Brody, Tim, Carr, Les, Gingras, Yves, Hajjem, Chawki, Harnad, Stevan and Swan, Alma,
Dirks, Lee and Hey, Tony (eds.)
Incentivizing the Open Access Research Web: Publication-Archiving, Data-Archiving and Scientometrics.
CTWatch Quarterly, 3, (3)
The research production cycle has three components: the conduct of the research itself (R), the data (D), and the peer-reviewed publication (P) of the findings. Open Access (OA) means free online access to the publications (P-OA), but OA can also be extended to the data (D-OA). The two hurdles for D-OA are that not all researchers want to make their data OA and that the online infrastructure for D-OA still needs additional functionality. In contrast, all researchers, without exception, do want to make their publications P-OA, and the online infrastructure for publication-archiving (a worldwide interoperable network of OAI-compliant Institutional Repositories [IRs]) already has all the requisite functionality for this. Yet because so far only about 15% of researchers are spontaneously self-archiving their publications today, their funders and institutions are beginning to mandate OA self-archiving in order to maximize the usage and impact of their research output. The adoption of these P-OA self-archiving mandates needs to be accelerated. Researchers’ careers and funding already depend on the impact (usage and citation) of their research. It has now been repeatedly demonstrated that making publications OA by self-archiving them in an OA IR dramatically enhances their research impact. Research metrics (e.g., download and citation counts) are increasingly being used to estimate and reward research impact, notably in the UK Research Assessment Exercise (RAE). But those metrics first need to be tested against human panel-based rankings in order to validate their predictive power. Publications, their metadata, and their metrics are the database for the new science of Scientometrics. The UK’s RAE, based on the research output of all disciplines from an entire nation, provides a unique opportunity for validating research metrics. In validating RAE metrics (through multiple regression analysis) against panel rankings, the publication (P) archive will be used as a data (D) archive. Hence the RAE provides an important test case both for publication metrics and for data-archiving. It will not only provide incentives for the P-OA self-archiving of publications, but it will also help to increase both the functionality and the motivation for D-OA data-archiving.
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