Organic Data Curation
We are investigating a novel approach to data publishing that is organic in its organization, requires minimal effort from the contributor, has parsimonious design, and is accessible to all scientists as well as other potential contributors. We offer a minimal pre-defined structure, and allow contributors to describe their data by easily defining their own metadata properties to suit their particular datasets, and to reuse common available vocabularies when it is convenient. The normalization of metadata will be organic, as other scientists aggregate datasets in the repository and find the need to aggregate them.
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Yolanda Gil
Senior Director for Major Strategic AI and Data Science Initiatives
I have broad research interests in AI and data science. As Principal Scientist I lead the Interactive Knowledge Capture research group, which is part of AI@ISI.