Do you want credit for making your data available and reusable?
If so, Scientific Data can help. It’s a new type of open access journal publishing a new type of content, the Data Descriptor, designed to provide detailed descriptions of datasets: focusing on how these have been produced, by whom, and how they could be reused. We aim to make your data more discoverable, interpretable and reusable. We are calling for submissions now and launching in May next year.
Why publish with Scientific Data?
You probably already have all the information you need about your own research data to draft and submit a Data Descriptor. By investing a little more work to pull it all together you get so much more, including:
Credit – Data Descriptors are peer-reviewed and citable. Their easily accessible format and high discoverability will get you citations and the credit you deserve. Increase you lab’s publishing output, using data you may already have.
Interpretability – Researchers want to know quickly and accurately what datasets are most useful to them and a Data Descriptor does this perfectly. Increase the chance of your data being reused – and get the credit!
Discoverability – Data Descriptors include both narrative and structured, curated information. Indexing in all major indexing services and ISA-Tab structured metadata gives you a level of visibility that is unsurpassed.
Advance science – Data Descriptors help open up more original datasets to more of the community. By providing credit and visibility we hope more researchers will deposit more data. More open data with detailed descriptions means increased reuse, which is good for science (and good for you).
Complementing traditional research papers
Scientific Data adds a level of description to data that traditional papers just cannot do. Data Descriptors encompass information on the genesis of datasets, detailing the experiment steps and linking to the resulting dataset. They don’t replace traditional papers, but complement them to increase focus on data and, ultimately, help to advance the scientific process. In addition, Data Descriptors are not expected to contain new scientific conclusions or interpretation, which means you can publish valuable data even in the absence of specific new findings or when the data might be considered confirmatory.
Do you know where your data is?
The increasing amount of data labs produce means it is more important than ever to have a data management plan. Do you know where your data is stored? In this era of Big Data, can you afford not to publish in Scientific Data?