Loading…

A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

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 desi...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2022-04
Main Authors: Bernholdt, David E, Doucet, Mathieu, Godoy, William F, Malviya-Thakur, Addi, Watson, Gregory R
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Bernholdt, David E
Doucet, Mathieu
Godoy, William F
Malviya-Thakur, Addi
Watson, Gregory R
description 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.
doi_str_mv 10.48550/arxiv.2204.05896
format article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2649833008</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2649833008</sourcerecordid><originalsourceid>FETCH-LOGICAL-a528-b985c6686592886be836d59ba16580d00145b186fb5648990e5b4435e7264c53</originalsourceid><addsrcrecordid>eNo1jk9LAzEUxIMgWGo_gLeA563ZJC9NjqXUP1AsuN7Ly-6rbG03a5JWe_Gzu6CeZpj5MQxjN6WYagsg7jB-taeplEJPBVhnLthIKlUWVkt5xSYp7YQQ0swkgBqx7zmvjvFEZx66waWMbYd-T7wK2_yJkfiyDumcMh0Sz2FA-j7EzJdfPcX2QF3GPceu4WufKJ4wt6EbkqpuqauJY-ZrfOcvbfNG_Pm_XaEPEXOI52t2ucV9osmfjll1v3xdPBar9cPTYr4qEKQtvLNQG2MNOGmt8WSVacB5LA1Y0QhRavClNVsPRlvnBIHXWgHNpNE1qDG7_V3tY_g4UsqbXTjG4UnaDICzSglh1Q_pfmAI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2649833008</pqid></control><display><type>article</type><title>A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory</title><source>ProQuest - Publicly Available Content Database</source><creator>Bernholdt, David E ; Doucet, Mathieu ; Godoy, William F ; Malviya-Thakur, Addi ; Watson, Gregory R</creator><creatorcontrib>Bernholdt, David E ; Doucet, Mathieu ; Godoy, William F ; Malviya-Thakur, Addi ; Watson, Gregory R</creatorcontrib><description>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.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.2204.05896</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Artificial intelligence ; Data management ; Demographics ; Laboratories ; Research facilities ; Software</subject><ispartof>arXiv.org, 2022-04</ispartof><rights>2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2649833008?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25753,27925,37012,44590</link.rule.ids></links><search><creatorcontrib>Bernholdt, David E</creatorcontrib><creatorcontrib>Doucet, Mathieu</creatorcontrib><creatorcontrib>Godoy, William F</creatorcontrib><creatorcontrib>Malviya-Thakur, Addi</creatorcontrib><creatorcontrib>Watson, Gregory R</creatorcontrib><title>A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory</title><title>arXiv.org</title><description>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.</description><subject>Artificial intelligence</subject><subject>Data management</subject><subject>Demographics</subject><subject>Laboratories</subject><subject>Research facilities</subject><subject>Software</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNo1jk9LAzEUxIMgWGo_gLeA563ZJC9NjqXUP1AsuN7Ly-6rbG03a5JWe_Gzu6CeZpj5MQxjN6WYagsg7jB-taeplEJPBVhnLthIKlUWVkt5xSYp7YQQ0swkgBqx7zmvjvFEZx66waWMbYd-T7wK2_yJkfiyDumcMh0Sz2FA-j7EzJdfPcX2QF3GPceu4WufKJ4wt6EbkqpuqauJY-ZrfOcvbfNG_Pm_XaEPEXOI52t2ucV9osmfjll1v3xdPBar9cPTYr4qEKQtvLNQG2MNOGmt8WSVacB5LA1Y0QhRavClNVsPRlvnBIHXWgHNpNE1qDG7_V3tY_g4UsqbXTjG4UnaDICzSglh1Q_pfmAI</recordid><startdate>20220412</startdate><enddate>20220412</enddate><creator>Bernholdt, David E</creator><creator>Doucet, Mathieu</creator><creator>Godoy, William F</creator><creator>Malviya-Thakur, Addi</creator><creator>Watson, Gregory R</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20220412</creationdate><title>A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory</title><author>Bernholdt, David E ; Doucet, Mathieu ; Godoy, William F ; Malviya-Thakur, Addi ; Watson, Gregory R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a528-b985c6686592886be836d59ba16580d00145b186fb5648990e5b4435e7264c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial intelligence</topic><topic>Data management</topic><topic>Demographics</topic><topic>Laboratories</topic><topic>Research facilities</topic><topic>Software</topic><toplevel>online_resources</toplevel><creatorcontrib>Bernholdt, David E</creatorcontrib><creatorcontrib>Doucet, Mathieu</creatorcontrib><creatorcontrib>Godoy, William F</creatorcontrib><creatorcontrib>Malviya-Thakur, Addi</creatorcontrib><creatorcontrib>Watson, Gregory R</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bernholdt, David E</au><au>Doucet, Mathieu</au><au>Godoy, William F</au><au>Malviya-Thakur, Addi</au><au>Watson, Gregory R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory</atitle><jtitle>arXiv.org</jtitle><date>2022-04-12</date><risdate>2022</risdate><eissn>2331-8422</eissn><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.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.2204.05896</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2022-04
issn 2331-8422
language eng
recordid cdi_proquest_journals_2649833008
source ProQuest - Publicly Available Content Database
subjects Artificial intelligence
Data management
Demographics
Laboratories
Research facilities
Software
title A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T05%3A27%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Survey%20on%20Sustainable%20Software%20Ecosystems%20to%20Support%20Experimental%20and%20Observational%20Science%20at%20Oak%20Ridge%20National%20Laboratory&rft.jtitle=arXiv.org&rft.au=Bernholdt,%20David%20E&rft.date=2022-04-12&rft.eissn=2331-8422&rft_id=info:doi/10.48550/arxiv.2204.05896&rft_dat=%3Cproquest%3E2649833008%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a528-b985c6686592886be836d59ba16580d00145b186fb5648990e5b4435e7264c53%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2649833008&rft_id=info:pmid/&rfr_iscdi=true