In the digital age, data is the raw material on which discoveries are built, and unfettered access to research data, whether in the Life Sciences or the Social Sciences, is crucial to accelerating progress in research. Data plays a central role in our ability to predict and counter natural disasters, understand human biology, and develop advances in computing technology.
Despite its tremendous importance, today, research data remains largely fragmented—isolated across millions of individual computers, blocked by disparate technical, legal and financial restrictions.
The amount of scientific and scholarly data grows exponentially each year, yet we still lack the infrastructure, policies, and practices to harness this vital resource. While some high profile projects—such as the Human Genome Project and the Large Hadron Collider—make their data openly accessible, too often data isn’t shared beyond those who generate it. The Internet was built by researchers to share data, but data sharing isn’t yet the norm in research.
The tremendous gap between what is possible with digital technology and our outdated infrastructure has led to the call for Open Data
Open Data is research data that:
Open Data typically applies to a range of non-textual materials, including datasets, statistics, transcripts, survey results, and the metadata associated with these objects. The data is, in essence, the factual information that is necessary to replicate and verify research results. Open Data policies usually encompass the notion that machine extraction, manipulation, and meta-analysis of data should be permissible.
Open Data has the potential to speed up the research process while simultaneously improving our confidence in those results. The access, use, and curation of this huge and growing body of data is central to the research enterprise.