In his most recent Huffington Post Science blog, Olivier Dumon, Elsevier's Managing Director of Research Applications and Platform, conveys the importance of data analytics in the world of big data. Big data is one thing, but it’s the gathering and analysis that lead to transformative discoveries.
In academic and corporate settings, data is being collected and offered for review. Olivier points to the importance of transparency when presenting data and analysis so all can understand the steps taken to arrive at the findings. Only this way will others trust the information.
To harness data’s power for the public good and in ways that create greater credibility and trust, those who analyze, share and sell data need to avoid the ‘black box’ approach. Presenting data and your analysis in a way that is transparent, and which allows the end-user to calculate the results themselves, is critical to building trust. In a world where data becomes ever more important, users will want to understand what’s behind it. In the increasingly data-driven economy and research climate, the black box model will become untenable.
Citing various examples, Olivier goes on to discuss the transparency found in CiteScore metrics in Scopus, the world’s largest abstract and citation database of peer-reviewed literature; this new “basket of metrics” can help researchers make better decisions on where to publish, which journals to subscribe to and when to adjust a journal’s editorial strategy. Adding to the open, cumulative approach, Dumon points to altmetrics pioneer Plum Analytics giving researchers a quicker and more comprehensive picture of how their work is being used and communicated.
Data analytics are already part of our lives; Olivier points out that they have the power to accelerate research and help solve today’s most onerous problems.