Academics and researchers worldwide continue to produce large numbers of scholarly documents including papers, books, technical reports, etc. and associated data such as tutorials, proposals, lab note books, and course materials. For example PubMed has over 20 million documents, 10 million unique names and 70 million name mentions. Google Scholar has recently been estimated to be a 100 million. Besides these traditional databases, there are also online social reference sites such as CiteULike or BibSonomy. This enables researchers to study scholarly collaboration at a very large scale. For example, researchers who are interested in scholarly collaboration can apply data mining techniques (including text mining, network mining, and social network analysis) within a distributed framework such as Hadoop to discover patterns and structures of collaboration, and potentially develop better tools for searching and recommending academic information. Collaboration among scholars is recognized as a feature in scientific discovery. The ever increasing diversity of disciplines and complexity of research problems, particularly multi-disciplinary research, requires collaboration. Besides the traditional venues of collaboration where scholars typically meet annually at conferences or meetings, the Internet provides a wide range of platforms for scholars to engage with other scholars. These new platforms include academic sites such as Academia.edu, ResearchGate and Mendeley, more interactive social sites such as Twitter and Facebook, and Wiki-style virtual collaboration sites. These services allow scholars to share academic resources, exchange opinions, follow each other’s research, keep up with current research trends, and most importantly, build their professional networks. Researchers, with encouragement from funding agencies, increasingly realize that scholarly achievements should not merely be the final published articles. The dataset used in this study and many other intermediary results are equally important for supporting research. Therefore, a set of rapidly developing research topics, research data management, data curation/stewardship, data sharing policy, etc. are becoming important issues for research communities.