Abstract
In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.
This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan).
G. R. Watson—Contributed equally to this work.
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References
Exascale computing project, September 2017. https://exascaleproject.org/
Abbott, R., et al.: Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo. SoftwareX 13, 100658 (2021). https://doi.org/10.1016/j.softx.2021.100658
Special issue on software that contributed to gravitational wave discovery. SoftwareX (2021). https://www.sciencedirect.com/journal/softwarex/special-issue/103XKC9DRLV
A survey on sustainable software ecosystems to support experimental and observational science at oak ridge national laboratory (2022). https://doi.org/10.6084/m9.figshare.19529995
Bartlett, R., et al.: xSDK foundations: toward an extreme-scale scientific software development kit. Supercomput. Front. Innov. 4(1), 69–82 (2017). https://doi.org/10.14529/jsfi170104
Bavota, G., Canfora, G., Penta, M.D., Oliveto, R., Panichella, S.: The evolution of project inter-dependencies in a software ecosystem: the case of apache. In: 2013 IEEE International Conference on Software Maintenance, pp. 280–289 (2013). https://doi.org/10.1109/ICSM.2013.39
Dhungana, D., Groher, I., Schludermann, E., Biffl, S.: Software ecosystems vs. natural ecosystems: learning from the ingenious mind of nature. In: Proceedings of the Fourth European Conference on Software Architecture: Companion Volume, pp. 96–102 (2010)
Dongarra, J., et al.: The International Exascale Software Project roadmap. Int. J. High Perform. Comput. Appl. 25(1), 3–60 (2011). https://doi.org/10.1177/1094342010391989
Enders, B., et al.: Cross-facility science with the Superfacility Project at LBNL. In: 2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP), pp. 1–7 (2020). https://doi.org/10.1109/XLOOP51963.2020.00006
Hannay, J.E., MacLeod, C., Singer, J., Langtangen, H.P., Pfahl, D., Wilson, G.: How do scientists develop and use scientific software? In: 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering, pp. 1–8 (2009). https://doi.org/10.1109/SECSE.2009.5069155
Heaton, D., Carver, J.C.: Claims about the use of software engineering practices in science: a systematic literature review. Inf. Softw. Technol. 67, 207–219 (2015). https://doi.org/10.1016/j.infsof.2015.07.011
Heroux, M.A.: The extreme-scale scientific software stack (e4s). Technical report, Sandia National Lab. (SNL-NM), Albuquerque, NM, United States (2019)
Ivezić, Ž., et al.: LSST: from science drivers to reference design and anticipated data products. Astrophys. J. 873(2) (2019). https://doi.org/10.3847/1538-4357/ab042c
Kaiya, H.: Meta-requirements for information system requirements: lesson learned from software ecosystem researches. Procedia Comput. Sci. 126, 1243–1252 (2018). https://doi.org/10.1016/j.procs.2018.08.066. Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22nd International Conference, KES-2018, Belgrade, Serbia
Kehrer, T., Penzenstadler, B.: An exploration of sustainability thinking in research software engineering. In: Chitchyan, R., Penzenstadler, B., Venters, C.C. (eds.) Proceedings of the 7th International Workshop on Requirements Engineering for Sustainable Systems (RE4SuSy 2018) co-located with the 26th International Conference on Requirements Engineering (RE 2018), Banff, Alberta, Canada, 20 August, 2018. CEUR Workshop Proceedings, vol. 2223, pp. 34–43. CEUR-WS.org (2018). http://ceur-ws.org/Vol-2223/paper5.pdf
Lamprecht, A.L., et al.: Towards fair principles for research software. Data Sci. 3(1), 37–59 (2020)
Manikas, K., Hansen, K.M.: Software ecosystems-a systematic literature review. J. Syst. Softw. 86(5), 1294–1306 (2013)
Megino, F.B., et al.: Integration of titan supercomputer at OLCF with ATLAS production system. In: Journal of Physics: Conference Series 898, 092002 (2017). https://doi.org/10.1088/1742-6596/898/9/092002
Monteith, J.Y., McGregor, J.D., Ingram, J.E.: Scientific research software ecosystems. In: Proceedings of the 2014 European Conference on Software Architecture Workshops, pp. 1–6 (2014)
Sadi, M.H., Dai, J., Yu, E.: Designing software ecosystems: how to develop sustainable collaborations? In: Persson, A., Stirna, J. (eds.) CAiSE 2015. LNBIP, vol. 215, pp. 161–173. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19243-7_17
dos Santos, R.P., Werner, C.M.L.: Revisiting the concept of components in software engineering from a software ecosystem perspective. In: Proceedings of the Fourth European Conference on Software Architecture: Companion Volume, ECSA 2010, pp. 135–142. Association for Computing Machinery, New York (2010). https://doi.org/10.1145/1842752.1842782
Storer, T.: Bridging the chasm: a survey of software engineering practice in scientific programming. ACM Comput. Surv. (CSUR) 50(4), 1–32 (2017)
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Bernholdt, D.E., Doucet, M., Godoy, W.F., Malviya-Thakur, A., Watson, G.R. (2022). A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13353. Springer, Cham. https://doi.org/10.1007/978-3-031-08760-8_46
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