Do open access data files represent an academic Risk?

Dear Sir, We wish to present our concerns about possible data theft that could result from the existence of freely available open access (OA) data sets. Such data sets may be increasingly found as supplementary files in a wide range of publishers’ journals, particularly those that focus on print format. Usually such traditional print journals have limited space, and thus authors, especially of large studies with large data sets, are usually encouraged to slough tangential and marginal results, or supporting data, into supplementary files, in a bid to save space, and thus publishing or printing costs. Such files tend to be found in Word, Excel, PDF, or other commonly available formats. Such formats can be easily manipulated, if in the wrong hands, using the same software, or even with slightly more sophisticated, but easily accessible, software. Competition for limited resources (salaries, research funding, positions, and grants) is increasing. Those who are vying for these resources are under constant pressure to either obtain new resources, or sustain current ones. When under pressure, there is a segment of the scientific populace who may revert to dishonest practices to get ahead of the pack, that is, to gain data from freely available sources. One of the easiest ways could be through data theft using OA files available freely on publishers’ websites. This letter serves as a heads-up to what may be a possible new source of risk to research integrity if the issue is not debated, and if precautionary measures are not taken to protect data and to avoid theft. A very recent case of blatant figure theft highlights this risk, even if the original stolen figure was not present in an OA supplementary file. In this case, an article by Sahoo et al. (2014) was retracted because one figure had been used that was in fact not that of the authors, but had been lifted from an article by another set of authors (Zhang, Large, Nordlander, & Wang, 2014). Although the retraction notice does not indicate precisely how the figure was obtained, one realistic possibility is the use of software to extract figures from PDF files, to save them in new formats, and to then reuse figures in “original research papers. ” Theft may be more difficult when a PDF file contains encryption or a password (Oaten, 2014). Theft from a supplementary OA file would “mask” the theft somewhat more than from the main file because the data in supplementary files are less conspicuous. Readers of this letter may ask: Why would any scientist risk being caught? Would the benefits trump the risks? While it is difficult to provide an answer to these questions, there are two reasons which could provide some explanation. The first relates to an increasingly large pool of so-called “predatory” OA journals (www.scholarlyoa.com), some of which may exercise more lax quality control, but many of which are being used to recognize the productivity of scientists. Such risks were recently highlighted by Tuffani (2015) within a Brazilian context. Thus, unsuspecting editors would not be able to differentiate a valid figure from a stolen one. Moreover, most academic scholars are likely to reference studies from higher impacted peer-reviewed journals, relying less on weaker academic journals, and thus the chances of misconduct being detected are rapidly decreasing as the volume of articles that flood the Internet increases. Presently, it is only by chance and through the observations of astute readers, that such cases are discovered. Current commercial plagiarism or text similarity software is unable to detect similarity in figures, nor can it detect whether any data were siphoned off any OA supplementary file, and remodeled in a new format. Currently, only astute editors or peers are likely to detect such cases, again, by chance. The misappropriation of text and data is already a widely discussed topic in the literature pertaining to plagiarism and scientific misconduct. But the issue of OA data sets, and OA supplementary files, is, surprisingly, not being discussed, and, as far as can be assessed, has very limited representation in the mainstream literature, although one recent article has, in fact, addressed the issue of using encrypted data trees to limit data theft (Blasco, Tapiador, Peris-Lopez, & Suarez-Tangil, 2015). For this reason, it is our expectation that this letter will not only spark wider debate, but also stimulate greater precautionary measures by publishers and authors to protect their data sets that are online in OA format. If the choice of providing supplementary files originates from the authors, then should the authors be responsible for security, or does that responsibility become that of the publisher if supplementary files are an official editorial request? A preemptive solution should not be found after a problem arises, but before one is born. © 2015 ASIS&T