Auditing biochemical research data: A case study

There is little documentation in the literature of how to conduct a data audit of laboratory research. The purpose of such an audit is to verify the extent to which the published data agree with the corresponding laboratory notebook data and whether the data thus examined appear to be sufficient to justify the published conclusions. A case study is presented, which demonstrates a step by step approach towards conducting a data audit of a published research study.     

A call for the development of “good research practices” (GRP) guidelines

It is proposed that the scientific community develop and implement “Good Research Practices”; (GRP) guidelines in order to improve the quality of research, reduce the incidence of scientific misconduct, and save large sums of monies from being wasted.     

Accountability in research using persons with mental illness

Although medical research involving the use of persons with mental illness is critically important, in order for the research to be ethical and legal there are certain considerations and restrictions which should be immediately readdressed in order to insure that the welfare of these vulnerable research subjects is protected, and their best interests are assured. A brief historical examination of medical research codes, guidelines, recommendations and Federal Regulations reveals the various considerations and restrictions on informed consent and accountability applicable to the use of persons with mental illness in medical research. Several concerns are raised about how these considerations and restrictions have been interpreted, and specific recommendations are offered to improve them immediately by means of representation from consumers and/or their families, and organizations, e.g., NAMI members.     

Which ethics for science and public policy?

The problem of inaccurate, misapplied or fraudulent scientific data could be addressed by government regulations, or by self‐regulation from within science itself. To many, self‐regulation implies the grounding of research activities in some “neutral”; standard of “ethics”; acceptable in a “pluralistic”; society. Yet, there is no such thing as a “neutral ethics”; and many “contemporary”; theories contain such serious theoretical deficiencies and contradictions that they are practically inapplicable. As a viable alternative to these theoretical and practical problems, an objectively based realistic framework of ethics is considered, and used to ground both the individual scientific and the collective public policy decision making processes. This is an ethics of properly integrated relationships. It is then applied to an analysis of many of the causes of incorrect scientific data, as well as of many of the internal and external pressures and abuses often experienced by scientists today. This approach respects the integrity of each decision maker as a human being and a moral agent—which in turn better insures the integrity of the protocol, the data, and the public policy decisions which follow—and ultimately, the integrity of the scientific enterprise itself. The alternative is government regulations.     

Data Audit as a Way to Prevent/Contain Misconduct

Research misconduct is frequently in the media headlines. There is consensus among leading experts on research integrity that the prevalence of misconduct in research is at least 1%, and shoddy work may even go over 5%. Unfortunately, misconduct in research impacts all walks of life from drugs to human subject protections, innovations, economy, policy, and even our national security. The main method of detecting research misconduct depends primarily on whistleblowers. The current regulations are insufficient since dependence on whistleblowers manifests itself as an accidental hit or miss. No other endeavor in our society depends on such a poor system of discovery of misconduct to remedy it. Nearly a quarter of a century ago, I proposed data audit as a means to prevent/contain research misconduct. The audit has to protect the creative process and be non-obtrusive. Data audit evaluates the degree of correspondence of published data with the source data. The proposed data audit does not require any changes in the way researchers carry out their work.     

Rethinking Authorship in the Era of Collaborative Research

The size and complexity of research teams continues to grow, especially within the realms of science and engineering. This has intensified already existing concerns about relying on traditional authorship schemes as the way to allocate credit for a contribution to a research project. In this paper, we examine current authorship problems plaguing research communities and provide suggestions for how those problems could potentially be mitigated. We recommend that research communities, especially those involved in large scale collaborations, revisit the contributor model and embrace it as means for allocating credit more authentically and transparently.