Typos.

Author: arokem

sections/03-challenges.qmd

@@ -56,17 +56,6 @@ have not yet had significant adoption as tools of day-to-day computational
 practice. At the same time, it provides clarity and robustness for standards
 developers communities that are well-versed in these tools.
 
-## Unclear pathways for standards success
-
-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 in order to inculcate a standard into the
-day-to-day practice of researchers.
 
 ## Cross-domain gaps
 
@@ -141,8 +130,20 @@ 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).
 
-## Sustainability
 
+## Unclear pathways for standards success and sustainability
+
+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.
 
 
 ## The importance of automated validation

sections/05-recommendations.qmd

@@ -28,7 +28,7 @@ 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 the distinct role that *data
-stewards* play in contemporary research. As policy demands for openess become
+stewards* play in contemporary research. As policy demands for openness become
 increasingly high, it is crucial to truly support experts whose role will be to
 develop, maintain, and facilitate the adoption and use of open-source
 standards. This support needs to manifest in all stages of the career of these
@@ -101,7 +101,7 @@ assessment of an existing standard, or as guidelines to develop new standards.
 For instance, barriers to adopting a data standard irrespective of team size
 and technological capabilities should be considered. Meta-standards should
 include formalization for versioning of standards and interactions with
-speficic related software. Aspects of communication with potential user
+specific related software. 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 standards-compliant datasets. Relatedly,