Thomas Herndon is definitely getting an A this semester.

Big-data boondoggles and brain-inspired chips are just two of the things we’re really getting wrong

"data on emailed request" means they don't.

We need to know how our data is being used.

Where do research data management services fit into today’s organisational charts for academic libraries? I have had this discussion several times in the past couple of months with librarians…

There has been an awakening that online threats are real and growing worse, and that the prevailing “patch and pray” approach to computer security will not do.

The Eagles have sued a concert footage archivist, accusing the man of violating their copyright after screening unlicensed footage in October.

Private companies want to scoop up your child's data.

A former South Carolina state employee who pleaded guilty to five felony charges after he sent personal information about more than 228,000 Medicaid recipients to

Big-data technology will eventually underpin the healthcare system, though to what extent and what that means to patients are questions needing to be asked.

Ars talks to Yahoo about making photos easier to find, share, and communicate with.

Erik Moore Introduction In 2007, OCLC published the report Shifting Gears: Gearing Up to Get Into the Flow to bring to the forefront a much needed conversation about digitization of archival collec…

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Amid the pressure and enthusiasm for researchers to share data, a rapidly growing number of tools and services have emerged. What do we know about the quality of these data? Why does quality matter? And who should be responsible for data quality? We believe an essential measure of data quality is the ability to engage in informed reuse, which requires that data are independently understandable. In practice, this means that data must undergo quality review, a process whereby data and associated files are assessed and required actions are taken to ensure files are independently understandable for informed reuse. This paper explains what we mean by data quality review, what measures can be applied to it, and how it is practiced in three domain-specific archives. We explore a selection of other data repositories in the research data ecosystem, as well as the roles of researchers, academic libraries, and scholarly journals in regard to their application of data quality measures in practice. We end with thoughts about the need to commit to data quality and who might be able to take on those tasks.