From 7b4d737244774dbef778d0bc2e6e33eaabf9de1f Mon Sep 17 00:00:00 2001 From: Quarto GHA Workflow Runner Date: Wed, 19 Jun 2024 21:44:27 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- _tex/index.tex | 156 +++++++++++++++++------ _tex/references.bib | 77 +++++++++++ index.docx | Bin 25135 -> 27416 bytes index.html | 72 +++++++---- index.pdf | Bin 62954 -> 68964 bytes sections/01-introduction.embed.ipynb | 2 +- sections/01-introduction.out.ipynb | 2 +- sections/02-use-cases-preview.html | 4 +- sections/02-use-cases.embed.ipynb | 2 +- sections/02-use-cases.out.ipynb | 2 +- sections/02-use-cases.qmd | 2 +- sections/03-challenges-preview.html | 60 ++++++--- sections/03-challenges.embed.ipynb | 16 +-- sections/03-challenges.out.ipynb | 16 ++- sections/03-challenges.qmd | 59 +++++++-- sections/04-cross-sector.embed.ipynb | 2 +- sections/04-cross-sector.out.ipynb | 2 +- sections/05-recommendations-preview.html | 32 +++-- sections/05-recommendations.embed.ipynb | 18 +-- sections/05-recommendations.out.ipynb | 24 ++-- sections/05-recommendations.qmd | 47 ++++--- sections/06-acknowledgments.embed.ipynb | 2 +- sections/06-acknowledgments.out.ipynb | 2 +- 24 files changed, 431 insertions(+), 170 deletions(-) diff --git a/.nojekyll b/.nojekyll index d1baa48..6519021 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -9f6d0f22 \ No newline at end of file +446ef2c6 \ No newline at end of file diff --git a/_tex/index.tex b/_tex/index.tex index bf69372..b36a464 100644 --- a/_tex/index.tex +++ b/_tex/index.tex @@ -269,7 +269,7 @@ \section{Introduction}\label{sec-intro} can help this mode of standards development thrive and reach its full potential. -\section{Use cases}\label{use-cases} +\section{Use cases}\label{sec-use-cases} To understand how OSS development practices affect the development of data and metadata standards, it is informative to demonstrate this @@ -364,12 +364,12 @@ \subsection{Community science}\label{community-science} the science. \section{Opportunities and risks for open-source -standards}\label{sec-opportunities} +standards}\label{sec-challenges} At the same time, these tools and practices are associated with risks that need to be mitigated. -\subsection{Flexibility vs.~stability}\label{flexibility-vs.-stability} +\subsection{Flexibility vs.~Stability}\label{flexibility-vs.-stability} One of the defining characteristics of OSS is its dynamism and its rapid evolution. Because OSS can be used by anyone and, in most cases, @@ -433,33 +433,68 @@ \subsection{Cross-domain funding gaps}\label{cross-domain-funding-gaps} Data standardization investment is justified if the standard is generalizable beyond any specific science domain. However while the use cases are domain sciences based, data standardization is seen as a data -infrastructure and not a science investment. Moreover due to how science -research funding works, scientists lack incentives to work across -domains, or work on infrastructure problems. +infrastructure and not a science investment. Moreover, due to how +science research funding works, scientists lack incentives to work +across domains or to work on infrastructure problems. \subsection{Data instrumentation issues}\label{data-instrumentation-issues} Data for scientific observations are often generated by proprietary -instrumentation due to commercialization or other profit driven -incentives. There islack of regulatory oversight to adhere to available -standards or evolve Significant data transformation is required to get -data to a state that is amenable to standards, if available. If not -available, there is lack of incentive to set aside investment or -resources to invest in establishing data standards. +instrumentation due to commercialization or other profit-driven +incentives. There is a lack of regulatory oversight to adhere to +available standards or evolve Significant data transformation is +required to get data to a state that is amenable to standards, if +available. If not available, there is a lack of incentive to set aside +investment or resources to invest in establishing data standards. + +\subsubsection{Harnessing new computing paradigms and +technologies}\label{harnessing-new-computing-paradigms-and-technologies} + +Open-source standards development faces the challenges of adapting to +new computing paradigms and technologies. Cloud computing provides a +particularly stark set of opportunities and challenges. On the one hand, +cloud computing offers practical solutions for many challenges of +contemporary data-driven research. For example, the scalability of cloud +resources addresses some of the challenges of the scale of data that is +produced by instruments in many fields. The cloud also makes data access +relatively straightforward, because of the ability to determine data +access permissions in a granular fashion. On the other hand, cloud +computing requires reinstrumenting many data formats. This is because +cloud data access patterns are fundamentally different from the ones +that are used in local posix-style file-systems. Suspicion of cloud +computing comes in two different flavors: the first by researchers and +administrators who may be wary of costs associated with cloud computing, +and especially with the difficulty of predicting these costs. Projects +such as NSF's Cloud Bank seek to mitigate some of these concerns, by +providing an additional layer of transparency into cloud costs (Norman +et al. 2021). The other type of objection relates to the fact that cloud +computing services, by their very nature, are closed ecosystems that +resist portability and interoperability. Some aspects of the services +are always going to remain hidden and privy only to the cloud computing +service provider. In this respect, cloud computing runs afoul of some of +the appealing aspects of OSS. That said, the development of ``cloud +native'' standards can provide significant benefits in terms of the +research that can be conducted. For example, NOAA plans to use cloud +computing for integration across the multiple disparate datasets that it +collects to build knowledge graphs that can be queried by researchers to +answer questions that can only be answered through this integration. +Putting all the data ``in one place'' should help with that. Adaptation +to the cloud in terms of data standards has driven development of new +file formats. A salient example is the ZARR format (Miles et al. 2024), +which supports random access into array-based datasets stored in cloud +object storage, facilitating scalable and parallelized computing on +these data. Indeed, data standards such as NWB (neuroscience) and OME +(microscopy) now use ZARR as a backend for cloud-based storage. In other +cases, file formats that were once not straightforward to use in the +cloud, such as HDF5 and TIFF have been adapted to cloud use (e.g., +through the cloud-optimized geoTIFF format). \subsection{Sustainability}\label{sustainability} \subsection{The importance of automated validation}\label{the-importance-of-automated-validation} -\subsection{Harnessing new computing paradigms and -technologies}\label{harnessing-new-computing-paradigms-and-technologies} - -Open-source standards development faces the challenges of adapting to -new technologies The development of standards that are well-Cloud -computing provides - \section{Cross-sector interactions}\label{sec-cross-sector} The importance of standards stems not only from discussions within @@ -569,12 +604,12 @@ \subsection{Industry}\label{industry} device vendors and researchers. \section{Recommendations for open-source data and metadata -standards}\label{recommendations-for-open-source-data-and-metadata-standards} +standards}\label{sec-recommendations} In conclusion of this report, we propose the following recommendations: -\subsection{Funding or Grantmaking -entities:}\label{funding-or-grantmaking-entities} +\subsection{Policy-making and Funding +entities:}\label{policy-making-and-funding-entities} \subsubsection{Fund Data Standards Development}\label{fund-data-standards-development} @@ -588,20 +623,33 @@ \subsubsection{Fund Data Standards The OSS model is seen as a particularly promising avenue for an investment of resources, because it builds on previously-developed procedures and technical infrastructure and because it provides avenues -for community input along the way. The clarity offered by procedures for -enhancement proposals and semantic versioning schemes adopted in -standards development offer avenues for a range of stakeholders to -propose to funding bodies well-defined contributions to large and -field-wide standards efforts. - -\subsubsection{Invest in Data Stewards Recognize data stewards as a -distinct role -in}\label{invest-in-data-stewards-recognize-data-stewards-as-a-distinct-role-in} - -research and science investment. Set up programs for training for data -stewards and invest in career paths that encourage this role. Initial -proposals for the curriculum and scope of the role have already been -proposed (e.g., in (Mons 2018)) +for democratization of development processes and for community input +along the way. The clarity offered by procedures for enhancement +proposals and semantic versioning schemes adopted in standards +development offer avenues for a range of stakeholders to propose to +funding bodies well-defined contributions to large and field-wide +standards efforts (e.g., (Pestilli et al. 2021)). + +\subsubsection{Invest in Data Stewards}\label{invest-in-data-stewards} + +Advancing the development and adoption of open-source standards requires +the dissemination of knowledge to researchers in a variety of fields, +but this dissemination itself may not be enough without the fostering of +specialized expertise. Therefore, it is important to recognize +\emph{data stewards} as a distinct role in research. To truly support +experts whose role will be to develop, maintain, and facilitate the +adoption and use of open-source standards, it will be necessary to set +up programs for training for data stewards and invest in career paths +that encourage this role. Initial proposals for the curriculum and scope +of the role have already been proposed (e.g., in (Mons 2018)). In +addition, in order for these individuals to be able to make the best use +of open-source standards, it will be important for these individuals to +be facile in the methodology of OSS. This does not mean that they need +to become software engineers -- though there may be some overlap with +the role of research software engineers (Connolly et al. 2023) -- but +rather that they need to become familiar with those parts of the OSS +development life-cycle that are useful for development of open-source +standards. \subsubsection{Review Data Standards Pathways}\label{review-data-standards-pathways} @@ -629,14 +677,14 @@ \subsubsection{Establish Governance}\label{establish-governance} \subsubsection{Program Manage Cross Sector alliances}\label{program-manage-cross-sector-alliances} -Encourage cross sector and cross domain alliances that can impact +Encourage cross-sector and cross-domain alliances that can impact successful standards creation. Invest in robust program management of these alliances to align pace and create incentives (for instance via Open Source Program Office / OSPO efforts). Similar to program officers at funding agencies, standards evolution need sustained PM efforts. Multi company partnerships should include strategic initiatives for -standard establishment -e.g.~\href{https://www.pistoiaalliance.org/news/press-release-pistoia-alliance-launches-idmp-1-0/}{Pistoiaalliance}. +standard establishment e.g. +\href{https://www.pistoiaalliance.org/news/press-release-pistoia-alliance-launches-idmp-1-0/}{Pistoiaalliance}. \subsubsection{Curriculum Development}\label{curriculum-development} @@ -646,7 +694,7 @@ \subsubsection{Curriculum Development}\label{curriculum-development} \subsection{Science and Technology Communities:}\label{science-and-technology-communities} -\subsubsection{User Driven Development}\label{user-driven-development} +\subsubsection{User-Driven Development}\label{user-driven-development} Standards should be needs-driven and developed in close collaboration with users. Changes and enhancements should be in response to community @@ -718,6 +766,13 @@ \section*{References}\label{references} et al. 2023. {``Data Preservation in High Energy Physics.''} \emph{The European Physical Journal C} 83 (9): 795. +\bibitem[\citeproctext]{ref-Connolly2023Software} +Connolly, Andrew, Joseph Hellerstein, Naomi Alterman, David Beck, Rob +Fatland, Ed Lazowska, Vani Mandava, and Sarah Stone. 2023. {``{Software} +{Engineering} {Practices} in {Academia}: Promoting the +3Rs---{Readability}, {Resilience}, and {Reuse}.''} \emph{Harvard Data +Science Review} 5 (2). + \bibitem[\citeproctext]{ref-Gorgolewski2016BIDS} Gorgolewski, Krzysztof J, Tibor Auer, Vince D Calhoun, R Cameron Craddock, Samir Das, Eugene P Duff, Guillaume Flandin, et al. 2016. @@ -729,6 +784,12 @@ \section*{References}\label{references} Koch, Christof, and R Clay Reid. 2012. {``Observatories of the Mind.''} \url{http://dx.doi.org/10.1038/483397a}. +\bibitem[\citeproctext]{ref-zarr} +Miles, Alistair, jakirkham, M Bussonnier, Josh Moore, Dimitri +Papadopoulos Orfanos, Davis Bennett, David Stansby, et al. 2024. +{``Zarr-Developers/Zarr-Python: V3.0.0-Alpha.''} Zenodo. +\url{https://doi.org/10.5281/zenodo.11592827}. + \bibitem[\citeproctext]{ref-Mons2018DataStewardshipBook} Mons, Barend. 2018. \emph{Data Stewardship for Open Science: Implementing FAIR Principles}. 1st ed. Vol. 1. Milton: CRC Press. @@ -739,10 +800,25 @@ \section*{References}\label{references} {LEADERSHIP} {IN} {AI}: A Plan for Federal Engagement in Developing Technical Standards and Related Tools.''} +\bibitem[\citeproctext]{ref-Norman2021CloudBank} +Norman, Michael, Vince Kellen, Shava Smallen, Brian DeMeulle, Shawn +Strande, Ed Lazowska, Naomi Alterman, et al. 2021. {``{CloudBank: +Managed Services to Simplify Cloud Access for Computer Science Research +and Education}.''} In \emph{Practice and Experience in Advanced Research +Computing}. PEARC '21. New York, NY, USA: Association for Computing +Machinery. \url{https://doi.org/10.1145/3437359.3465586}. + \bibitem[\citeproctext]{ref-Nosek2019CultureChange} Nosek, Brian. n.d. {``Strategy for Culture Change.''} \url{https://www.cos.io/blog/strategy-for-culture-change}. +\bibitem[\citeproctext]{ref-pestilli2021community} +Pestilli, Franco, Russ Poldrack, Ariel Rokem, Theodore Satterthwaite, +Franklin Feingold, Eugene Duff, Cyril Pernet, Robert Smith, Oscar +Esteban, and Matt Cieslak. 2021. {``A Community-Driven Development of +the Brain Imaging Data Standard (BIDS) to Describe Macroscopic Brain +Connections.''} \emph{OSF}. + \bibitem[\citeproctext]{ref-Poldrack2024BIDS} Poldrack, Russell A, Christopher J Markiewicz, Stefan Appelhoff, Yoni K Ashar, Tibor Auer, Sylvain Baillet, Shashank Bansal, et al. 2024. {``The diff --git a/_tex/references.bib b/_tex/references.bib index f05565f..312dee3 100644 --- a/_tex/references.bib +++ b/_tex/references.bib @@ -1,3 +1,80 @@ +@software{zarr, + author = {Alistair Miles and + jakirkham and + M Bussonnier and + Josh Moore and + Dimitri Papadopoulos Orfanos and + Davis Bennett and + David Stansby and + Joe Hamman and + James Bourbeau and + Andrew Fulton and + Gregory Lee and + Ryan Abernathey and + Norman Rzepka and + Zain Patel and + Mads R. B. Kristensen and + Sanket Verma and + Saransh Chopra and + Matthew Rocklin and + AWA BRANDON AWA and + Max Jones and + Martin Durant and + Elliott Sales de Andrade and + Vincent Schut and + raphael dussin and + Shivank Chaudhary and + Chris Barnes and + Juan Nunez-Iglesias and + shikharsg}, + title = {zarr-developers/zarr-python: v3.0.0-alpha}, + month = jun, + year = 2024, + publisher = {Zenodo}, + version = {v3.0.0-alpha}, + doi = {10.5281/zenodo.11592827}, + url = {https://doi.org/10.5281/zenodo.11592827} +} + +@inproceedings{Norman2021CloudBank, +author = {Norman, Michael and Kellen, Vince and Smallen, Shava and DeMeulle, Brian and Strande, Shawn and Lazowska, Ed and Alterman, Naomi and Fatland, Rob and Stone, Sarah and Tan, Amanda and Yelick, Katherine and Van Dusen, Eric and Mitchell, James}, +title = {{CloudBank: Managed Services to Simplify Cloud Access for Computer Science Research and Education}}, +year = {2021}, +isbn = {9781450382922}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3437359.3465586}, +doi = {10.1145/3437359.3465586}, +abstract = {CloudBank is a cloud access entity founded to enable the computer science research and education communities to harness the profound computational potential of public clouds. By delivering a set of managed services designed to alleviate common points of friction associated with cloud adoption, Cloudbank serves as an integrated service provider to the research and education community. These services include front-line help desk support, cloud solution consulting, training, account management, cost monitoring and optimization support, and automated billing. CloudBank has a multi-cloud pay-per-use billing model and aims to serve the spectrum of cloud users from novice to advanced.}, +booktitle = {Practice and Experience in Advanced Research Computing}, +articleno = {45}, +numpages = {4}, +keywords = {Cloud Computing}, +location = {Boston, MA, USA}, +series = {PEARC '21} +} + +@article{Connolly2023Software, + author = {Connolly, Andrew and Hellerstein, Joseph and Alterman, Naomi and Beck, David and Fatland, Rob and Lazowska, Ed and Mandava, Vani and Stone, Sarah}, + journal = {Harvard Data Science Review}, + number = {2}, + year = {2023}, + month = {apr 27}, + note = {https://hdsr.mitpress.mit.edu/pub/f0f7h5cu}, + publisher = {}, + title = { + +{Software} {Engineering} {Practices} in {Academia}: Promoting the 3Rs---{Readability}, {Resilience}, and {Reuse}}, + volume = {5}, +} + +@article{pestilli2021community, + title={A community-driven development of the Brain Imaging Data Standard (BIDS) to describe macroscopic brain connections}, + author={Pestilli, Franco and Poldrack, Russ and Rokem, Ariel and Satterthwaite, Theodore and Feingold, Franklin and Duff, Eugene and Pernet, Cyril and Smith, Robert and Esteban, Oscar and Cieslak, Matt}, + journal={OSF}, + year={2021} +} + @MISC{Nosek2019CultureChange, title = "Strategy for Culture Change", author = "Nosek, Brian", diff --git a/index.docx b/index.docx index 8850c496c24cfa69d46decf0c4d25aae059aa971..d49d1c2982717192ea8f0a17955277f66967343e 100644 GIT binary patch delta 19133 zcmV((K;XZx!~vMr0Sr(}0|XQR0tg5IimkB>vH=2$t+T)Z4gn5|tbsnOv9S@1A_TeBD2I^7p_0yMLRPxyhQTDr*6sFYU{l@19KRdiHX2 z(`FMjm3Cles)XN-Of{7?{IeQw-k2(%RVGu`!q-iU&FyE;_BW?emrvZ+Oz-nGW;D{7 zI(7^2Us6x}msDT-C6y{<4exCydS?B%neU!7Rr%6=Re!3p%2+e1`Fg`M0sg9Ps_=R@v#J_ZPte)@fRch_OFepf49}& z;r|eSnTWr95r1iL3E>-7EWoOntYqyUddH_!nfr4LZ@1Z%hRq<9Lu0O{vbwscL4x3$ zbpG9w?PvIsrJTZ-HD#_Uuz$F^CVxX~>>hr%I5}C`T0@w&2IBwypa1oL#YcRah@VD3 zzx%kBF5tDUYz;R;jw?Bvtg(!2U$~9u)D=v(5594;fa#h^Uf9xmTr$f*po7kj&<|SGv8{@Tz?MXyJc3V zIO*+yICNkCSf_ffGIWf=-5JBrtk9*H%50)bCE&cP65c?7`WCPm8eBXr3;0N_ib9XU z)mHe2Q*D(MwMk|7@@t7t!XL;AqzRWpLPUmz7KpB>6;j;j96l(^FQO) zq_1_Yl^uvvkbHQOn)YCWvVRKi3hWv)TPv@XC{2xv z$u-_uF!yu8>xNw{WCaI0Ylel+;OFvM>ViA~+&Zhki5JJXi59dxEPp=PM*g+YmBI+j ziV=uCugFe75NTIOER;PVE$G9d!2hMs894b$fV5tzi7DtaDR)v9)(Diq8ukupQXCX22M)Uda4HE z61FIc6GaZESeO|lVko-98-5KM+X}14C8{HdrpTZh28Jft8Gn~*q-(TTbc!z0$3yhH z)}CzGF8U{F`5BtRtO2FeODKu)W_1@4FBJSLS(3mOrX2T!L9`~*reCXUQo^RD+DW%_ zij9LHL%Rll&hhS|nH(ozq&L z_CzbAwm~yzqjl7Z6+B8H2EV#&Ok+u@jw^ndL`&qbsDHgM-YrB)Ty|SJ5)p0=-u+=J z1tfDb!%cz(<)AN1ZwYC)e8wmePv`Uu#D$)MS+9zDPo&Qhj?vzf(nTU{Ok^7Y#6B1N z{Mu;v;LFjjJ;zav45FdCi*~6W{M^fFG_y*9T(DYRmrV}XHS803Y_RV`d zLp*A)`$>{n$)~l3_f9x$tx7m-w+RQUvOX-mGAS|+JLuBX6lkHod#tPjhHLmzs?36xdIH?QTK98^WJ*gJiJq7!jJ9Bf3f%;@ ze}ANr7B2n6t?Jw2@_S!z|rH2pB*u*5wbLMxc>#2b~!V6K6TazoW z(mCzxYYpxKryP6YFr!+!`)8s>p0>G=Hq&{oFd@SK-gtd@dj1r*F=4TD}kPW_1 ziOF)@7l`~zm7%9xr}K9yc0uxPihr!=1#VGRp;F!%xfrKCcP z4;d0IacroPA+swVuq*bG>VWVltOW`P zzA*7hnSe~qxK6+e!P0(Pj(;I%gxk5R00W40`gLze-CDvGYGe01laKW=oc3Jm_KXjSM8qkmYq5$^D5nHm>_ z>WMSQ@H%klbgrV(<4JAPt#6sQhrBw)*RA|ncoj@in4&Fb;m6+SR9QThrhbO$S1RXH zInQeoFaLK{`4JL0D$Gq%^bl9UL{zU@R&H)fxNq8$k(|LvOYnhhTZ>C&R*aJ^ndcQH zqA)c!K?_rk6=lRixqp0l0ZVxJOuA+PTHsXW8qLE{)i+q1WEEXD(;>h| z<@`^StM94Ek`SJWa%aAlI#LodjMnL)UVEV~S!Rkt4u4J6R_tM6SPTG{$LVjv z@4&u>brME{Ri@$VlFFh~3hQCCgKdgpUdkz0URtZK{ajOakrBv*daE#zQF_RUOZ=sC z9wa7du;_BD)(l%jhKJUH(5ohbl(fz)x^M7T=|oXiR1S3&E3ZIAT=9K`*yMNxZh-7B zDQ{=k_<%7*pMQnhAvV@{?Vo@8mvxRYIY!}YvWY+c^uJRXA}p|hCsa?K@+qJYR!Yt| z>Twdac$hm}5NZFHx(UXI4+-1ZWWkA~9C2$6p1mJ`3fKPDGL89fU&$9xZv5C`x zEv|^S5G9wD;%LNHamfq#oNuBv-o9N7!sLyC$h9cIx_@Z!EgA{{G3>(dJF-NvMoYBH z0D1WxCc9`+aOMa{pMzqYDldYOb3`gZ*CY6Ws~sXzogo3KFKv8=J&yimgaL)1B5SDP zMaB5Og~K<_S94{?-zD_d{0y264#tTT5W55_wTNEV%HJZ-0eNJ#s%Y?iE1luFO> zc`Zj0VSfoqJ9siEBkUPMlzjuQ7I0JdM%HYvLe{+KB5Obz`y`Di&^5aQ@zG2BnpXC! 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Table of contents

  • 1 🚧 Under construction 🚧
  • 2 Abstract
  • 3 Introduction
  • -
  • 4 Use cases +
  • 4 Use cases
  • -
  • 5 Opportunities and risks for open-source standards +
  • 5 Opportunities and risks for open-source standards
  • 6 Cross-sector interactions
  • -
  • 7 Recommendations for open-source data and metadata standards +
  • 7 Recommendations for open-source data and metadata standards
      -
    • 7.1 Funding or Grantmaking entities: +
    • 7.1 Policy-making and Funding entities:
    • 7.2 Science and Technology Communities:
        -
      • 7.2.1 User Driven Development
      • +
      • 7.2.1 User-Driven Development
      • 7.2.2 Meta-Standards development
      • 7.2.3 Ontology Development
      • 7.2.4 Formalization Guidelines
      • @@ -213,7 +219,7 @@

        3 IntroductionCommunity-driven development of robust, adaptable and useful standards draws significant inspiration from the development of open-source software (OSS) and has many parallels and overlaps with OSS development. OSS has a long history going back to the development of the Unix operating system in the late 1960s. Over the time since its inception, the large community of developers and users of OSS have developed a host of socio-technical mechanisms that support the development and use of OSS. For example, the Open Source Initiative (OSI), a non-profit organization that was founded in the 1990s developed a set of guidelines for licensing of OSS that is designed to protect the rights of developers and users. On the more technical side, tools such as the Git Source-code management system support open-source development workflows that can be adopted in the development of standards. Governance approaches have been honed to address the challenges of managing a range of stakeholder interests and to mediate between large numbers of weakly-connected individuals that contribute to OSS. When these social and technical innovations are put together they enable a host of positive defining features of OSS, such as transparency, collaboration, and decentralization. These features allow OSS to have a remarkable level of dynamism and productivity, while also retaining the ability of a variety of stakeholders to guide the evolution of the software to take their needs and interests into account.

        Data and metadata standards that adopt tools and practices of OSS (“open-source standards” henceforth) stand to reap many of the benefits that the OSS model has provided in the development of other technologies.The present report explore how OSS processes and tools have affected the development of data and metadata standards. The report will triangulate common features of a variety of use cases; it will identify some of the challenges and pitfalls of this mode of standards development, with a particular focus on cross-sector interactions; and it will make recommendations for future developments and policies that can help this mode of standards development thrive and reach its full potential.

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        +

        4 Use cases

        To understand how OSS development practices affect the development of data and metadata standards, it is informative to demonstrate this cross-fertilization through a few use cases. As we will see in these examples some fields, such as astronomy, high-energy physics and earth sciences have a relatively long history of shared data resources from organizations such as LSST and CERN, while other fields have only relatively recently become aware of the value of data sharing and its impact. These disparate histories inform how standards have evolved and how OSS practices have pervaded their development.

        @@ -240,11 +246,11 @@

        Another interesting use case for open-source standards is community/citizen science. This approach, which has grown Here, standards are needed to facilitate interactions between an in-group of expert researchers who generate and curate data and a broader set of out-group enthusiasts who would like to make meaningful contributions to the science.

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        +

        5 Opportunities and risks for open-source standards

        At the same time, these tools and practices are associated with risks that need to be mitigated.

        -

        5.1 Flexibility vs. stability

        +

        5.1 Flexibility vs. Stability

        One of the defining characteristics of OSS is its dynamism and its rapid evolution. Because OSS can be used by anyone and, in most cases, contributions can be made by anyone, innovations flow into OSS in a bottom-up fashion from user/developers. Pathways to contribution by members of the community are often well-defined: both from the technical perspective (e.g., through a pull request on GitHub, or other similar mechanisms), as well as from the social perspective (e.g., whether contributors need to accept certain licensing conditions through a contributor licensing agreement) and the socio-technical perspective (e.g., how many people need to review a contribution, what are the timelines for a contribution to be reviewed and accepted, what are the release cycles of the software that make the contribution available to a broader community of users, etc.). Similarly, open-source standards may also find themselves addressing use cases and solutions that were not originally envisioned through bottom-up contributions of members of a research community to which the standard pertains. However, while this dynamism provides an avenue for flexibility it also presents a source of tension. This is because data and metadata standards apply to already existing datasets, and changes may affect the compliance of these existing datasets. Similarly, analysis technology stacks that are developed based on an existing version of a standard have to adapt to the introduction of new ideas and changes into a standard. Dynamic changes of this sort therefore risk causing a loss of faith in the standard by a user community, and migration away from the standard. Similarly, if a standard evolves too rapidly, users may choose to stick to an outdated version of a standard for a long time, creating strains on the community of developers and maintainers of a standard who will need to accommodate long deprecation cycles.

        @@ -257,11 +263,15 @@

        5.4 Cross-domain funding gaps

        -

        Data standardization investment is justified if the standard is generalizable beyond any specific science domain. However while the use cases are domain sciences based, data standardization is seen as a data infrastructure and not a science investment. Moreover due to how science research funding works, scientists lack incentives to work across domains, or work on infrastructure problems.

        +

        Data standardization investment is justified if the standard is generalizable beyond any specific science domain. However while the use cases are domain sciences based, data standardization is seen as a data infrastructure and not a science investment. Moreover, due to how science research funding works, scientists lack incentives to work across domains or to work on infrastructure problems.

        5.5 Data instrumentation issues

        -

        Data for scientific observations are often generated by proprietary instrumentation due to commercialization or other profit driven incentives. There islack of regulatory oversight to adhere to available standards or evolve Significant data transformation is required to get data to a state that is amenable to standards, if available. If not available, there is lack of incentive to set aside investment or resources to invest in establishing data standards.

        +

        Data for scientific observations are often generated by proprietary instrumentation due to commercialization or other profit-driven incentives. There is a lack of regulatory oversight to adhere to available standards or evolve Significant data transformation is required to get data to a state that is amenable to standards, if available. If not available, there is a lack of incentive to set aside investment or resources to invest in establishing data standards.

        +
        +

        5.5.1 Harnessing new computing paradigms and technologies

        +

        Open-source standards development faces the challenges of adapting to new computing paradigms and technologies. Cloud computing provides a particularly stark set of opportunities and challenges. On the one hand, cloud computing offers practical solutions for many challenges of contemporary data-driven research. For example, the scalability of cloud resources addresses some of the challenges of the scale of data that is produced by instruments in many fields. The cloud also makes data access relatively straightforward, because of the ability to determine data access permissions in a granular fashion. On the other hand, cloud computing requires reinstrumenting many data formats. This is because cloud data access patterns are fundamentally different from the ones that are used in local posix-style file-systems. Suspicion of cloud computing comes in two different flavors: the first by researchers and administrators who may be wary of costs associated with cloud computing, and especially with the difficulty of predicting these costs. Projects such as NSF’s Cloud Bank seek to mitigate some of these concerns, by providing an additional layer of transparency into cloud costs (Norman et al. 2021). The other type of objection relates to the fact that cloud computing services, by their very nature, are closed ecosystems that resist portability and interoperability. Some aspects of the services are always going to remain hidden and privy only to the cloud computing service provider. In this respect, cloud computing runs afoul of some of the appealing aspects of OSS. That said, the development of “cloud native” standards can provide significant benefits in terms of the research that can be conducted. For example, NOAA plans to use cloud computing for integration across the multiple disparate datasets that it collects to build knowledge graphs that can be queried by researchers to answer questions that can only be answered through this integration. Putting all the data “in one place” should help with that. Adaptation to the cloud in terms of data standards has driven development of new file formats. A salient example is the ZARR format (Miles et al. 2024), which supports random access into array-based datasets stored in cloud object storage, facilitating scalable and parallelized computing on these data. Indeed, data standards such as NWB (neuroscience) and OME (microscopy) now use ZARR as a backend for cloud-based storage. In other cases, file formats that were once not straightforward to use in the cloud, such as HDF5 and TIFF have been adapted to cloud use (e.g., through the cloud-optimized geoTIFF format).

        +

        5.6 Sustainability

        @@ -269,10 +279,6 @@

        5.7 The importance of automated validation

        -
        -

        5.8 Harnessing new computing paradigms and technologies

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        Open-source standards development faces the challenges of adapting to new technologies The development of standards that are well-Cloud computing provides

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        6 Cross-sector interactions

        @@ -292,18 +298,18 @@