More on citizen science.

references.bib

@@ -1,3 +1,24 @@
+
+@ARTICLE{Musen2022metadata,
+  title     = "Without appropriate metadata, data-sharing mandates are
+               pointless",
+  author    = "Musen, Mark A",
+  abstract  = "Funders and investigators must demand appropriate metadata
+               standards to take data from foul to FAIR. Funders and
+               investigators must demand appropriate metadata standards to take
+               data from foul to FAIR.",
+  journal   = "Nature",
+  publisher = "Springer Science and Business Media LLC",
+  volume    =  609,
+  number    =  7926,
+  pages     = "222",
+  month     =  sep,
+  year      =  2022,
+  keywords  = "Research data; Research management",
+  language  = "en"
+}
+
+
 @software{zarr,
   author       = {Alistair Miles and
                   jakirkham and

sections/01-introduction.qmd

@@ -10,14 +10,14 @@ understand everything from the cellular operations of the human body, through
 business transactions on the internet, to the structure and history of the
 universe. However, the development of new machine learning methods and
 data-intensive discovery more generally depends on Findability, Accessibility,
-Interoperability and Reusability (FAIR) of data [@Wilkinson2016FAIR]. One of
-the main mechanisms through which the FAIR principles are promoted is the
-development of *standards* for data and metadata. Standards can vary in the
-level of detail and scope, and encompass such things as *file formats* for the
-storage of certain data types, *schemas* for databases that organize data,
-*ontologies* to describe and organize metadata in a manner that connects it to
-field-specific meaning, as well as mechanisms to describe *provenance* of
-analysis products.
+Interoperability and Reusability (FAIR) of data [@Wilkinson2016FAIR] as well as
+metadata [@Musen2022metadata]. One of the main mechanisms through which the
+FAIR principles are promoted is the development of *standards* for data and
+metadata. Standards can vary in the level of detail and scope, and encompass
+such things as *file formats* for the storage of certain data types, *schemas*
+for databases that organize data, *ontologies* to describe and organize
+metadata in a manner that connects it to field-specific meaning, as well as
+mechanisms to describe *provenance* of analysis products.
 
 Community-driven development of robust, adaptable and useful standards draws
 significant inspiration from the development of open-source software (OSS) and
@@ -28,24 +28,24 @@ 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.
+developers and users. On the technical side, tools such as the Git Source-code
+management system support complex and distributed open-source workflows that
+accelerate, streamline, and robustify OSS development. 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
+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 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.

sections/02-use-cases.qmd

@@ -8,18 +8,21 @@ history of shared data resources from organizations such as LSST, CERN, and
 NASA, 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.
+It also demonstrates field-specific limitations on the adoption of OSS tools
+and practices that exemplify some of the challenges, which we will explore
+subsequently.
 
 ## Astronomy
 
-One prominent example of a community-driven standard is the FITS (Flexible
+An early prominent example of a community-driven standard is the FITS (Flexible
 Image Transport System) file format standard, which was developed in the late
 1970s and early 1980s [@wells1979fits], and has been adopted worldwide for
 astronomy data preservation and exchange. Essentially every software platform
 used in astronomy reads and writes the FITS format. It was developed by
 observatories in the 1980s to store image data in the visible and x-ray
 spectrum. It has been endorsed by IAU, as well as funding agencies. Though the
 format has evolved over time, “once FITS, always FITS”. That is, the format
-cannot be evolved to introduce changes that break backwards compatibility.
+cannot be evolved to introduce changes that break backward compatibility.
 Among the features that make FITS so durable is that it was designed originally
 to have a very restricted metadata schema. That is, FITS records were designed
 to be the lowest common denominator of word lengths in computer systems at the
@@ -34,12 +37,13 @@ conforming images obsolete.
 Because data collection is centralized, standards to collect and store HEP data
 have been established and the adoption of these standards in data analysis has
 high penetration [@Basaglia2023-dq]. A top-down approach is taken so that
-within every large collaboration standards are enforced, and this adoption is
-centrally managed. Access to raw data is essentially impossible, and making it
-publicly available is both technically very hard and potentially ill-advised.
-Therefore, analysis tools are tuned specifically to the standards. Incentives
-to use the standards are provided by funders that require data management plans
-that specify how the data is shared.
+within every large collaboration, standards are enforced, and this adoption is
+centrally managed. Access to raw data is essentially impossible because of its
+large volume, and making it publicly available is both technically very hard
+and potentially ill-advised. Therefore, analysis tools are tuned specifically
+to the standards of the released data. Incentives to use the standards are
+provided by funders that require data management plans that specify how the
+data is shared (i.e., in a standards-compliant manner).
 
 ## Earth sciences
 
@@ -74,9 +78,27 @@ slightly different technical approach, it tries to emulate the open-ended and
 community-driven aspects of Python development to accept contributions from a
 wide range of stakeholders and tap a broad base of expertise.
 
-## Automated discovery
-
 ## Community science
 
-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.
+Another interesting use case for open-source standards is community/citizen
+science. This approach, which has grown in the last 20 years, 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.