March 31, 2014
Recently, one of the world’s largest publishers announced it would permit conditional open access to its collection of millions of online scholarly papers. The decision represents important progress in the expanding effort to foster open access to research data and results. However, this more open access to research content is conditioned on acceptance of certain limitations which have raised concerns in the research community.
Major academic publisher, Elsevier, has published more than eleven million scholarly papers which are available online. The company has now agreed to make those papers accessible for software-based searches, provided that parties accessing the material agree to certain contractual commitments with Elsevier in advance.
Researchers now routinely use software which enables them to search for and access information contained in massive collections of data. This automated text-mining process enables them to identify and collect material relevant to their research activities.
Previously, the publishers controlling important collections of research materials, including published scholarly papers, resisted the automated text-mining process. The publishers often used technical means to block the database searches. Researchers requesting permission to conduct the text-mining searches often faced significant delays before receiving responses to their requests from the publishers.
The resistance to providing access was present even when the parties requesting access to the data were subscribers to the online materials of the publishers. Researchers who paid for online access to the publisher’s archives were often, nonetheless, denied access to the collection for the purpose of automated text-mining.
This resistance appears to be largely the result of the inability of publishers to develop strategies for open access they believe are consistent with their traditional revenue-generation model. Until the leading publishers develop commercial strategies more appropriate for the digital environment, they are likely to remain reluctant to facilitate true open data access.
Elsevier’s decision to permit automated text-mining represents an important positive step toward more efficient and effective use of scholarly research data. The key to the ultimate success of the Elsevier effort rests, however, on the specific terms and conditions that the company chooses to impose as conditions for text-mining access.
Open access to scholarly publications and the research data associated with those publications serves the public interest. Open access to that material helps to ensure that the full benefits of investments in scientific research are realized by the maximum number of people in as short a time as possible.
Ideally, Elsevier will apply conditions on open access that are reasonable and are consistent with expansive access to the archived materials. Other publishers should join Elsevier in the effort to find workable open access models for research data. Key research funders such as governments and foundations should continue their current efforts to promote open data access by requiring such access as a condition of research funding support.