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Abstract Legumes, comprising one of the largest, most diverse, and most economically important plant families, are the subject of vibrant research and development worldwide. Continued improvement of legume crops will benefit from the recent proliferation of genetic (including genomic) resources; but the diversity, scale, and complexity of these resources presents challenges to those managing and using them. A workshop held in March of 2019 addressed questions of data resources and priorities for the legumes. The workshop identified various needs and recommendations: (a) Develop strategies to effectively store, integrate, and relate genetic resources collected in different projects. (b) Leverage information collected across many legume species by standardizing data formats and ontologies, improving the state of metadata about datasets, and increasing use of the FAIR data principles. (c) Advocate for the critical role that curators exercise in integrating complex datasets into databases and adding high value metadata that enable downstream analytics and facilitate practical applications. (d) Implement standardized software and database development practices to best leverage limited developer time and expertise gained from the various legume (and other) species. (e) Develop tools and databases that can manage genetic information for the world's plant genetic resources, enabling efficient incorporation of important traits into breeding programs. (f) Centralize information on databases, tools, and training materials and establish funding streams to support training and outreach.
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A general purpose tool-set for representing data relationships: Converting data into knowledge
Rich metadata is required to find and understand the recorded measurements from modern experiments with their immense and complex data stores. Systems to store and manage these metadata have improved over time, but in most cases are ad-hoc collections of data relationships, often represented in domain or site specific application code. We are developing a general set of tools to store, manage, and retrieve datarelationship metadata. These tools will be agnostic to the underlying data storage mechanisms, and to the data stored in them, making the system applicable across a wide range of science domains.
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- Award ID(s):
- 1640829
- PAR ID:
- 10027980
- Date Published:
- Journal Name:
- IEEE 2016 New York Scientific Data Summit (NYSDS)
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/nysds.2016.7747809
