Guest Editorial: Big Scholar Data Discovery and Collaboration.

The papers in this special section focus on scholarly data collection and knowledge discovery. 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, and course materials. The ever-increasing diversity of disciplines and complexity of real-word problems, require researchers to seek new inspiration and collaboration outside of their own fields. Nowadays, besides traditional venues of collaboration such as conference meetings, the Internet provides a wide range of platforms for scholars to engage with other scholars. These new platforms (such as Google Scholar, ResearchGate, and Wi-ki-style virtual collaboration sites) enrich and document the ways scholars share academic resources, exchange opinions, follow each other’s research, keep up with current research trends, and build their professional networks. The first part of this special issue includes two articles that exemplify research opportunities and challenges in scholarly big data. Their contributions cover three themes: scalable algorithms for extracting scholarly-specific information content, fine-grained tools for analyzing and anticipating scientific impact, and system design for supporting scholarly specific information query.