Uncertainty About the Long-Term: Digital Libraries, Astronomy Data, and Open Source Software

Darch, Peter T.; Sands, Ashley E.

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https://hdl.handle.net/2142/99012 Copy

Description

Title

Uncertainty About the Long-Term: Digital Libraries, Astronomy Data, and Open Source Software

Author(s)

• Darch, Peter T.
• Sands, Ashley E.

Issue Date

2017

Keyword(s)

• Astronomy
• Big data
• Big science
• Data management
• Data curation
• Knowledge infrastructures
• Long term
• Open source
• Scientific data

Abstract

Digital library developers make critical design and implementation decisions in the face of uncertainties about the future. We present a qualitative case study of the Large Synoptic Survey Telescope (LSST), a major astronomy project that will collect and make available large-scale datasets. LSST developers make decisions now, while facing uncertainties about its period of operations (2022-2032). Uncertainties we identify include topics researchers will seek to address, tools and expertise, and availability of other infrastructures to exploit LSST observations. LSST is using an open source approach to developing and releasing its data management software. We evaluate benefits and burdens of this approach as a strategy for addressing uncertainty. Benefits include: enabling software to adapt to researchers’ changing needs; embedding LSST standards and tools in community practices; and promoting interoperability with other infrastructures. Burdens include: open source community management; documentation requirements; and trade-offs between software speed and accessibility.

Publisher

IEEE.org

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/99012

DOI

10.1109/JCDL.2017.7991584

Sponsor(s)/Grant Number(s)

Alfred P. Sloan Foundation (#20113194, #201514001)

Owning Collections