Scientific Annotation: Using Graphs to Facilitate Interdisciplinary Science
Scientific Annotation: Using Graphs to Facilitate Interdisciplinary Science

Abstract: 

Data resources in the Earth Sciences range from kilobytes to terabytes, with a range of user communities, technical competence, and scientific uses. As interdisciplinary research continues to grow there is a significant need to increase usability and discoverability, to assign credit to data generators, developers and to provide people with the tools and knowledge they need to help address some of society's most pressing issues. This presentation showcases an approach that uses neo4j's graph database, open source APIs, the use of persistent identifiers such as ORCIDs and DOIs, and crowd sourcing to help connect disciplines within the Earth Sciences to undertake science for a new century.

Bio: 

Simon Goring is an interdisciplinary scientist working at the intersections of biology, computer science and the earth sciences (http://goring.org). He uses information about the past to help understand the future challenges of climate change as part of the Neotoma Paleoecology Database (http://neotomadb.org). As an Assistant Scientist in the Department of Geography at the University of Wisconsin-Madison, and an adjunct professor in Computer Sciences at the University of British Columbia he focuses on translational activities, helping to enable the next generation of scientists to leverage open data science tools to undertake new discoveries in the physical sciences, with a particular focus on exposing "dark data" and working to support equity through technology. As part of this effort he is the lead PI of the Throughput Project, funded by the National Sciences Foundation through the EarthCube program (http://earthcube.org). Throughput uses a graph database (neo4j) as the principal backbone to connect scientific users to a cookbook of code, that connects data, analysis and publication. This application helps support early career researchers working on interdisciplinary research by facilitating code discovery, data reuse and online collaboration.

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