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While data is the cornerstone of scientific research, traditional mechanisms of research assessment overlook these data outputs, instead focusing solely on publications. However, publications are just the tip of the iceberg: in reality, science is based on a complex landscape of research data and activities, which can be published or shared beyond traditional journal articles. Information scientists and software engineers are now working to relate and make accessible all of this data for research networking, research evaluation, resource sharing, and hypothesis discovery. Furthermore, federal funding agencies are increasing their requirements for data sharing and data standardization. Researchers, though, are often largely unaware of data standardization efforts and tools to access shared data.
In order to deal with this onslaught of data, standards, and tools, universities are asking libraries to play an increasing role in information management strategies. This includes training, data housing, and dissemination of information about tool resources. Libraries are at a key intersection between the research community and semantic engineers, and are increasingly hiring specialists with a research background to provide data modeling, curation, and scientific information dissemination services. As a result, libraries have been working closely with the research community to build and integrate semantic tools into the entire research cycle. Librarians can help researchers understand ways to interpret and share their data, and use tools to query the large amounts of existing data.