Newly released: Data Curation Primer on Data Accessibility

See the Primer here.

Although accessibility is a commonly-used word in the context of data management and sharing, it has most often been used in the more general sense of data that is findable and widely available. This includes considerations around indexing, clear context (and language), well-defined and standardized access paths, using open file formats, and paywalls/affordability. However, accessibility that explicitly takes into account the needs of a range of potential users including those with disabilities or neurodivergence is most often not included in this approach, and this shortfall is long overdue to be addressed. (Additionally, of course, accessibility benefits everyone who encounters the data regardless of their abilities–accessible data is more navigable and understandable for everyone!)

For the purposes of this work, truly accessible data means data compatible with assistive technologies, and featuring the considered use of design features such as color contrast, font size and legibility, and alternatives to visual presentations of information such that users with physical/sensory disabilities or who are neurodivergent have equivalent access to the information represented by the data.

Over the course of a summer internship, then-UMSI student Emily Oxford ('21) researched and drafted content providing guidance for curators (and researchers) on what it means to explicitly consider the accessibility of data as part of the curation and publication process. The project output is part of a growing library of resources, "Data Curation Primers," whose creation is supported by the Data Curation Network (DCN). (Data curation primers, in brief, are "peer-reviewed, living documents that detail a specific subject, disciplinary area or curation task and that can be used as a reference to curate research data.")

The final deliverable of the internship was the addition of a section to the R Primer, and a draft of content for a primer more broadly focused on Data Accessibility in general. Much of the content was pulled or adapted from guidelines created to govern web content, or guide the creation of accessibility-sensitive files using various types of software (Adobe, Microsoft Office, etc.) After Emily's graduation, Data Curation Specialist Rachel Woodbrook took over the completion of the primer, which went through the DCN's peer review process.

The primer is introductory and not comprehensive, but it is the culmination of significant work researching and collating resources on the intersection of data management and accessibility in one place; and synthesizing and mapping principles from one area to various different types of data where they are applicable.

The primer is primarily organized by type of data or content (e.g., text, images, time-based, etc.), with a section on metadata addressing accessibility as well. Appendix A contains a list of areas for further investigation and study--as multiple content types can be included in a single dataset or file (think of a database, or a PDF with both text and images), there are many horizons yet to be fully explored!

The biggest challenges to the effective curation of data for accessibility are limitations on time and expertise; many curators and researchers already feel over capacity. How many datasets do we see (or produce) that actually follow all best practices? But the reality is that change happens over time, every journey is made up of single steps, and we always start from where we are. As data professionals who educate researchers and advocate for best practices, we are particularly well-placed to help others realize where things need to change. Accessibility is not all-or-nothing, and any change for the better helps us move toward building new default practices. As guides to and stewards of data, curators can encourage researchers to build accessibility into data planning, collection, analysis, and archiving.

 


(1) Johnston, L. R., Carlson, J., Hudson-Vitale, C., Imker, H., Kozlowski, W., Olendorf, R., & Stewart, C. (2018). How Important is Data Curation? Gaps and Opportunities for Academic Libraries. Journal of Librarianship and Scholarly Communication, 6(1). https://doi.org/10.7710/2162-3309.2198)