Leveraging Shared Expertise for Data Curation and Discovery
Submitted by Hannah Hadley
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Discuss the concept of network models of shared curation and data discovery expertise. Some examples: Data Curation Network, Portage’s Canadian Data Curation Experts Forum, Dutch Data Curation Network, Data Discovery Collaboration, and others.
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Determine geographic or alternatively related subject specific areas of need within the international community or within various national communities.
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Examine how we may leverage our strengths in curation expertise across the globe through both formal and informal networks.
Collaborative Notes Link: https://docs.google.com/document/d/18Fn9R_cpD63Qj12NvETc6fR1d7RWCOO0uTqn...
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Welcome & Introductions
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Background on various shared expertise network models (e.g. Portage, Data Curation Network) and similar groups or projects (e.g. Data Discovery Collaboration Project, Dutch Data Curation Network) serving communities around the world.
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Briefly introduce other modes of partnerships and shared expertise that networks can engage in, such as: education, data discovery, research and development, advocacy, and resources.
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Facilitate panel discussion with networks and similar groups or projects:
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Examine benefits and costs of starting or joining a network.
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Examine support mechanisms and questions for development
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Examine alternate ways to engage with networks in order to share and extend expertise worldwide
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Brainstorm to identify areas of complementary need, such as may be found in similar geographies or possibly based on subject needs.
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Engage attendes in the conversation and allow for questions
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What are your local experiences and needs?
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Discuss shared goals or project ideas.
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Gather information to map these networks and similar projects into a usable directory
Funders increasingly require that data sets arising from sponsored research must be preserved and shared, and many publishers either require or encourage that data sets accompanying articles are made available for reuse and reproducibility through a publicly accessible repository. However, the data curation activities that support these preservation and sharing activities are costly, requiring training in advanced curation practices, specific technical competencies and relevant subject expertise. Few organizations will be able to hire and sustain all of the data curation expertise that researchers will require. Even those with the means to do more will benefit from a collective approach that will allow them to supplement at peak times, access specialized capacity when infrequently-curated types arise, and to stabilize service levels to account for local staff transition, such as during turn-over periods.
Drawing on our experiences in piloting the DCN to date, we have sparked interest from several national and international organizations who have similar goals and challenges with curating research data and see the benefit of a networked approach. This BoF will explore these shared interests and associated challenges with networked data curation with the aim to determine how we can move forward in a data curation world without borders.
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