More links.

sections/02-use-cases.qmd

@@ -86,8 +86,7 @@ some standards have been developed in the industry (e.g., Keyhole Markup
 Language (KML) by Keyhole Inc., which Google later acquired), they later became
 international standards of the OGC, which now encompasses more than 450
 commercial, governmental, nonprofit, and research organizations working
-together on the development and implementation of open standards
-[https://www.ogc.org](https://www.ogc.org).
+together on the development and implementation of open standards ([https://www.ogc.org](https://www.ogc.org)).
 
 ## Neuroscience
 
@@ -121,30 +120,29 @@ wide range of stakeholders and tap a broad base of expertise.
 ## Community science
 
 Another interesting use case for open-source standards is community/citizen
-science. An early example of this approach is OpenStreetMap
-[https://www.openstreetmap.org](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.
+science. An early example of this approach is OpenStreetMap ([https://www.openstreetmap.org](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.
 
 

sections/05-recommendations.qmd

@@ -20,7 +20,7 @@ can rely. For example, it is now clear that governance principles and rules can
 mitigate some of the risks and challenges mentioned in @sec-challenges,
 especially for communities beyond a certain size that need to converge toward a
 new standard or rely on an existing standard. Developers and maintainers should
-review existing governance practices such as [The Open Source Way](https://www.theopensourceway.org/the_open_source_way-guidebook-2.0.html#_project_and_community_governance).
+review existing governance practices such as those provided by The Open Source Way([https://www.theopensourceway.org/](https://www.theopensourceway.org/the_open_source_way-guidebook-2.0.html#_project_and_community_governance)).
 
 
 ### Foster meta-standards development
@@ -44,7 +44,7 @@ its specific technological capabilities should be considered.
 More generally, meta-standards could include formalization for versioning of
 standards and interactions with specific related software. This includes
 amplifying formalization/guidelines on how to create standards (for example,
-metadata schema specifications using LinkML (https://linkml.io)). However,
+metadata schema specifications using LinkML, [https://linkml.io](https://linkml.io)). However,
 aspects of communication with potential user audiences (e.g., researchers in
 particular domains) should be taken into account as well. For example, in the
 quality of onboarding documentation and tools for ingestion or conversion into
@@ -59,9 +59,8 @@ meta-standards and high-level descriptions of the standards-development process
 avoid known pitfalls, such as the dreaded proliferation of standards, or
 complexity-impeded adoption. Surveying and documenting the success and failures
 of current standards for a specific dataset / domain can help disseminate
-knowledge about the standardization process. Resources such as
-[Fairsharing](https://fairsharing.org/) or [Digital Curation Center](https://www.dcc.ac.uk/guidance/standards)
-can help guide this process.
+knowledge about the standardization process. Resources such as Fairsharing (
+[https://fairsharing.org/](https://fairsharing.org/)) or the Digital Curation Center ([https://www.dcc.ac.uk/guidance/standards](https://www.dcc.ac.uk/guidance/standards)) can help guide this process.
 
 ### Develop standards in tandem with standards-associated software