Balancing the needs of consumers and producers for scientific data collections

Agarwal, D.; Damerow, Joan; Varadharajan, Charuleka; Christianson, Danielle; Pastorello, Gilberto; Cheah, You-Wei; Ramakrishnan, Lavanya

doi:10.1016/j.ecoinf.2021.101251

Cited by 4 publications

(1 citation statement)

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“…Use Case 1: Efficiently publish and cite large number of samples and associated (meta)data Many studies that involve physical samples include dozens, hundreds, or even thousands of samples and subsamples. There is no widely-adopted method to efficiently cite large numbers of datasets 45 , let alone the physical samples linked to them. However, we can include metadata indicating all the samples used in a given dataset.…”

Section: Use Case Review: Needs For Tracking Sample Usementioning

confidence: 99%

Opening Doors to Physical Sample Data Discovery, Integration, and Credit

Damerow,

Raia,

Stanley

et al. 2024

Preprint

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Physical samples and their associated (meta)data underpin scientific discoveries across disciplines, and can enable new science when appropriately archived. However, there are significant gaps in community practices and infrastructure that currently prevent accurate provenance tracking, reproducibility, and attribution. For the vast majority of samples, descriptive metadata is often sparse, inaccessible, or absent. Samples and associated (meta)data may also be scattered across numerous physical collections, data repositories, laboratories, data files, and papers with no clear linkages or provenance tracking as new information is generated over time. The Physical Samples Curation Cluster has therefore developed ‘A Scientific Author Guide for Publishing Open Research Using Physical Samples.’ This involved synthesizing existing practices, community feedback, and assessing real-world examples to identify community and infrastructure needs. We identified areas of work needed to enable authors to efficiently reference samples and related data, link related samples and data, and track their use. Our goal is to help improve the discoverability, interoperability, use of physical samples and associated (meta)data into the future.

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Section: Use Case Review: Needs For Tracking Sample Usementioning

confidence: 99%