Promoting an open research culture

Abstract

Author guidelines for journals could help to promote transparency, openness, and reproducibility

Effects of tDCS on motor learning and memory formation: A consensus and critical position paper

“…Present problems in the field include: (1) insufficient use of double-blind designs (see above, for example only 25 out of the 60 published studies on tDCS effects on motor learning in healthy adults reviewed here utilized double-blind designs) and positive controls (stimulation of other cortical regions); (2) insufficient differentiation and understanding of design and claims when carrying out exploratory (hypothesis-generating) versus confirmatory (hypothesis-driven) research (the former suggesting trends and providing data for prospective power analysis and the latter, strengthened by preregistration (Finkel, Eastwick, & Reis, 2015), allowing drawing conclusions on particular effects; (3) insufficient efforts to reduce false-positive rates in studies geared to provide proof of principle data to power subsequent clinical trials; (4) scarcity of preregistration of hypothesis, design, power analysis and data processing for research written up as hypothesis-driven and confirmatory (see for example https://blogs.royalsociety.org/publishing/registered-reports/); (5) insufficient prepublication and sharing of materials (Lauer, Krumholz, & Topol, 2015;Morey et al, 2016), particularly in relation to negative results; (6) insufficient post-publication repositories of data (see for example (Campbell et al, 2002)) and in general (Nosek et al, 2015)) to allow additional analyses; (7) seldom use of experimental designs with replications built in (Anderson et al, 2016;Cohen et al, 1997;Gilbert, King, Pettigrew, & Wilson, 2016;Nosek et al, 2015); and (8) use of appropriate sample size based on prospective power analysis for studies claimed to be hypothesis-driven.…”

Our path to better science in less time using open data science tools

“…Many researchers do not attempt to reproduce their own work 17,72 -ourselves included before 2013-and thus may not realize that there could be reproduc ibility issues in their own approaches. But they can likely identify inefficiencies.…”

“…Our story is only one potential path because there are many ways to upgrade scientific practiceswhether collaborating only with your 'future self ' or as a team-and they depend on the shared commitment of individuals, institutions and publishers 6,16,17 . We do not review the important, ongoing work regarding data management architecture and archiving 8,18 , work flows 11,[19][20][21] , sharing and publishing data [22][23][24][25] and code [25][26][27] , or how to tackle reproducibility and openness in science [28][29][30][31][32] .…”

Research integrity: Don't let transparency damage science

“…In the wake of evidence that many research findings are not reproducible 1 , the scientific community has launched initiatives to increase data sharing, transparency and open critique. As with any new development, there are unintended consequences.…”