Aggregating productivity indices for ranking researchers across multiple areas

The impact of scientific research has traditionally been quan-tified using productivity indices such as the well-known h-index. On the other hand, different research fields—in fact, even different research areas within a single field—may have very different publishing patterns, which may not be well described by a single, global index. In this paper, we argue that productivity indices should account for the singulari-ties of the publication patterns of different research areas, in order to produce an unbiased assessment of the impact of scientific research. Inspired by ranking aggregation ap-proaches in distributed information retrieval, we propose a novel approach for ranking researchers across multiple re-search areas. Our approach is generic and produces cross-area versions of any global productivity index, such as the volume of publications, citation count and even the h-index. Our thorough evaluation considering multiple areas within the broad field of Computer Science shows that our cross-area indices outperform their global counterparts when as-sessed against the official ranking produced by CNPq, the Brazilian National Research Council for Scientific and Tech-nological Development. As a result, this paper contributes a valuable mechanism to support the decisions of funding bodies and research agencies, for example, in any research assessment effort