Sound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and in the enduring scholarly record. In other words, data should be considered legitimate, citable products of research. Data citation, like the citation of other evidence and sources, is good research practice and is part of the scholarly ecosystem supporting data reuse.
In support of this assertion, and to encourage good practice, Force11 — a community of scholars, librarians, archivists, publishers and research funders that aims to facilitate the change toward improved knowledge creation and sharing — released a set of guiding principles for data within scholarly literature, another dataset, or any other research object.
Kevin Esterling, Perspective from Political Science (II)
This is the fifth post of a video series in which we ask leading social science academics and experts to discuss research transparency in their discipline. The interview was recorded on December 13, 2013 at the University of California, Berkeley.
“Interdisciplinary initiatives are where most progress happens and where exciting innovations come from”
Maya Petersen, Perspective from Medicine
This is the fourth post of a video series in which we ask leading social science academics and experts to discuss research transparency in their discipline. The interview was recorded on December 13, 2013 at the University of California, Berkeley.
The Experiments in Governance and Politics network (EGAP) is requesting statements of interest for leading edge experimental research projects on political accountability in developing countries. This grant round is specifically designed to foster knowledge cumulation across studies. Successful applicants will engage in closely related projects and adhere to a common set of research standards. The $1.8 million pool will support 4-6 research projects that address a common theme and/or one or more “grouped” applications that link 2-3 individual projects across different research sites. This request for short statements of interest seeks to identify clusters of research projects with comparable interventions and outcome measures which will form the basis of the main call. The deadline for submission of statements is March 17, 2014. More info here.
Registration is now open for the first BITSS summer institute (June 2-5, 2014 – Berkeley, CA). The workshop is designed for students, post-docs, and junior faculty eager to learn more about new transparency tools available and appropriate for their own research in economics, political science, psychology or another related discipline. Course description, list of instructors, and application instructions are available on the ICPSR Summer Program Portal.
Brian Nosek, Perspective from Psychology
This is the third post of a video series in which we ask leading social science academics and experts to discuss research transparency in their discipline. The interview was recorded on December 13, 2013 at the University of California, Berkeley.
Or why Jane Austen might well be the first game theorist.
Science is in crisis, just when we need it most [...] A major root of the crisis is selective use of data. Scientists, eager to make striking new claims, focus only on evidence that supports their preconceptions. Psychologists call this “confirmation bias”: We seek out information that confirms what we already believe. “We each begin probably with a little bias,” as Jane Austen writes in “Persuasion,” “and upon that bias build every circumstance in favor of it.” [...] Austen might say that researchers should emulate Mr. Darcy in “Pride and Prejudice,” who submits, “I will venture to say that my investigations and decisions are not usually influenced by my hopes and fears.” [...] But it would be wrong to say that the ideal scholar is somehow unbiased or dispassionate [...] A researcher cannot separate in advance the productive prejudices that enable understanding from the prejudices that hinder it. We all bring different preconceptions to our inquiries, and these preconceptions can spur as well as blind us.
Understanding science as fundamentally a human process might be necessary to save science itself, concludes Michael Suk-Young Chwe (UCLA) in the NYT.