Publishers, too, are marching toward transparency. Scientific
journals across fields are increasingly moving toward open-access models, including the newest APA journal, the Archives of
Scientific Psychology, which launched in 2013.
Yet transparency isn’t a new idea. APA Publisher Gary
VandenBos, PhD, says he’s been involved in initiatives to
expand data sharing since 1990, following a discussion at an
NIH conference. At the time, he says, practical and technical
challenges made sharing data difficult. “Improvements in
computer technology over the last seven or eight years have
made it much easier to be able to clean, anonymize and share
data,” he says.
Recently, VandenBos participated in a collaborative effort
among a group of publishers, academic leaders and funding
agency representatives, organized by the Center for Open
Science in Charlottesville, Virginia, to develop a document
known as the Transparency and Openness Promotion (TOP)
guidelines. Published in Science in June, the guidelines were
designed to help scientific journals across all disciplines
promote transparency, openness and reproducibility.
Already, more than 500 journals are signatories of the
guidelines, says Brian Nosek, PhD, a psychologist at the University
of Virginia and co-founder of the Center for Open Science. While
APA has not yet decided whether to officially become a signatory
of the guidelines, VandenBos says, the association’s Publications
and Communications Board is using the TOP guidelines as a tool
in ongoing discussions of transparency.
“The transparency movement is moving fast,” Nosek says.
“This isn’t just within a particular discipline, or a particular
nation. The momentum is upon us.”
Despite that momentum, there are challenges in putting data on
public display — or even in making them available to a limited
group of scientists.
One of the first problems will be to adequately define “data,”
says John Capitanio, PhD, a psychologist at the University of
California, Davis, and another member of APA’s Data Sharing
Working Group. If you score behaviors from a videotaped
subject, for example, are the numbers the data? Or is it the video
itself? “There are logistical issues, stemming from fundamental
questions about what, exactly, are the data,” he says.
Then there’s the issue of data that are sensitive in nature.
“When we talk about data sharing, we tend to use models
that are fairly unproblematic,” Ross says. Genetic sequences or
coordinates of distant planets are relatively straightforward. But
“social science data, and in particular psychology data, can have
repercussions on individuals and on subject groups,” he says.
Ross knows about delicate data firsthand. He studies men
who have sex with men in Africa. “These data can be used by
governments and organizations to argue against human rights,”
he says. In one African country, Ross says, a government official
recently tried to access his data to help make the case for a bill
that would legalize the death penalty for gay men in certain
circumstances. “We have to realize that access to these data
might actually be quite dangerous for the communities who
have given us their trust,” he says.
And it’s not just a problem in foreign countries. In the
United States, a number of Native American communities
explicitly say they retain ownership of research data because
of historic misuses of such data, Ross says. “It’s not as if the
question of ownership of data is a simple one.”
But even studies that seem fairly benign on the surface can
pose ethical problems for data sharing, Jennings says. Sometimes
just a few data points are enough to unravel anonymity. A study
of underage drinking among college athletes, for instance, might
note a student’s race, age and sport. In a small college, that could
be all it takes to pinpoint which student was engaged in the
illegal activity. “Demographic information might make it easy to
identify some subjects,” she says.
There’s also the issue of informed consent. Participants in
research studies have signed consent forms describing how
the data will be used. But if those data are shared, they may be
used for any number of secondary analyses in years to come —
analyses to which the subjects have not consented. The scientific
community, together with the public, will need to reconsider
and redefine the concept of “informed consent,” says Panicker.
Data sharing also presents practical problems. Will journal
article methods sections need to become more detailed
and explicit? Will authors need to learn new procedures for
annotating data so that anyone can understand them? How will
the data be delivered to journals, or entered into repositories?
“The learning curve could be fairly steep,” Capitanio says.
Nosek believes that integrating data sharing into a
researcher’s daily workflow will be one of the biggest challenges
to overcome before data sharing is widespread. “When you
get down to the brass tacks, a lot of these initiatives require
researchers to do something new,” he says. Hoping to make
that process less painful, he and his colleagues at the Center for
• Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D.,
Bowman, S.D., Breckler, S.J., Yarkoni, T. (2015). Promoting
an open research culture: Author guidelines for journals
could help to promote transparency, openness, and
reproducibility. Science, 348(6242), 1422–1425.
• APA Data Sharing Working Group. (2015, June).
Data sharing: Principles and considerations for policy
development. Retrieved from www.apa.org/science/
• Psychological Science Agenda. (2013, March). White
House issues public access policy for publications and data.
Retrieved from www.apa.org/science/about/psa/2013/03/