DataONE:Notebook/ArticleCitationPractices:Manuscript

• Intro
  • state that this has been studied for molecular/medical but not eco/evo
  • term: "original data author"
• Methods
  • Time sample snapshot
    • First 25-50 articles from 2010
    • for Percentage stats, current state of things
  • Random sample
    • blocked by journal and by year
  • Extraction
    • Fields
    • PT/GA not assumed to be on treebase unless explicitly stated (even if the other was)
• Results
• Discussion
  • General
    • Suggested best practices (see knoxville ppt)
    • Internal (journal) supplementary data used more as a dump than for reusable data
      • Specifically, sysbio problems (see Knoxville ppt and 7/13 blog)
    • differences between journals
    • examples of haphazard citations
  • Anecdotes
    • NABS: talk with NEON, Alain, Miller
    • Author frustrated with Treebase: 10.1093/sysbio/syp080
    • Genbank oddities (cited a bazillion different ways in the same paper = need for best practices): http://dx.doi.org.erl.lib.byu.edu/10.1111/j.1365-294X.2009.04411.x 10.1111/j.1365-294X.2009.04411.x

AND http://dx.doi.org.erl.lib.byu.edu/10.1111/j.1365-294X.2009.04433.x	10.1111/j.1365-294X.2009.04433.x

• • Future directions (i.e. didn't have time to explore)
    • Software/model reuse and sharing (R-packages, GUIs for math equations, etc)
    • Method metadata (additional supplementary data about methods, i.e. explicit protocols or analysis steps that help make the data re-usable)
      • also, the reusability of the file format
    • Track the cited or shared datasets
    • Databases (all the rage, but not standardized. at least the metadata and cache could be stored at a repository)
  • Recommendations for future studies
    • only extract methods
    • more in-depth: time series, snapshots of more journals, funding analysis, other factor analysis