Mozilla Science Lab Week in Review, April 27 – May 3

The Week in Review is our weekly roundup of what’s new in open science from the past week. If you have news or announcements you’d like passed on to the community, be sure to share on Twitter with @mozillascience and @billdoesphysics, or join our mailing list and get in touch there.

Awards & Grants

  • Applications for the PLOS Early Career Travel Award Program are now open; ten $500 awards are available to help early career researchers publishing in PLOS attend meetings and conferences to present their work.

Tools & Resources

Blogs & Papers

  • A study led by the Center for Open Science that attempted to replicate the findings of 100 journal articles in psychology has concluded, with data posted online; 39 of the articles investigated were reproduced, with substantial similarities found in several dozen more.
  • The Joint Research Centre of the European Commission has released an interim report on their ongoing work in ‘Analysis of emerging reputation mechanisms for scholars’; the report maps an ontology of research-related activities onto the reputation-building activities that attempt to capture them, and reviews the social networks that attempt to facilitate this construction of reputation on the web.
  • Alyssa Goodman et al published Ten Simple Rules for the Care and Feeding of Scientific Data in PLOS Computational Biology. In it, the authors touch not only on raw data, but the importance of permanent identifiers by which to identify it, and the context provided by publishing workflows in addition to code.
  • David Takeuchi wrote about his concerns that the American federal government’s proposed FIRST act will curtail funding for the social sciences, and place too much emphasis on perceived relevance at the expense of reproducibility.
  • The Georgia Tech Computational Linguistics Lab blogged about the results of a recent graduate seminar where students were set to reproducing the results of several papers in computational social science. The author makes several observations on the challenges faced, including the difficulties in reproducing results based on social network or other proprietary information, and on the surprising robustness of machine-learning driven analyses.
  • Cobi Smith examined both the current state and future importance of open government data in Australia.

Meetings & Conferences