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There is great value embedded in reusing scientific data for secondary discoveries. However, it is challenging to find and reuse the large amount of existing scientific data distributed across the web and data repositories. Some of the challenges reside in the volume and complexity of scientific data, others pertain to the current practices and workflow of research data management. AIDR 2019 (Artificial Intelligence for Data Discovery and Reuse) is a new conference that brings together researchers across a broad range of disciplines, computer scientists, tool developers, data providers, and data curators, to share innovative solutions that apply artificial intelligence to scientific data discovery and reuse, and discuss how various stakeholders work together to create a health data ecosystem. This editorial summarizes the main themes and takeaways from the inaugural AIDR '19 conference.
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Arctic Ice
Integrating field data, remote satellite imagery, scientific analysis, and multimedia visual representation to document Arctic ice that is disappearing due to climate change, this artwork is the outcome of a four-year collaboration involving art, design, and polar science between artist Cy Keener, landscape researcher Justine Holzman, climatologist Ignatius Rigor, and scientist John Woods. With this work, Keener and Holzman’s goal is to make scientific data tangible, visceral, and experiential. They ask how artistic and creative practices can contribute to scientific endeavors while making scientific research visible to the public.
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- Award ID(s):
- 1951762
- PAR ID:
- 10415781
- Date Published:
- Journal Name:
- Issues in science and technology
- Volume:
- 39
- Issue:
- 1
- ISSN:
- 0748-5492
- Page Range / eLocation ID:
- 48-53
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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