Today, we are pleased to announce our first Advisory Panel and Editorial Board members from the social sciences. Researchers from these communities are now invited to submit Data Descriptor manuscripts describing quantitative datasets, particularly those that may be of use for integrative analyses that stretch across the traditional boundaries between the natural and social sciences. Read more
Tony Hey’s job at Microsoft is to connect external scientific researchers with researchers at Microsoft to solve big data scientific problems that people care about. He observes that some scientific areas are more open to this than others, depending on the commercial value attached to the data. He believes that funding agencies and libraries need to assist researchers by providing tools and infrastructure that support open science.
Isaac Kohane combines large clinical and genomic datasets to help unravel the genetics of diseases like depression, autism, arthritis and diabetes. He describes how data sharing can enable researchers to make better diagnoses of patients with life-threatening conditions.
“Data are a bit closer to people’s hearts” says Gavin Simpson, who believes that open data sharing is not yet part of the culture in ecology. He sees a role for data repositories that better support collaboration, so that scientists can see that sharing their data is contributing to the “greater good.”
Stephen Friend, Co-Founder of Sage Bionetworks, proposes three steps to change the attitudes of ‘ownership’ amongst scientists when it comes to data, and makes suggestions for the responsibility of funders in that process.
The first person representing a research funder in the ‘Data Matters’ series tells us that data sharing practices in biomedical research are a ‘hodgepodge’. He believes funders, scientists and publishers must work together to shift the scientific incentive from the traditional concept-centric paper to a data-centric publication.
Maryann Martone tells us about her view of data sharing within the neurosciences. She says that some scientists are “just dead set against it … and there’s another group that just does this as a matter of practice.” She highlights the importance of making data discoverable, and thinks publishers will have to help researchers to store and manage the data as a primary scientific product.
Professor Heck is used to data sharing and data repositories, as proteomics makes use of large data sets which are impossible for any one person to interpret. He asks how we can implement traceability to see how people actually use the data. Read more
As Director of the Swiss-Prot Group, Professor Xenarios is part of a team which curates and safeguards data. He says: “There is a tendency to think that when data is generated it is the end of the story.” He believes that ensuring the data doesn’t languish unused in a repository is vital, and argues that reproducibility of research is actually much more important than the quality of data. Read more
Hailing from the historically more ‘open’ field of genomics, Professor Graveley is used to data sharing and data reuse. But he argues quality is an issue, and quality control is critical to the future of open science. Read more