It’s all very well saying that information is available to everyone, or that government processes are designed to be transparent. But how many people can access the scientific and long-winded sentences in these documents? Even the abstract below on this very topic needs interpretation into everyday words. It’s easy to talk about universal design. However, academics often make research on accessibility and inclusion inaccessible and exclusive. How about more walking the walk, and talking the talk? We need universal design for data access.
The article on Open Government Data Through the Lens of Universal Design is about accessing data sets. This might include population census data, or data that underpin policy decisions. By casting the lens of the seven principles of universal design over the data sets the authors found ways to improve accessibility. Nine issues were found, three related to the web and the rest to data presentation.
This is an important aspect of inclusion. It helps people with disability and others to see how data are used, and to give them a voice. Information is power. The article includes recommendations for discussion on how to improve the situation.
The article can be downloaded from ResearchGate where you can request the full text from the authors. Otherwise it is available on SpringerLink where you will need institutional access for a free read. Note the dated use of the term “special needs”.
Open Data are increasingly being used for innovation, developing government strategies, and enhancing the transparency of the public sector. This data is aimed to be available to all people regardless of their abilities, professions and knowledge.
Research is showing, however, that open data, besides being physically inaccessible to people with special needs, those are also semantically inaccessible to people who lack data science expertise.
In order to identify specific accessibility challenges associated with open government data portals and datasets, we conducted an analysis using seven principles of Universal Design.
In total, nine challenges are identified based on issues discovered. Three challenges are identified on the web portal interface level, namely: dataset filtering and categorization, access using a keyboard, and breadcrumb and back navigation.
The other six challenges are identified on dataset level: dataset previewing, dataset size, dataset formats, dataset purpose, dataset labelling, and dataset literacy. For each challenge, we propose recommendations as a means to incite a discussion about the features that open data should possess in order to be widely accessible, including people with disabilities and those lacking data science expertise and knowledge.