Mapping the “long tail” of research funding: A topic analysis of NSF grant proposals in the division of astronomical sciences

Gretchen R. Stahlman, P. Bryan Heidorn

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

“Long tail” data are considered to be smaller, heterogeneous, researcher-held data, which present unique data management and scholarly communication challenges. These data are presumably concentrated within relatively lower-funded projects due to insufficient resources for curation. To better understand the nature and distribution of long tail data, we examine National Science Foundation (NSF) funding patterns using Latent Dirichlet Allocation (LDA) and bibliographic data. We also introduce the concept of “Topic Investment” to capture differences in topics across funding levels and to illuminate the distribution of funding across topics. This study uses the discipline of astronomy as a case study, overall exploring possible associations between topic, funding level and research output, with implications for research policy and practice. We find that while different topics demonstrate different funding levels and publication patterns, dynamics predicted by the “long tail” theoretical framework presented here can be observed within NSF-funded topics in astronomy.

Original languageEnglish (US)
Article numbere276
JournalProceedings of the Association for Information Science and Technology
Volume57
Issue number1
DOIs
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Library and Information Sciences

Keywords

  • astronomy
  • data curation
  • long tail
  • research funding
  • topic analysis

Fingerprint

Dive into the research topics of 'Mapping the “long tail” of research funding: A topic analysis of NSF grant proposals in the division of astronomical sciences'. Together they form a unique fingerprint.

Cite this