Beginning January 2014, Psychological Science gave authors the opportunity to signal open data and materials if they qualified for badges that accompanied published articles. Before badges, less than 3% of Psychological Science articles reported open data. After badges, 23% reported open data, with an accelerating trend; 39% reported open data in the first half of 2015, an increase of more than an order of magnitude from baseline. There was no change over time in the low rates of data sharing among comparison journals. Moreover, reporting openness does not guarantee openness. When badges were earned, reportedly available data were more likely to be actually available, correct, usable, and complete than when badges were not earned. Open materials also increased to a weaker degree, and there was more variability among comparison journals. Badges are simple, effective signals to promote open practices and improve preservation of data and materials by using independent repositories. Openness is a core value of scientific practice. The sharing of research materials and data facilitates critique, extension, and application within the scientific community, yet current norms provide few incentives for researchers to share evidence underlying scientific claims. In January 2014, the journal Psychological Science adopted such an incentive by offering “badges” to acknowledge and signal open practices in publications. In this study, we evaluated the effect that two types of badges—Open Data badges and Open Materials badges—have had on reported data and material sharing, as well as on the actual availability, correctness, usability, and completeness of those data and materials both in Psychological Science and in four comparison journals. We report an increase in reported data sharing of more than an order of magnitude from baseline in Psychological Science, as well as an increase in reported materials sharing, although to a weaker degree. Moreover, we show that reportedly available data and materials were more accessible, correct, usable, and complete when badges were earned. We demonstrate that badges are effective incentives that improve the openness, accessibility, and persistence of data and materials that underlie scientific research.

It is widely believed that research that builds upon previously published findings has reproduced the original work. However, it is rare for researchers to perform or publish direct replications of existing results. The Reproducibility Project: Cancer Biology is an open investigation of reproducibility in preclinical cancer biology research. We have identified 50 high impact cancer biology articles published in the period 2010-2012, and plan to replicate a subset of experimental results from each article. A Registered Report detailing the proposed experimental designs and protocols for each subset of experiments will be peer reviewed and published prior to data collection. The results of these experiments will then be published in a Replication Study. The resulting open methodology and dataset will provide evidence about the reproducibility of high-impact results, and an opportunity to identify predictors of reproducibility.

Replicability is an important feature of scientific research, but aspects of contemporary research culture, such as an emphasis on novelty, can make replicability seem less important than it should be. The Reproducibility Project: Cancer Biology was set up to provide evidence about the replicability of preclinical research in cancer biology by repeating selected experiments from high-impact papers. A total of 50 experiments from 23 papers were repeated, generating data about the replicability of a total of 158 effects. Most of the original effects were positive effects (136), with the rest being null effects (22). A majority of the original effect sizes were reported as numerical values (117), with the rest being reported as representative images (41). We employed seven methods to assess replicability, and some of these methods were not suitable for all the effects in our sample. One method compared effect sizes: for positive effects, the median effect size in the replications was 85% smaller than the median effect size in the original experiments, and 92% of replication effect sizes were smaller than the original. The other methods were binary – the replication was either a success or a failure – and five of these methods could be used to assess both positive and null effects when effect sizes were reported as numerical values. For positive effects, 40% of replications (39/97) succeeded according to three or more of these five methods, and for null effects 80% of replications (12/15) were successful on this basis; combining positive and null effects, the success rate was 46% (51/112). A successful replication does not definitively confirm an original finding or its theoretical interpretation. Equally, a failure to replicate does not disconfirm a finding, but it does suggest that additional investigation is needed to establish its reliability.

Credibility of scientific claims is established with evidence for their replicability using new data. According to common understanding, replication is repeating a study’s procedure and observing whether the prior finding recurs. This definition is intuitive, easy to apply, and incorrect. We propose that replication is a study for which any outcome would be considered diagnostic evidence about a claim from prior research. This definition reduces emphasis on operational characteristics of the study and increases emphasis on the interpretation of possible outcomes. The purpose of replication is to advance theory by confronting existing understanding with new evidence. Ironically, the value of replication may be strongest when existing understanding is weakest. Successful replication provides evidence of generalizability across the conditions that inevitably differ from the original study; Unsuccessful replication indicates that the reliability of the finding may be more constrained than recognized previously. Defining replication as a confrontation of current theoretical expectations clarifies its important, exciting, and generative role in scientific progress.

We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology. The initial aim of the project was to repeat 193 experiments from 53 high-impact papers, using an approach in which the experimental protocols and plans for data analysis had to be peer reviewed and accepted for publication before experimental work could begin. However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments. Third, once experimental work started, 67% of the peer-reviewed protocols required modifications to complete the research and just 41% of those modifications could be implemented. Cumulatively, these three factors limited the number of experiments that could be repeated. This experience draws attention to a basic and fundamental concern about replication – it is hard to assess whether reported findings are credible.

P90 ribosomal S6 kinase (RSK) is an important downstream effector of mitogen-activated protein kinase, but its biological functions are not well understood. We have now identified the first small-molecule, RSK-specific inhibitor, which we isolated from the tropical plant Forsteronia refracta. We have named this novel inhibitor SL0101. SL0101 shows remarkable specificity for RSK. The major determinant of SL0101-binding specificity is the unique ATP-interacting sequence in the amino-terminal kinase domain of RSK. SL0101 inhibits proliferation of the human breast cancer cell line MCF-7, producing a cell cycle block in G1 phase with an efficacy paralleling its ability to inhibit RSK in intact cells. RNA interference of RSK expression confirmed that RSK regulates MCF-7 proliferation. Interestingly, SL0101 does not alter proliferation of a normal human breast cell line MCF-10A, although SL0101 inhibits RSK in these cells. We show that RSK is overexpressed in ∼50% of human breast cancer tissue samples, suggesting that regulation of RSK has been compromised. Thus, we show that RSK has an unexpected role in proliferation of transformed cells and may be a useful new target for chemotherapeutic agents. SL0101 will provide a powerful new tool to dissect the molecular functions of RSK in cancer cells.