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diff --git a/.nojekyll b/.nojekyll
@@ -1 +1 @@
-eb1f2ff1
+01dbea7f
diff --git a/_tex/elsarticle.cls b/_tex/elsarticle.cls
@@ -1011,8 +1011,7 @@
          \ifx\@elsarticlemyfooteralign\@elsarticlemyfooteralignright%
            {}\hfill\@elsarticlemyfooter%
          \else%
-               Preprint submitted to \ifx\@journal\@empty%
-                 Elsevier%
+               \ifx\@journal\@empty%
             \else\@journal\fi\hfill\@date\fi%
          \fi%
          \fi%

diff --git a/_tex/index.tex b/_tex/index.tex
@@ -4,8 +4,7 @@
 \PassOptionsToPackage{dvipsnames,svgnames,x11names}{xcolor}
 %
 \documentclass[
-  number,
-  preprint]{elsarticle}
+  number]{elsarticle}
 
 \usepackage{amsmath,amssymb}
 \usepackage{iftex}
@@ -157,28 +156,39 @@
 
 \begin{frontmatter}
 \title{Towards an open-source model for data and metadata standards}
-\author[1]{Ariel Rokem%
+\author[1,2]{Ariel Rokem%
 \corref{cor1}%
 }
-
-\author[1]{Vani Mandava%
+ \ead{[email protected]} 
+\author[3,2]{Vani Mandava%
 %
 }
 
-\author[1]{Nicoleta Cristea%
+\author[4,2]{Nicoleta Cristea%
 %
 }
 
-\author[1]{Anshul Tambay%
+\author[3,2]{Anshul Tambay%
 %
 }
 
-\author[1]{Andrew J. Connolly%
+\author[5,2]{Andrew J. Connolly%
 %
 }
 
 
-\affiliation[1]{organization={University of Washington},,postcodesep={}}
+\affiliation[1]{organization={University of Washington, Department of
+Psychology},city={Seattle},country={USA},countrysep={,},postcodesep={}}
+\affiliation[2]{organization={University of Washington, eScience
+Institute},city={Seattle},country={USA},countrysep={,},postcodesep={}}
+\affiliation[3]{organization={University of Washington, Scientific
+Software Engineering
+Center},city={Seattle},country={USA},countrysep={,},postcodesep={}}
+\affiliation[4]{organization={University of Washington, Department of
+Civil and Environmental
+Engineering},city={Seattle},country={USA},countrysep={,},postcodesep={}}
+\affiliation[5]{organization={University of Washington, Department of
+Astronomy},city={Seattle},country={USA},countrysep={,},postcodesep={}}
 
 \cortext[cor1]{Corresponding author}
 
@@ -187,6 +197,30 @@
 
 
 
+\begin{abstract}
+Progress in machine learning and artificial intelligence promises to
+advance research and understanding across a wide range of fields and
+activities. In tandem, increased awareness of the importance of open
+data for reproducibility and scientific transparency is making inroads
+in fields that have not traditionally produced large publicly available
+datasets. Data sharing requirements from publishers and funders, as well
+as from other stakeholders, have also created pressure to make datasets
+with research and/or public interest value available through digital
+repositories. However, to make the best use of existing data, and
+facilitate the creation of useful future datasets, robust, interoperable
+and usable standards need to evolve and adapt over time. The open-source
+development model provides significant potential benefits to the process
+of standard creation and adaptation. In particular, data and meta-data
+standards can use long-standing technical and socio-technical processes
+that have been key to managing the development of software, and which
+allow incorporating broad community input into the formulation of these
+standards. On the other hand, open-source models carry unique risks that
+need to be considered. This report surveys existing open-source
+standards development, addressing these benefits and risks. It outlines
+recommendations for standards developers, funders and other stakeholders
+on the path to robust, interoperable and usable open-source data and
+metadata standards.
+\end{abstract}
 
 
 

diff --git a/index.docx b/index.docx
diff --git a/index.html b/index.html
diff --git a/index.pdf b/index.pdf
diff --git a/sections/01-introduction.embed.ipynb b/sections/01-introduction.embed.ipynb
@@ -14,7 +14,7 @@
     "\n",
     "Data and metadata standards that use tools and practices of OSS (“open-source standards” henceforth) reap many of the benefits that the OSS model has provided in the development of other technologies. The present report explores how OSS processes and tools have affected the development of data and metadata standards. The report will survey 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."
    ],
-   "id": "68bde417-020e-4d9e-a92f-f840cd71e28e"
+   "id": "d02bb291-b4b8-4602-a2a8-23d2dd510c62"
   }
  ],
  "nbformat": 4,

diff --git a/sections/01-introduction.out.ipynb b/sections/01-introduction.out.ipynb
@@ -18,7 +18,7 @@
     "\n",
     "Wilkinson, Mark D, Michel Dumontier, I Jsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, et al. 2016. “The FAIR Guiding Principles for Scientific Data Management and Stewardship.” *Sci Data* 3 (March): 160018."
    ],
-   "id": "7da720b3-7fa5-403a-af57-3bf15d92134b"
+   "id": "48c2a4bb-4105-41c4-8095-10d9e6097de2"
   }
  ],
  "nbformat": 4,

diff --git a/sections/02-use-cases.embed.ipynb b/sections/02-use-cases.embed.ipynb
@@ -30,7 +30,7 @@
     "\n",
     "Another interesting use case for open-source standards is community/citizen science. An early example of this approach is OpenStreetMap <https://www.openstreetmap.org>, which allows users to contribute to the project development with code and data and freely use the maps and other related geospatial datasets. But this example is not unique. Overall, this approach has grown in the last 20 years and has been adopted in many different fields. It has many benefits for both the research field that harnesses the energy of non-scientist members of the community to engage with scientific data, as well as to the community members themselves who can draw both knowledge and pride in their participation in the scientific endeavor. It is also recognized that unique broader benefits are accrued from this mode of scientific research, through the inclusion of perspectives and data that would not otherwise be included. To make data accessible to community scientists, and to make the data collected by community scientists accessible to professional scientists, it needs to be provided in a manner that can be created and accessed without specialized instruments or specialized knowledge. 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. This creates a particularly stringent constraint on transparency and simplicity of standards. Creating these standards in a manner that addresses these unique constraints can benefit from OSS tools, with the caveat that some of these tools require additional expertise. For example, if the standard is developed using git/GitHub for versioning, this would require learning the complex and obscure technical aspects of these system that are far from easy to adopt, even for many professional scientists."
    ],
-   "id": "ef5062bb-b877-4616-af91-700689bf08f5"
+   "id": "ff672cd8-8dce-4c1b-9aac-08cc40350ede"
   }
  ],
  "nbformat": 4,

diff --git a/sections/02-use-cases.out.ipynb b/sections/02-use-cases.out.ipynb
@@ -46,7 +46,7 @@
     "\n",
     "Wells, Donald Carson, and Eric W Greisen. 1979. “FITS-a Flexible Image Transport System.” In *Image Processing in Astronomy*, 445."
    ],
-   "id": "2c933bd2-5896-4057-b68c-bf2f3c8b7c4e"
+   "id": "9b5dc5b7-dbc4-4772-9858-2881bd004aea"
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diff --git a/sections/03-challenges.embed.ipynb b/sections/03-challenges.embed.ipynb
@@ -36,7 +36,7 @@
     "\n",
     "The development of open-source standards faces similar sustainability challenges to those faced by open-source software that is developed for research. Standards typically develop organically through sustained and persistent efforts from dedicated groups of data practitioners. These include scientists and the broader ecosystem of data curators and users. However, there is no playbook on the structure and components of a data standard, or the pathway that moves the implementation of a specific data architecture (e.g., a particular file format) to become a data standard. As a result, data standardization lacks formal avenues for success and recognition, for example through dedicated research grants (and see @sec-cross-sector). This hampers the long-term trajectory that is needed to inculcate a standard into the day-to-day practice of researchers."
    ],
-   "id": "7d52d5df-1bff-4f33-953f-19961bc39f4f"
+   "id": "38d90182-3c94-44b8-8717-52db26fa239f"
   }
  ],
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diff --git a/sections/03-challenges.out.ipynb b/sections/03-challenges.out.ipynb
@@ -50,7 +50,7 @@
     "\n",
     "Scroggins, Michael, and Bernadette M Boscoe. 2020. “Once FITS, Always FITS? Astronomical Infrastructure in Transition.” *IEEE Ann. Hist. Comput.* 42 (2): 42–54."
    ],
-   "id": "fd61dd54-746b-4707-a6be-52949ef8fc38"
+   "id": "f5bee5d8-62e8-4a34-a57b-742e348bf718"
   }
  ],
  "nbformat": 4,

diff --git a/sections/04-cross-sector.embed.ipynb b/sections/04-cross-sector.embed.ipynb
@@ -26,7 +26,7 @@
     "\n",
     "Interactions of data and meta-data standards with commercial interests may provide specific sources of friction. This is because proprietary/closed formats of data can create difficulty at various transition points: from one instrument vendor to another, from data producer to downstream recipient/user, etc. On the other hand, in some cases, cross-sector collaborations with commercial entities may pave the way to robust and useful standards. For example, imaging measurements in human subjects (e.g., in brain imaging experiments) significantly interact with standards for medical imaging, and chiefly the Digital Imaging and Communications in Medicine (DICOM) standard, which is widely used in a range of medical imaging applications, including in clinical settings \\[@Larobina2023-vq, @Mustra2008-xk\\]. The standard emerged from the demands of the clinical practice in the 1980s, as digital technologies were came into widespread use in medical imaging, through joint work of industry organizations: the American College of Radiology and the National Association of Electronic Manufacturers. One of the defining features of the DICOM standard is that it allows manufacturers of instruments to define “private fields” that are compliant with the standard, but which may include idiosyncratically organized data and/or metadata. This provides significant flexibility, but can also easily lead to the loss of important information. Nevertheless, the human brain imaging case is exemplary of a case in which industry standards and research standards coexist and need to communicate with each other effectively to advance research use-cases, while keeping up with the rapid development of the technologies."
    ],
-   "id": "0bebd3ba-5622-4f33-9807-7960ad37c350"
+   "id": "e94ab12b-95c1-4d7d-8192-aba2657707bf"
   }
  ],
  "nbformat": 4,

diff --git a/sections/04-cross-sector.out.ipynb b/sections/04-cross-sector.out.ipynb
@@ -36,7 +36,7 @@
     "\n",
     "The National Science and Technology Council. 2022. “Desirable Characteristics of Data Repositories for Federally Funded Research.” *Executive Office of the President of the United States, Tech. Rep*."
    ],
-   "id": "d6f8e2f9-560a-42df-bdb6-cf3905d5f6e9"
+   "id": "6ca2495f-f0dd-49b2-be58-a8c7963cf025"
   }
  ],
  "nbformat": 4,

diff --git a/sections/05-recommendations.embed.ipynb b/sections/05-recommendations.embed.ipynb
@@ -48,7 +48,7 @@
     "\n",
     "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 Offices at Universities or other research organizations). Similar to program officers at funding agencies, standards evolution need sustained PM efforts. Multi-party partnerships should include strategic initiatives for standard establishment such as the Pistoia Alliance (<https://www.pistoiaalliance.org/>)."
    ],
-   "id": "3e49d810-d49a-4958-bcf7-55426adb57e7"
+   "id": "50ce2ff0-f8a1-4217-86eb-719284b7497f"
   }
  ],
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diff --git a/sections/05-recommendations.out.ipynb b/sections/05-recommendations.out.ipynb
@@ -56,7 +56,7 @@
     "\n",
     "Van Tuyl, Steve, ed. 2023. “Hiring, Managing, and Retaining Data Scientists and Research Software Engineers in Academia: A Career Guidebook from ADSA and US-RSE.” https://doi.org/<https://doi.org/10.5281/zenodo.8329337>."
    ],
-   "id": "eb33bfc5-b60f-4b10-8bda-29232ec74ea8"
+   "id": "9ab74357-d558-4d82-8e42-0ea2d9744e94"
   }
  ],
  "nbformat": 4,

diff --git a/sections/06-acknowledgments.embed.ipynb b/sections/06-acknowledgments.embed.ipynb
@@ -12,7 +12,7 @@
     "\n",
     "The workshop and this report were funded through [NSF grant #2334483](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334483&HistoricalAwards=false) from the NSF [Pathways to Enable Open-Source Ecosystems (POSE)](https://new.nsf.gov/funding/opportunities/pathways-enable-open-source-ecosystems-pose) program. The opinions expressed in this report do not necessarily reflect those of the National Science Foundation."
    ],
-   "id": "5a18aaf7-37e3-4e6a-a304-c2d751ff10ec"
+   "id": "3fc54093-97fa-47c3-b4ef-7b24d6fc05ef"
   }
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diff --git a/sections/06-acknowledgments.out.ipynb b/sections/06-acknowledgments.out.ipynb
@@ -12,7 +12,7 @@
     "\n",
     "The workshop and this report were funded through [NSF grant #2334483](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334483&HistoricalAwards=false) from the NSF [Pathways to Enable Open-Source Ecosystems (POSE)](https://new.nsf.gov/funding/opportunities/pathways-enable-open-source-ecosystems-pose) program. The opinions expressed in this report do not necessarily reflect those of the National Science Foundation."
    ],
-   "id": "984dce61-ec9d-4dde-9892-f301b193aea0"
+   "id": "ba5572ae-0800-44e1-bbc1-c1b6ed88796c"
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diff --git a/sections/07-participants.embed.ipynb b/sections/07-participants.embed.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "#"
    ],
-   "id": "57fde416-2560-43ab-8de7-fefcc0e58fe4"
+   "id": "4153eeae-c6e8-4454-aa23-75e01d7e6c3c"
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@@ -16,7 +16,7 @@
    "source": [
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-   "id": "e8974446-5b62-449f-8597-a51dd2e3f857"
+   "id": "d901c59b-f4d3-432f-a824-4c0ed4d9fa65"
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    "cell_type": "markdown",
@@ -56,7 +56,7 @@
     "| Yaroslav Halchenko        | Dartmouth University                 |\n",
     "| Ziheng Sun                | George Mason University              |"
    ],
-   "id": "aedfbf1a-c4e4-4278-9098-503e5491c72b"
+   "id": "2371d360-6936-4bcb-ac12-421c5d52c27b"
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diff --git a/sections/07-participants.out.ipynb b/sections/07-participants.out.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "#"
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-   "id": "e360e076-4c8a-4ace-b97b-a2fcb2c6e424"
+   "id": "ec366097-577e-4a8a-ac3e-61b1168bf13d"
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@@ -16,7 +16,7 @@
    "source": [
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-   "id": "ffe29adb-59ae-44b3-a68d-6c97a386e373"
+   "id": "1f205ac9-5c6d-4b1f-8716-10a7cc4f2f8e"
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   {
    "cell_type": "markdown",
@@ -56,7 +56,7 @@
     "| Yaroslav Halchenko        | Dartmouth University                 |\n",
     "| Ziheng Sun                | George Mason University              |"
    ],
-   "id": "b589ce0b-ff24-4057-915b-215a91e7ab02"
+   "id": "77ad6633-9631-4c37-b07b-18e219d45e40"
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