In the broadest sense, my research interests revolve around the documentation of science. To this end, I seek to understand not just the means by which science is documented, but also the purpose for this documentation. In a more narrow sense, consistent with the work of Richard Whitley, I believe that the documentation of science may be manifested differently and for different purposes within different types of institutions and environments. I am specifically interested in its documentation within industry, especially as the publication of research findings appears counter to the goals of such an institution. My current research is thus aimed at understanding both means my which industry documents it scientific activity and the purpose for such documentation.

I have recently explored the epistemological value of scientific documentation and in doing so have reaffirmed my conceptual foundation that science is, at its core, a communal activity that requires the communication of results. In fact, I assert that scientific findings are created through their documentation during the process of communication. It is in the synthesis of scientific results and their placement within the larger body of scientific discourse, necessary for communication, that the scientific finding is created. In turn, science documents have been studied as historical artifact (History of Science), proof of scientific activity (Philosophy of Science), and as organizational structure (Sociology of Science). Within Information Science, the study of science though its documents – known as scientometics - has been largely concerned with, similar the later, the use of scientific documents as a means of identifying the structure of the scientific community or individual domains within it. In doing so, it has internalized Robert Merton's norm of communism and associated recognition to identify both a shared communal body of science and the associated reputational economy (Paula Stephens) necessary for its functioning.

However, Richard Whitley correctly points out that different institutions are more aligned or less aligned with the goals of this public science community. Specifically, while both research universities and industry are producers of scientific discovery and innovation, they have vastly different alignments to public science. The internal rewards structure and governing policies of research universities are consistent with both the creation of a shared public body of science and the individual reputational currency attained through publication of such science. This however, is not as true in industry which, based on a view of knowledge as resource, should reap more benefit from keeping findings secrete or otherwise protected.

Despite this, it is the case that industry does, at times, document its research findings through disclose of those finding by means of publication. My current research is thus focused on this paradox and seeks to identify the purpose of such disclose and whether the means by which the findings are documented is related to their intended purpose. I have recently assessed the influence of top management team education on a firm's participation in public science. While these results were positive, I believe there could also be more strategic purposes for such documentation. My current research in progress seeks to identify different means by which industry publishes research findings. The future direction of this research is to align documentation means with documentation purpose through both a thorough understanding of scientific documentation within industry and the potential strategic benefits to a firm of publishing research findings.

Scholarly Profiling and Network Analysis

The use of scholarly public profiles has been important in faciliting collaboration among scholars not otherwise affiliated and the use of social network analysis to understand these collaboration patterns is a well researched area. My work in this area has involved both team research initiatives under the direction of Dr. Ying Ding, as well as individaul iniatives analysising ontolgoies related to scholarly profiling and collaboration networks within computer science.

Published Work:
  • Chambers, T., Milojević, S., Ding, Y. (2014). Female Semantic Web researchers: Does collaboration with male researchers influence their network status? [poster] In Proceedings of the 2014 ACM conference onWeb science (WebSci'14). ACM, New York, NY, USA, 301-302 doi: 10.1145/2615569.2615659
  • Chambers, T., Shah, S., Uranker, A., Kalyan, V., Scharnhorst, A., Reijhoudt, L., Ridenour, L., Guéret, C., & Ding, Y. (2013). Bilingual researcher profiles: Modeling Dutch researchers in both English and Dutch using the VIVO ontology. [poster] In Proceedings of the American Society for Information Science and Technology 50(1):1-4 doi: 10.1002/meet.14505001137
  • Xu, J., Ding, Y., Song, M. & Chambers, T. (2015). Author credit-assignment schemas: A comparison and analysis. Journal of the American Society for Information Science & Technology doi: 10.1002/asi.23495
  • Song, M., Kim, S., Zhang, G., Ding, Y., & Chambers, T., (2014). Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central. Journal of the American Society for Information Sciences & Technology 65(2):352–371. doi: 10.1002/asi.22970
  • Guéret, C., Chambers, T., Reijnhoudt, L., van der Most, F., & Scharnhorst, A. (2013).Genericity versus expressivity: An exercise in semantic interoperable research information systems for Web Science. arXiv preprint arXiv:1304.5743

Citation Analysis

Citation analysis remains a core feature of bibliometric and research evaluation studies. My work in this area has involved team research initiatives under the direction of Dr. Ying Ding, which seek to better understand the use of citation in scholarly activities. This work has included research on science linkage using patent citation and work with content-based citation analysis to enhance the meaning of traditional citation analysis.

Published Work:
  • Ding, Y., Zhang, G., Chambers, T. Song, M., Wang, X., & Zhai, C., (2014). Content-based citation analysis: The next generation of citation analysis. Journal of the American Society for Information Science & Technology 65(9):1820-1833 doi: 10.1002/asi.23256
  • Li, R., Chambers, T., Ding, Y., Zhang, G., & Meng, L., (2014) Patent citation anyalysis: Caculating science linkage base on citing motivation. Journal of the American Society for Information Science & Technology 65(5):1007-1017 doi: 10.1002/asi.230540

Content/Knowledge Analysis with Text Mining

Beginning with the belief that there is embedded knowledge in scholarly publications, work in this area focuses on extracting and liking this embedded knowledge to create a new understanding or discovery. My work in this area has involved team research initiatives under the direction of Dr. Ying Ding, that developed and utilized an entitymetric tool to measure individual entity impact, as well as, topic modeling and general text mining.

Published Work:
  • Ding, Y., Song, M., Jai, H., Yu, Q., Yan, E., Lin, L., & Chambers,T., (2013). Entitymetrics: Measuring the impact of knowledge units. PLOS ONE 8 (8):e71416. doi:10.1371/ journal.pone.0071416
  • Song, M., Han, N., Kim, Y., Ding, Y., & Chambers, T. (2013). Discovering implicit entiy relation with the Gene-Citation-Gene network. PLOS ONE 8 (12):e84639. doi: 10.1371/journal.pone.0084639
  • Li, D., Tang, J., Ding, Y., Shuai, X., Chambers, T., Sun, G., Luo, Z., & Zhang, J. (2015). Topic-level opinion influence model (TOIM): An investigation using tencent microblogging. Journal of the American Society for Information Science & Technology doi: 10.1002/asi.23350
  • Song, M. & Chambers, T. (2014). Text Mining with the Stanford CoreNLP. In Y. Ding, R. Rousseau,& D. Wolfram (Eds.) Measuring Scholarly Impact: Methods and Practice (pp.215-234). Heidelberg: Springer. doi: 10.1007/978-3-319-10377-8