Ten Simple Rules for the Care and Feeding of Scientific Data

Our path to better science in less time using open data science tools

“…Our story is only one potential path because there are many ways to upgrade scientific practiceswhether collaborating only with your 'future self ' or as a team-and they depend on the shared commitment of individuals, institutions and publishers 6,16,17 . We do not review the important, ongoing work regarding data management architecture and archiving 8,18 , work flows 11,[19][20][21] , sharing and publishing data [22][23][24][25] and code [25][26][27] , or how to tackle reproducibility and openness in science [28][29][30][31][32] . Instead, we focus on our experience, because it required changing the way we had always worked, which was extraordinarily intimidating.…”

Exploring openness in data and science: What is “open,” to whom, when, and why?

“…A primary challenge to data sharing and integration is decisions made locally about curation and documentation. According to Goodman, et al (2014), the ability to produce reusable research data is increased if individuals conduct their research with a "data reuse" perspective in mind. Studies of local data sharing practices tend not to use terms such as "open data" when referring to data made legally and technically available.…”

Versioned data: why it is needed and how it can be achieved (easily and cheaply)

“…Moreover, increasing numbers of standalone "Data papers" (or descriptors) have been appearing in standard domain-level journals, as well as specialised data journals. Yet, while the last decade has witnessed a rapid and exciting change in attitudes towards data sharing and publishing, the scientific community is still grappling with how to effectively disseminate and manage open-source datasets 2,5,[7][8][9][10] . In particular, the current model for publishing data has not yet embraced the idea that many datasets are designed to answer scientific questions that extend beyond the scope of a single empirical paper.…”