@inproceedings{d357919f1fa54f70a668f22ad7ba55d3,
title = "Uncertainty about the Long-Term: Digital Libraries, Astronomy Data, and Open Source Software",
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.",
keywords = "Astronomy, Big data, Big science, Data curation, Data management, Knowledge infrastructures, Long term, Open source, Scientific data",
author = "Darch, {Peter T.} and Sands, {Ashley E.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 ; Conference date: 19-06-2017 Through 23-06-2017",
year = "2017",
month = jul,
day = "25",
doi = "10.1109/JCDL.2017.7991584",
language = "English (US)",
series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017",
address = "United States",
}