Needs
https://doi.org/10.6084/m9.figshare.11561946.v145-55 min: Wil Doane (IDA): Assessing the Impact of Land Imaging
https://doi.org/10.6084/m9.figshare.11561913.v155-90 min: The Way Forward:
1 - Got Use Case?
2 - ESIP Cluster?
https://www.esipfed.org/get-involved/collaborate3 - Who's In?
Session Notes
View Recording: https://youtu.be/yi05crW6Ya0\Takeaways- How to connect data with the uses of that data = Documenting how data matter.
Federating knowledge bases is daunting task but possible. - Connect research and data to place (but gap around using place identifiers in linked data).
Discussion of potentially make a new cluster or using another one. Decision to recharter/repurpose/rename the data discovery cluster. - Sin of computer science is giving people impression that things are mostly 1 to 1 relationship, but more accurately life and universe is full of many-to-many relationships, i.e., graph databases > RDBMS
