John Jost’s Open Peer Review

After a desk-rejection for JPSP, my co-author and I submitted our ms. to PSPB (see blog After several months, we received the expected rejection. But it was not all in vane. We received a signed review by John Jost and for the sake of open science, I am pleased to share it with everybody. My comments are highlighted in bold.

Warning. The content may be graphic and is not suitable for all audiences.

Back in July 2021, the authors sent me a draft of the present paper. I am glad that they did so, because it gave us an opportunity to exchange our opinions and interpretations and to try to correct any misunderstanding or misinterpretations. Unfortunately, however, I see that in the present submission many of those misinterpretations (including false and misleading statements) remain. Thus, I am forced to conclude, reluctantly, that we are not dealing with misunderstandings here but with strategic misrepresentations that seem willful. To be honest, this saddens me, because I thought we could make progress through mutual dialogue. But I don’t see how it serves the goals of science to engage in hyperbole and dismissiveness and to misrepresent so egregiously the views of professional colleagues.

For all of these reasons, and those enumerated below, I am afraid that I cannot support publication of this paper in PSPB.
John Jost

(1) On p. 3 the authors write: “IAT scores close to zero for African Americans have been interpreted as evidence that “sizable proportions of members of disadvantaged groups – often 40% to 50% or even more exhibit implicit (or indirect) biases against their own group and in favor of more advantaged groups” (Jost, 2019, p. 277). This is not true. We did not “interpret” the mean-level scores in terms of frequency distributions (or vice versa). We looked at both. So these are two separate observations; one observation was not used to explain the other. For African Americans the mean-level scores were close to zero (no preference) and, using a procedure described in the note to Figure 1 for Jost et al. (2004 p. 898), we concluded that 39.3% exhibited a pro-White/anti-Black bias. (The 40-50% figure comes from
other intergroup comparisons included in the original article).

It is not important how you did arrive at a precise percentage of unconsciously self-hating African Americans. We used this quote to make clear that you treated the race IAT as a perfectly valid measure of unconscious bias to arrive at the conclusion that a large percentage of African Americans (and a much larger percentage than White Americans) have a preference for the White out-group over the Black in-group. This is the key claim of your article and this is the claim that we challenge. At issue is the validity of the race IAT which is required to make valid claims about African Americans, not the statistical procedure to estimate a percentage.

(2) On p. 4, the authors write: “Jost et al.’s (2004) claims about African Americans follow a long tradition of psychological research on African Americans by mostly White psychologists. Often this research ignores the lived experience of African Americans, which often leads to false claims…” There are two very big problems with this section of the paper, which I have already pointed out to the authors (and they have apparently chosen to ignore them).
(a) The first is that this is an ad hominem critique, directed at me because of a personal characteristic, namely my race. For centuries philosophers have rejected this as a fallacious form of reasoning: whether something is true or false has nothing to do with the personal characteristics of the person making this claim. Furthermore, the senior author (Uli Schimmack) is obviously wielding this critique in bad faith; he, too, is White, so if he took his own objection seriously he would refrain from making any claims about the psychology of African Americans, but he obviously has not refrained from doing so in this submission
or in other forums.

It is a general observation that White researchers have speculated about African American’s self-esteem and mental states often without consulting African Americans. (see our quote of Adams). And I, Ulrich Schimmack, did collaborate with my African American wife on this paper to avoid this very same mistake.

(b) The second problem with this claim, which I have also already pointed out to the authors, is that the very same hypotheses about internalization of inferiority advanced by Jost et al. (2004) in the article in question were, in fact, made by a number of Black scholars, including W.E.B. DuBois, Frantz Fanon, Steven Biko, and Kenneth and Mamie Clark. These influences are discussed in considerable detail in my 2020 book, A Theory of System Justification.

Kenneth and Mamie Clark are the authors’ of the famous doll studies from the 1940s. Are we supposed to believe that nothing has changed over the past 80 years and that we can just use a study with children in 1940s to make claims about adult African Americans’ attitudes in 2014? What kind of social psychologists would ignore the influence of situations and culture on attitudes?

(3) On the next page the authors write: “Just like White theorists’ claims about self-esteem, Jost et al.’s claims about African Americans’ unconscious are removed from African Americans’ own understanding of their culture and identity and disconnected from other findings that are in conflict with the theory’s predictions. The only empirical support for the theory is the neutral score of African Americans on the race IAT.” Now, this claim is absurd. The book cited above describes hundreds of studies providing empirical support for the theory that have nothing to do with the IAT.

Over the past 10 years, we have seen this gaslighting again and again. When one study is criticized, it is defended by pointing to the vast literature of other studies that also support this claim. There may be other evidence, but it is not clear how this other evidence could reveal something about the unconscious. The whole appeal of the IAT was that it shows something that explicit measures cannot show. In fact, explicit ratings often show a stronger in-group favoritism among African Americans. To dismiss this finding, Jost has to allude to the unconscious which shows the hidden preference of Whites.

(4) They go on: “We are skeptical about the claim that most African-Americans secretly favor the outgroup based on the lived experience of the second author” (p. 5). But this was not our claim. As noted above, we found that 39.3% of African Americans (not “most”) exhibited a pro-White/anti-Black bias on the IAT. But, of course, the theory is about relations among variables, not about the specific percentage of Black people who do X, Y, or Z (which is, of course, affected by historical factors, among many other things).

Back to the game with percentages. We do not care whether you wrote 40% or 50%. We care about the fact that you make claims about African American’s unconscious based on an invalid measure.

(5) On p. 6 the authors write: “the mean score of African Americans on the race IAT may be shifted towards a pro-White bias because negative cultural stereotypes persist in US American culture. The same influence of cultural stereotypes would also enhance the pro-White bias for White Americans. Thus, an alternative explanation for the greater in-group bias for White Americans than for African Americans on the race IAT is that attitudes and cultural stereotypes act together for White Americans, whereas they act in opposite directions for African Americans” (p. 6).

As noted above, in July 2021 I wrote to the authors in an attempt to clarify that, from the perspective of SJT, the effects of “cultural stereotypes” in no way support “an alternative explanation” for out-group favoritism, because stereotypes (since the very first article by Jost & Banaji, 1994) have been considered to be system-justifying devices. Here is what I wrote to them: You describe the influence of “cultural stereotypes” as some kind of an alternative to system justification processes, but they are not. The theory started as a way of understanding the origins and consequences of cultural stereotypes. None of this contradicts SJT at all: “The nature of the task may activate cultural stereotypes that are normally not activated when African Americans interact with each other. As a result, the mean score of African Americans on the race IAT may be shifted towards a pro-White bias because negative cultural stereotypes persist in US American culture. The same influence of cultural stereotypes would also enhance the pro-White bias for White Americans.” Yes, this is perfectly consistent with SJT. In fact, it is part of our point. And the purpose of SJT is not to explain what happens “when African Americans interact with each other,” although it may shed some light on intragroup dynamics. I think of the scene in Spike Lee’s (a Black film director, as you well know) movie, School Daze, when the light-skinned and dark-skinned African Americans are fighting/dancing
with each other. There is plenty of system justification going on there, it seems to me.
We may (or may not disagree) in our interpretation of the social dynamics in School Daze, but I feel that the authors are now willfully misrepresenting system justification theory on the issue of “cultural stereotypes,” even after I explicitly sought to clarify their misrepresentation months ago: The activation of cultural stereotypes IS part of what we are trying to understand in terms of SJT.

Jost ignores that many other social psychologists have raised concerns about the validity of the race IAT because it may conflate knowledge of negative stereotypes with endorsement of these stereotypes and attitudes (Olson & Fazio, DOI: 10.1037/0022-3514.86.5.653). For anybody who cares, please ask yourself why Jost does not address the key point of our criticism, namely the use of race IAT scores to make inferences about African Americans’ unconscious without evidence that it can measure conscious or unconscious preferences of African Americans.

(6) It has been a while since I read the Bar-Anan and Nosek (2014) article, but my memory for it is incompatible with the claim that those authors were foolish enough to simply assume that the most valid implicit measures was the one that produced the biggest difference between Whites and Blacks in terms of in-group bias, as the present authors claim (pp. 7-8). As I recall, Bar-Anan and Nosek made a series of serious and comprehensive comparisons between the IAT and other tasks and concluded on the basis of those comparisons, not the one graphed in Figure 1 here, that the validity of the IAT was superior. I feel that, in addition to seriously representing my own work, they are also seriously misrepresenting the work of Bar-Anan and Nosek. Those authors should also have the opportunity to review and/or respond to the present claims being made about the (in) validity of the IAT.

Would you kill Dumbledore if he asked you to?

So, the reviewer relies on his foggy memory to question our claim instead of retrieving a pdf file and checking for himself. New York University should be proud of this display of scholarship. I hope Jost made sure to get his Publons credit. Here is the relevant section from Bar-Anan and Nosek (2014 p. 675;

(7) One methodological improvement of this paper over the previous draft that I saw is that this version now includes other implicit measures, including the single category IAT. However, the hypothesis stated on p. 9, allegedly on behalf of SJT, is incorrect: “System justification theory predicts a score close to zero that would reflect an overall neutral attitude and at least 50% of participants who may hold negative views of the in-group.” This is wrong on several counts and indicates a real lack of familiarity with SJT, which predicts that (to varying degrees) people are motivated to hold favorable attitudes toward themselves (ego justification), their in-group (group justification), and toward the overarching social system (system justification). This last motive—in a departure from the first two—implies that, based on the strength of system justification tendencies, advantaged group members’ attitudes toward the ingroup
will become more favorable and disadvantaged group members’ attitudes toward the in-group
will become less favorable. As noted above, SJT is not about making predictions about absolute scores or frequency counts—these are all subject to historical and many other contextual factors. It would be foolish to predict that African Americans have a neutral (near zero) attitude toward their own group or that 50% have a negative attitude. This is not what the theory says at all. Unless you have separate individual-level estimates of ego, group, and system justification scores, the most one could hypothesize is that on the single category IAT is that African Americans would have a more favorable evaluation of the out-group than European Americans would, and European Americans would have a more favorable
evaluation of the in-group than African Americans would. Note that I am writing this before looking at the results.

We are interested in African Americans and White Americans attitudes towards their in-groups and out-groups. If System Justification Theory (SJT) makes no clear predictions about these attitudes, we do not care about SJT. However, we do care about an article that has been cited over 1,000 times that makes the claim that many African Americans have unconscious negative attitudes towards their in-group and the support of this claim by means of computing a percentage of African Americans who scored above zero on a White-Black IAT (i.e., slower responses when African American is paired with good than when African American is paired with bad). We show that the race IAT lacks convergent validity with other implicit measures and that other implicit measures show different results. Thus, Jost has to justify why we should focus on the IAT results and ignore the results from other IAT tasks. So far, he has avoided talking about our actual empirical results.

(8) On pp. 10-11 the authors concede: “The model was developed iteratively using the data. Thus, all results are exploratory and require validation in a separate sample. Due to the small number of Black participants, it was not possible to cross-validate the model with half of the sample. Moreover, tests of group differences have low power and a study with a larger sample of African Americans is needed to test equivalence of parameters… models with low coverage (many missing data) may overestimate model fit. A follow-up study that administers all tasks to all participants should be conducted to provide a stronger test of the model.” These seem like serious limitations that, in the absence of replication with much larger samples, undermine the very strong conclusions the authors wish to draw.

So Jost can make strong claims (40% of African Americans have unconscious negative attitudes towards their group) based on an unvalidated measure, but when we actually show that the measure lacks validity, we need to replicate our findings first? This is not how science works. Rather, Jost needs to explain why other implicit measures, including the single category IAT do not show the same pattern as the race IAT that was used in the 2001 article.

(9) There is a peculiar paragraph on p. 13 in the “Results” sections, even though it goes well beyond the reporting of results: “Most important is the finding that race IAT scores for African Americans were unrelated to the attitudes towards the in-group and out-group factors. Thus, scores on the race IAT do not appear to be valid measures of African Americans’ attitudes. This finding has important implications for Jost et al.’s (2004) reliance on race IAT scores to make inferences about African Americans’ unconscious attitudes towards their in-group. This interpretation assumed that race IAT scores do provide valid information about African American’s attitudes towards the ingroup, but no evidence for this assumption was provided. The present results show 20 years later that this fundamental assumption is wrong. The race-IAT does not provide information about African Americans’ attitudes towards the in-group as reflected in other implicit measures.”

First of all, I don’t know if one can conclude, even in principle, that the race IAT is invalid for African Americans on the basis of a single study carried out with approximately 200 African American participants. There have been dozens, if not more, studies conducted (see Essien et al., 2020, JPSP), so it seems that any attempt to claim invalidity across the board should be based on a far more comprehensive analysis of larger data sets. Second, if I understand the specific methodological claim here it is that African Americans’ race IAT scores are not correlated with whatever the common factor is that is shared by the other implicit attitude measures (AMP, evaluative priming, and SC-IAT) and one explicit attitude measure (feeling thermometer). At most, it seems to me that one could conclude, on the basis of this, that the race IAT is measuring something different than the other things. This is not all that surprising; indeed, the IAT was supposed to measure something different from feeling thermometers. It seems like a stretch to conclude that the IAT is invalid and the other measures are valid simply because they appear to be measuring somewhat or even completely different things.

Third, the hyperbolic and misleading language implies that something about the IAT is a “fundamental assumption” of SJT, but this is false. The IAT was simply considered to be the best implicit measure at that time (20 years ago), so that is what we used. But it is silly to assume that hypotheses, especially “fundamental” ones, should be forever tied to specific operationalizations. Fourth, the attacking, debunking nature of this paragraph—against the IAT as a methodological instrument and against SJT as a theoretical framework—makes it clear that the authors are not really very interested in the dynamics of ingroup and outgroup favoritism among members of advantaged and disadvantaged groups (measured in different ways). It’s as if the real issue doesn’t even come up here.

Finally, we get to the substantive issue. First, let’s get the gaslighting out of the way. There have not been dozens of studies trying to validate the race IAT for African Americans. There have been zero. This is not surprising because there have also been no serious attempts to validate the race IAT for White respondents or IATs in general (Schimmack, 2021; The key problem is that social psychologists are poorly trained in psychometrics (i.e. the science of psychological measurement and construct validation; Schimmack, 2021,

Now on to the substantive issue. We are the first two show that among African Americans, several implicit measures (e.g., evaluative priming, AMP, single category IAT) show some (modest) convergent validity with each other. Not surprisingly, they also show convergent validity with explicit measures because all measures mostly reflect a common attitude (rather than one conscious and one unconscious ones) (Schimmack, 2021; All of these measures show as much (or more) positivity in in-group attitudes for African Africans as for White Americans. This is an interesting finding because positive attitudes on explicit measures were dismissed by Jost. But now several implicit measures show the same result. Thus, it is not a simple rating bias. Now the race IAT and its variants are the odd ones with a different pattern. Why? That remains to be examined, but to make claims about African Americans’ attitudes we would need to know the answer to this question. Maybe it is just a method artifact? Just raising this possibility is a noteworthy contribution to science.

(10) Eventually, a few pages later, the authors get around to telling us what they really found with respect to the actual research question: “Also expected was the finding that out-group attitudes of African Americans, d = .42, 95%CI , are more favorable than out-group attitudes of White Americans, d = .20, 95%CI.” So, um, African Americans exhibited more favorable attitudes toward Whites than Whites exhibited toward African Americans. This is precisely what system justification theory would have predicted, as I noted above (before looking at the results). It is, perhaps, an interesting discovery — if it is replicated with larger samples — that out-group attitudes are unrelated to in-group attitudes for both groups and that in-group attitudes were equally positive for both groups. But, with respect to the key question of out-group favoritism, the authors actually obtained support for SJT but refuse to even acknowledge it. Is this really what science is about? On the contrary, they draw this outrageous conclusion: “Thus, support for the system justification theory rests on a measurement artifact.” In point of fact, when the authors return to the comparative ingroup vs. outgroup measure they arrive at a conclusion that is virtually the same as Jost et al. (2004): “White Americans’ scores on the race IAT
are systematically biased towards a pro-White score, d = .78, whereas African Americans’ scores are only slightly biased towards a pro-Black score, d = -.19.” Yes, advantaged groups tend to show reasonably strong in-group favoritism, whereas disadvantaged groups tend to show weak in-group favoritism, with substantial proportions showing out-group favoritism. This is precisely what we found 20 years ago. The authors and I already had this exchange back in July, but their paper contains the same misleading statements as before. Here is our exchange:

You write: “Proponents of system justification theory might argue that attitudes towards the in-group have to be evaluated in relative terms. Viewed from this perspective, the results still show relatively more in-group favoritism for White Americans, d = .62 – .20 = .42 than African Americans, d = .54 – .40 = .14. However, out-group attitudes contribute more to this difference, d = .40 = .20 = .20, than in-group differences, d = .62 – .54 = .08. Thus, one reason for the difference in relative preferences is that African Americans attitudes towards Whites are more positive than White Americans’ attitudes towards African Americans.”
My response: Yes, this is key. We are talking about the ways in which people respond to relative status, power, and wealth, etc. rankings within a given social system (or society). The fact that “African Americans attitudes towards Whites are more positive than White Americans’ attitudes towards African Americans” is supportive of SJT.

Oh boy, sorry if you had to read all of this. Does it make sense to make a distinction between in-group attitudes and out-group attitudes? I hope we can agree that it does. Would we be surprising if Black girls like White dolls more than White girls like Black dolls? Not really and it doesn’t tell us anything about internalizing stereotypes. The important and classic doll study did not care about the comparison of out-group attitudes. The issue was whether Black children preferred White dolls over Black dolls and Jost et al. (2001) claimed that many African Americans internalized negative stereotypes of their group and positive stereotypes of Whites so that they have a relatively greater preference of White over Black. The problem is that the race IAT confounds in-group and out-group attitudes and that measures that avoid this confound like the single-attribute IAT don’t show the same result.

(11) Another huge problem with this whole research program is that it ignores completely the strongest piece of evidence for SJT in this context, namely that the degree of out-group favoritism among disadvantaged groups is positively associated with support for the status quo, measured in terms of political conservatism and individual difference measures of system-justifying beliefs (e.g., see Ashburn-Nardo et al., 2003; Essien et al., 2020; Jost et al., 2004). If Blacks’ responses on the IAT were random or meaningless, I see no reason why they would be consistently correlated with other measures of system justification. But the voluminous literature shows that they are (Essien et al., 2020). Although I have pointed this out to the authors before, they have simply ignored the issue once again, even though this is a key piece of evidence that supports the SJT interpretation of implicit attitudes about advantaged
and disadvantaged groups

Back to gaslighting. Let’s say there are some studies that show this pattern. How does Jost explain the pattern of results in the present study? He doesn’t. That is the point.

(12) All of the above problems are repeated in the General Discussion, so there is no need to address them again point by point. But I will say that other key issues that the authors and I discussed in July are also ignored in the present submission: I wrote: This statement is interesting but far too categorical, in my opinion: “It would be a mistake to interpret this difference in evaluations of the out-group as evidence that African Americans have
internalized negative stereotypes about their in-group.” First, it is not an either/or situation, as if people either love their group or hate it. This is not how people are. There are multiple, conflicting motives involving ego, group, and system justification, and ambivalence is part of what interests us as system justification theorists. Second, there is plenty of other evidence suggesting that—again, to some degree—African Americans and other groups “internalize”
negative stereotypes. Are you really suggesting that there are NO psychological consequences for African Americans living in a society in which they are systematically devalued? I’m still waiting for an answer to that last question. The purpose of this submission, it seems to me, is not to illuminate anything, really, and indeed very little, if anything, is illuminated. The purpose of the paper, it seems, is to create the appearance of something scandalous and awful and perhaps even racist in the research literature when, in fact, the substantive results obtained here are very similar to what has been found before. And if the authors really want to declare that the race-based IAT is a completely useless measure, they have a lot more work to do than re-analyzing previously published data from one relatively small study.

With the confidence of a peer-reviewer in the role of an expert, Jost feels confident enough to lie when he writes “In fact, the substantive results obtained here are very similar to what has been found before.” Really? Nobody has examined convergent validity of various implicit measures among African Americans before. Bar-Anan and Nosek collected the data, but they didn’t analyze them. Instead, they simply concluded that the race IAT is the best measure because it shows the strongest differences between groups. Here we show that implicit measures that can be scored to distinguish in-group and out-group attitudes do not show that African Americans hold negative views of their in-group. Does it matter? Yes it does. Where do African Americans want to live? Who do they want to marry? Would they want other African Americans as colleagues? The answers to these questions depend on their in-group attitudes. So, if Jost cared about African Americans rather than about his theory that made him famous, he might be a bit more interested in our results. However, Jost just displays the same level of curiosity about disconfirming and distressing evidence as many of his colleagues; that is, none. Instead, he fights like a cornered animal to defend his system of ideas against criticism. You might even call this behavior system justification.

15 Years of PLOS ONE – Author Perspectives

This December marks 15 years since PLOS ONE published its first papers. As we celebrate this milestone, we invited authors of some of the first papers to be published, as well as an author of a more recent paper, to share information about their careers, their perspectives on Open Science, and their experiences as PLOS ONE authors.

We spoke with Miriam Kolko (University of Copenhagen), Matthew Goddard (University of Lincoln), Andrej A Romanovsky (Arizona State University) and Seppo Ylä-Herttuala (University of Eastern Finland).

Their perspectives provide a fascinating insight into how their research careers have progressed in the past fifteen years, as well as the changes the research world has experienced. We hear about the importance of open science practices, and how open access publishing has gone from a relatively new idea fifteen years ago to an almost ubiquitous endeavor in the present day. They also discuss their experiences of both expected and unexpected discoveries, how they have stayed on track in pursuing their research goals, and the importance of being a good collaborator and keeping flexible in a dynamic research landscape.

Miriam Kolko

Miriam Kolko is a chief physician and glaucoma specialist at the Copenhagen University Hospital, Rigshospitalet-Glostrup and an author of the PLOS ONE paper “The Prevalence and Incidence of Glaucoma in Denmark in a Fifteen Year Period: A Nationwide Study [1]”.

Could you tell us a bit about what you are working on at the moment? What does your lab group look like?

MK: I am in the fortunate situation of leading the research group Eye Translational Research Unit, EyeTRU. We work with different aspects of glaucoma. All our research projects have the patient in mind and we thus have preclinical and clinical models to explore the pathophysiology behind glaucoma. In addition, we work to stratify and optimize existing treatments for glaucoma patients. We are particularly aware of the inappropriate side effects that occur with preservative-containing eye drops as well as the sparse regulation of generics. Finally, we work with big data to identify predictive factors for risk assessment and earlier detection of sight-threatening diseases, such as glaucoma. Currently, EyeTRU consists of 2 postdocs, 8 PhD students, a laboratory technician and several master’s and bachelor’s students.

It is essential to share knowledge, including sharing data, so that the most knowledge is obtained that can benefit patients

Miriam Kolko

What does a typical day at work look like for you?

MK: I am a clinician-scientist and spend half my time with patients and half time with teaching and research. I treat patients with glaucoma medically and surgically twice a week. The remaining time goes with research teaching and multicenter studies.

In your field, how important are open science practices? Do you have any success stories of having shared or re-used data, code, a preprint, or something else?

MK: Transparency is really important and creates the environment for original ideas and collaborations. The ability to publish preprints is one of many ways to share research at an early stage. Another very important prerequisite for knowledge sharing and innovative research is a safe working environment. Sure, competition is important, but teamwork is the key to ground-breaking research. In general, I believe that it is essential to share knowledge, including sharing data, so that the most knowledge is obtained that can benefit patients.

Can you tell us about an important moment in your career as a scientist, which helped shape you as a researcher?

MK: My research career started in the United States as a Fulbright scholar and later as a PhD student Under Professor Nicolas G Bazan. I spent a total of 5 years in the USA, which shaped me as a basic science researcher and has since given me the foundation to create a translational research environment in my research group Eye Translational Eye Research, EyeTRU.

PLOS ONE is celebrating 15 years as a journal this year. Can you tell us where you were in your career 15 years ago? If you could give advice to your former self as a researcher, what would you say?

MK: Believe in the impossible and keep going. Life as a clinician-scientist or full researcher is fantastic, but you face challenges along the way. The environment is harsh and the best advice is to stay behave as one would like others to behave.

Matthew Goddard

Matthew Goddard is a professor at the University of Lincoln and an author of the PLOS ONE paper “Invasion and Persistence of a Selfish Gene in the Cnidaria [2].”

Looking back at your paper, which was one of the first papers published in PLOS ONE, what did you learn from this study? Did you continue to work in this field and build on these findings?

MG: This paper was the first report inferring the dynamics of the evolution of homing endonuclease genes (HEGs: a type of ’selfish’ gene or non-Mendelian element) in metazoans. The surprising finding was they appear to have horizontally transferred between Cnidarian species. This was one of the final papers in my line of enquiry into HEGs and I moved on to other areas after this.

To meaningfully translate science done in university labs to the outside world is a hard but rewarding activity.

Matthew Goddard

Do you remember when you first heard of PLOS ONE? What made you first interested in publishing with PLOS ONE?

MG: This was back in the days before the explosion of journals occurred and most were still only accessible via subscriptions. I recall hearing the news of a new type of journal that was completely open access being suggested and I liked the idea of this very much. It was a gamble publishing in a new journal with a new format with no impact factor etc. but this was worth it as the ethos of the open access idea sat well with us.

Could you tell us a bit about what you are working on at the moment? What does your lab group look like?

MG: Mostly studying the effects of agricultural management (i.e. conservation agricultural approaches) and land-use change on soil biology (using DNA and classic methods) and physiochemical attributes (mainly C-sequestration and water retention). These are important areas, especially for the UK, to help understand how to best manage land given climate change and the desire to move to more sustainable agricultural approaches. There is a lack of data in this area.

In your field, how common are open science practices? Do you have any success stories of having shared or re-used data, code, a preprint, or something else?

MG: Very common, and pre-prints of any publication must be available to evaluated via the UK Research Excellence Framework (REF) system. I tend to conduct studies that generate data but we have used whole genome DNA sequence data from various microbes that are publicly available to better understand the genomes that we have sequenced. Such resources are invaluable to help understand the larger ecological and genetic picture.

PLOS ONE is celebrating 15 years as a journal this year. Can you tell us where you were in your career 15 years ago? If you could give advice to your former self as a researcher, what would you say?

MG: I had just completed my first post-doctoral position at the NERC centre for population biology at Imperial College’s Silwood Park in the UK. I am not sure about advice to my former self, but to someone at the first post-doc stage of their career it would be to expose yourself to and learn from as wide a diversity of scientists, ideas and places as possible.

Publishing papers is crucial to a career in research. Can you tell us of an event or memory that was not a paper, which influenced your career as a researcher?

MG: Hard: probably moving from the ‘blue-skies’ area where I mostly just interacted with other researchers during my PhD and post-doc to interacting with farmers/agricultural workers and gaining an appreciation of how to attempt to meaningfully translate science done in university labs to the outside world is a hard but rewarding activity.

Andrej A Romanovsky

Andrej A Romanovsky is a founder of Zharko Pharma and an Adjunct Faculty member at Arizona State University, and author of the PLOS ONE paper “Neural Substrate of Cold-Seeking Behavior in Endotoxin Shock [3]”.

Looking back at your paper, which was one of the first papers published in PLOS ONE, what did you learn from this study?

AAR: Actually, that was the very first paper published by PLOS ONE [3]. That study was conducted by two brilliant researchers, Camila Almeida and Alex Steiner, who at that time were postdocs in my FeverLab. Both were trained by Professor Guillermo Branco, a patriarch of Brazilian thermophysiology, and both have become highly productive independent scientists. Camila, who played a leading role on that study, and Alex made a remarkable discovery by showing that behavioral thermoregulation does not require the integrity of the brain structure called hypothalamus. Many textbooks on thermoregulation state that body temperature is controlled by a “central government” located in the hypothalamus. This widely spread erroneous view is allegedly supported by the fact that rats with lesions in a certain part of the hypothalamus cannot defend their body temperature against heat or cold. Camila and Alex reproduced these experiments. They found that rats with lesioned hypothalami indeed could not defend themselves against thermal challenges – but only when they were restrained in little cages and could not use behavioral thermoregulation. When the same rats were allowed to move freely and select a warmer or cooler environment, they exhibited fully competent thermoregulatory responses – no weakness whatsoever! That study was a blow to the idea that the hypothalamus is the “chief commander” of thermoregulation. If the readers of this blog are interested to learn more about how this idea was discrowned and what replaced it, please go to my review [5].

But most importantly, we enjoyed – and still enjoy and are proud of – being a part of the open access revolution.

Andrej A Romanovsky

Do you remember when you first heard of PLOS ONE? What made you first interested in publishing with PLOS ONE?

AAR: The history of science is the history of illusions (like the one about the hypothalamus controlling body temperature)… In 2006, we published in PLOS Biology a study conducted in FeverLab by Alex Steiner (mentioned above) and Andrei Ivanov (now Professor at Cleveland Clinic), with the help of multiple collaborators [6]. This study, which found that fever is initiated outside of the brain, in the lungs and liver, was well-received. Encouraged by this success, we submitted our next study to PLOS Biology – again! Soon we received good reviews and an invitation to move the paper to … PLOS ONE. At that time, PLOS ONE did not exist, and this is where illusions enter our story. Listen, everybody knows that there are many Nature journals, right? Nature Neuroscience, Nature Immunology, Nature This, Nature That… But among all the Nature journals, there is one that stands like Gulliver among the Lilliputians: Nature! Camila, Alex, and I tried to imagine what type of journal PLOS ONE would be. And we came to the conclusion, or should I say illusion, that PLOS ONE would be the same to the PLOS journals as Nature was to the Nature journals! It was due to this illusion that we accepted the invitation, and this is how the very first PLOS ONE article [3] was born! And although PLOS ONE did not turn into the most prestigious PLOS journal (and was not designed to do so), our article seeded what has grown to become the Gulliver of all Gullivers in scientific publishing – the journal that has published more papers than any other academic journal in the history of mankind. But most importantly, we enjoyed – and still enjoy and are proud of – being a part of the open access revolution.

Could you tell us a bit about what you are working on at the moment?

AAR: I retired from laboratory research in 2019 to dedicate my remaining professional life to making several new drugs. The ideas for all these drugs came from or are closely related to my past research. Together with my colleagues, we have launched a couple of startups, including my favorite, Zharko Pharma. The name is a transliteration of the Russian adverb жарко (žárko), which means hot, like in feeling uncomfortably hot. Zharko’s goal is to develop a drug for treating the thermal discomfort experienced by menopausal women – hot flashes. Hot flashes are a widely spread condition that are debilitating in some women, and no effective non-hormonal treatment is currently available.

Publishing papers is crucial to a career in research. Can you tell us of an event or memory that was not a paper, which affected your research?

AAR: Yes, I can tell you about a silly event in FeverLab’s life that gave us a cover of the Journal of Neuroscience. When Andras Garami (now Head of Thermophysiology Department at University of Pécs Medical School in Hungary) worked with me as a postdoc, we were studying the role of the so-called TRPV1 channel in thermoregulation. The latest Nobel Prize in Physiology or Medicine was given to David Julius and Ardem Patapoutian “for their discoveries of receptors for temperature…”, including TRPV1. This channel is expressed on sensory nerves and is responsible for the burning sensation we have while eating chili peppers. Being a Hungarian, Andras was not a stranger to spicy foods, but he wanted to experience first-hand how spicy “spicy” can be and was looking in grocery stores for the hottest peppers. Eventually he found a habanero so spicy that blisters covered his lips after he tasted it. Not a surprise that many mammals avoid eating spicy peppers! Soon thereafter we needed to confirm the absence of the TRPV1 channel in TRPV1-knockout mice. We realized that these mice should not feel the hotness of habanero and would be expected to be able to eat this pepper, whereas “normal” mice (those with a functional TRPV1) should avoid this blister-inducing “poison”. Andras then ran experiments in mice, and these experiments confirmed our expectations. We later published an article about thermoregulation in TRPV1-knockout mice in the Journal of Neuroscience [7], a knockout mouse devouring a habanero stares out at you with hungry eyes from the cover of this issue.

Seppo Ylä-Herttuala

n Academy Professor at the University of Eastern Finland and author of PLOS ONE paper “Short and Long-Term Effects of hVEGF-A165 in Cre-Activated Transgenic Mice [4]”

Looking back at your paper, which was one of the first papers published in PLOS ONE, what did you learn from this study? Did you continue to work in this field and build on these findings?

SYH: We have a long history in therapeutic angiogenesis studies and this PLOS ONE paper was one of the first to realistically study long-term safety concerns of VEGF-A overexpression in vivo. The results were very important since they showed that even a low-level VEGF-A expression in vivo for an extended period of time (> one year) can cause significant side effects, such as cancer, thus preventing the use of vectors leading to long-term transgene expression in clinical VEGF-A studies. Also, Cre-loxP technology was quite new at that time and the paper showed how useful it is for in vivo safety and efficacy studies. We still use this mouse model for retinal angiogenesis studies.

Do you remember when you first heard of PLOS ONE? What made you first interested in publishing with PLOS ONE?

SYH: I think that it was from PLOS website.

For younger researchers, I would say that “Be brave and aim high to reach your vision and goals but be also realistic and prepared for sharp turns and surprises in your research”.

Seppo Ylä-Herttuala

Could you tell us a bit about what you are working on at the moment? What does your lab group look like?

SYH: We are continuing our pioneering work in cardiovascular gene therapy. After several advances in vector design, transgene optimization and improved local cardiac delivery methods, we have continued to apply therapeutic angiogenesis for the treatment of severe myocardial ischemia and have now conducted five clinical phase 1 and 2 trials with adenoviral vectors. Our most recent multicenter trial is currently recruiting patients in five cardiology centers in the EU for the treatment of severe coronary heart disease. We also have a very active research program for new vector development and in VEGF signaling mechanisms. My research group currently has 35 members.

In your field, how common are open science practices? Do you have any success stories of having shared or re-used data, code, a preprint, or something else?

SYH: Open access practices are very common in biomedical and clinical research. Most of our papers are now open access. This is also a requirement of EU and ERC grants which we have had during the last 10 years. Also, we have used open access data archives to identify new non-coding RNAs and gene expression profiles in mouse, pig and human heart and other tissues. From these sources we have identified new short hairpin RNAs and miRs which can regulate endogenous VEGF expression.

PLOS ONE is celebrating 15 years as a journal this year. Can you tell us where you were in your career 15 years ago? If you could give advice to your former self as a researcher, what would you say?

SYH: Fifteen years ago I was a just-appointed professor of Molecular Medicine with a very enthusiastic research program in angiogenesis and cardiac ischemia, extending from VEGF signaling studies to translational and clinical studies. Most of these goals have now come through, albeit with several surprises and new turns in the research direction over the years. For younger researchers, I would say that “Be brave and aim high to reach your vision and goals but be also realistic and prepared for sharp turns and surprises in your research”.

Publishing papers is crucial to a career in research. Can you tell us of an event or memory that was not a paper, which influenced your career as a researcher?

SYH: I so well remember the moment in 1996 when we, as the first in the world, did the first adenoviral gene transfer to human arteries with percutaneous catheter technique. This paved the way for my further research career in angiogenesis and cardiac ischemia.

Author biographies

Miriam Kolko

Miriam Kolko is chief physician and glaucoma specialist at the Copenhagen University Hospital, Rigshospitalet-Glostrup. She is also professor in translational eye research at the Department of Drug Design and Pharmacology at the University of Copenhagen. Prof. Kolko is president of the Danish Glaucoma Society and board member of Fight for Sight, Denmark. During medical school Prof. Kolko completed a Fulbright Scholarship at the Neuroscience Center of Excellence, Louisiana State University, US. Here she became interested in basic neuroscience. After medical school, she completed a Ph.D. and a postdoctoral position in the same laboratory. In 2003, Prof. Kolko returned to Denmark after a total period of 5 years in the United States. She completed another postdoctoral position, after which she underwent residency in ophthalmology followed by a 3-year glaucoma fellowship. From 2014 to 2017, Prof. Kolko directed glaucoma in the Region of Zealand until she was assigned to her current position. At the University of Copenhagen, Prof. Kolko is heading the research cluster “Personalised Medicine”. In addition, Prof. Kolko is heading the research group, Eye Translational Research Unit (EyeTRU). The research in EyeTRU concerns cellular, translational, epidemiological and clinical models for understanding glaucomatous neurodegeneration. Prof. Kolko has received more recognitions. Among these, she has received the first “Award of excellence” from the Danish Ophthalmological Association and the Lions Prize. Prof. Kolko is co-chair of the neuroprotection SIG in the EGS and member of the EGS membership and national society committee. Recently, Prof. Kolko was elected to the WGA, Associate Advisory Board and as EVER glaucoma chair. Finally, Prof. Kolko was elected member of the board of directors of ACTA Ophthalmologica. All in all, Prof. Kolko is one of the few clinician-scientists that bridge between a clinical career with medical and surgical treatment of glaucoma patients and basic and translational research models to understand the pathophysiology behind as well as the current management of glaucoma.

Matthew Goddard

Professor Matthew R Goddard, PhD, BSc hons, DIC, FHEA undertook a PhD and post-doctoral fellowship in evolutionary and ecological biology at Imperial College (Silwood Park), then moved to a Faculty position at University of Auckland (New Zealand) in 2004 and then gain a Professorial position at the University of Lincoln (UK) in 2015. Mat has worked extensively with the agricultural sector and spearheaded microbial ecology revealing the differential distribution of microbes associated with agriculture and how this may effect agricultural outputs. Mat now has a strong focus on soils and runs large scale agri-ecosystem projects fusing next-generation DNA sequencing to evaluate biodiversity (not just microbes) with soil physics and chemistry to both understand the effect of agricultural managements and land-use change to provide evidence to inform decisions by land owners that aim to minimise disease and elevate agricultural and ecological health and quality.

Andrej A. Romanovsky

Andrej A. Romanovsky, MD, PhD, FAPS, is a physiologist and neuroscientist with primary expertise in body temperature regulation. In 2019, he left his Professor position at St. Joseph’s Hospital in Phoenix, Arizona, to work on the development of drugs for disorders of thermoregulation and hot flashes. Dr. Romanovsky helped to found the pharmaceutical startups Zharko Pharma, Catalina Pharma, and Synventa and currently works with these companies as an officer, Board member, or consultant. His current primary affiliation is with Zharko Pharma in Olympia, Washington; he also holds an Adjunct Faculty position at Arizona State University. Dr. Romanovsky has published more than 130 articles in peer-reviewed scientific journals. He is the Editor-in-Chief of the journal Temperature and the Editor of two volumes on Thermoregulation: From Basic Neuroscience to Clinical Neurology published by Elsevier within the Handbook of Clinical Neurology series in 2018. In 2019, he was elected as a Fellow of the American Physiological Society. Andrej’s hobby is tree farming. He has co-founded the family partnership Tree Fever: Forestland Conservation and Development and since 2011 has been operating a Douglas-fir tree farm growing timber in western Washington. He is married to Nancy L. Romanovsky, an oil painter, and they have four children and two grandchildren.

Seppo Ylä-Herttuala

Dr. Seppo Yla-Herttuala, MD, PhD, FESC is a world leader in cardiovascular gene therapy for ischemic diseases. His team was the first to use adenovirus-mediated gene transfer to human arteries already in 1996. Since then, he has conducted five phase 1-2 clinical trials in cardiovascular gene therapy. He is also the originator of the concept of epigenetherapy. His group has been widely recognized for basic biology, translational and epigenetic research of the vascular endothelial growth factors (VEGFs), especially focusing on the new members of the VEGF family. Previously he worked with oxidized LDL and atherosclerosis and was the first to show that OxLDL exists in human atherosclerotic lesions. His list of publications includes over 600 peer reviewed scientific articles.


1. Kolko M, Horwitz A, Thygesen J, Jeppesen J, Torp-Pedersen C. The Prevalence and Incidence of Glaucoma in Denmark in a Fifteen Year Period: A Nationwide Study. PLoS ONE. 2015;10(7): e0132048. doi: 10.1371/journal.pone.0132048

2. Goddard MR, Leigh J, Roger AJ, Pemberton AJ. Invasion and Persistence of a Selfish Gene in the Cnidaria. PLoS ONE. 2006;1(1): e3. doi: 10.1371/journal.pone.0000003

3. Almeida MC, Steiner AA, Branco LGS, Romanovsky AA. Neural Substrate of Cold-Seeking Behavior in Endotoxin Shock. PLoS ONE. 2006;1(1): e1. doi: 10.1371/journal.pone.0000001

4. Leppänen P, Kholová I, Mähönen AJ, Airenne K, Koota S, Mansukoski H, et al. Short and Long-Term Effects of hVEGF-A165 in Cre-Activated Transgenic Mice. PLoS ONE. 2006;1(1): e13. doi: 10.1371/journal.pone.0000013

5. Romanovsky AA. The thermoregulation system and how it works. Handb Clin Neurol. 2018;156: 3-43. doi: 10.1016/B978-0-444-63912-7.00001-1

6. Steiner AA, Ivanov AI, Serrats J, Hosokawa H, Phayre AN, Robbins JR, Roberts JL, Kobayashi S, Matsumura K, Sawchenko PE, Romanovsky AA. Cellular and molecular bases of the initiation of fever. PLOS Biol. 2006;4: e284. doi: 10.1371/journal.pbio.0040284

7. Garami A, Pakai E, Oliveira DL, Steiner AA, Wanner SP, Almeida MC, Lesnikov VA, Gavva NR, Romanovsky AA. Thermoregulatory phenotype of the Trpv1 knockout mouse: thermoeffector dysbalance with hyperkinesis. J Neurosci 2011;31: 1721-1733. doi: 10.1523/JNEUROSCI.4671-10.2011

Disclaimer: Views expressed by contributors are solely those of individual contributors, and not necessarily those of PLOS.

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Contemporary Publishing Fellow

“The 21st-Century Publishing Fellow is a member of the Library’s Research Data and Digital Scholarship unit, reporting to the Assistant University Librarian, Research Data and Digital Scholarship. The incumbent contributes to the team’s efforts to transform the digital publishing landscape by piloting a publication program focusing on high-quality, media-rich, networked, and interactive public scholarship, often produced under the aegis of a new collaboration with Penn Press.

The incumbent proactively explores emerging publishing technologies, platforms, and practices, and provides leadership in recommending, planning, and implementing pilot digital publishing services that will provide the campus community with the tools, resources, and infrastructure for publishing multimodal projects and experimental digital scholarship….


Lead the development, management, and assessment of a pilot of sustainable, innovative open publishing services for publications that may include e.g., archival materials, time-based media, data, and other digital media…. ”

ESG data is a public good. Let’s open it up. – ImpactAlpha

“There is a lot of confusion about how to implement climate as well as environmental, social and governance, or ESG, analysis in finance. Today, ratings agencies, researchers and fund managers use different, often proprietary models to assess companies’ ESG performance. That makes it difficult to compare one company to another, and leaves room for greenwashing. 

It also holds back a full throttled re-pricing of social and environmental-related risks and opportunities. 

Climate risk analysis should not be an “investment edge,” but a “public good.” Global warming is already causing more frequent extreme weather events, and scientists warn that we are headed for far worse without a dramatic course correction. 

So here’s an idea: let’s make climate and ESG data open to everyone. …”

SPARC Statement on UNESCO Ratification of Open Science Recommendation

“SPARC welcomes the unanimous ratification of the UNESCO Recommendation on Open Science during its 41st General Conference.  This action represents an enormous step forward towards creating a global knowledge sharing ecosystem that is both open and equitable by design.

As the COVID-19 pandemic and the climate crisis have underscored, there is an urgent need to accelerate scientific progress and to reimagine how we produce, share, and communicate scientific information. The UNESCO Open Science Recommendation provides a critical tool to catalyze change towards this on a global scale. 

Developed through an inclusive, transparent, and multi-stakeholder consultation process, the Recommendation is the first global standard-setting framework for international open science policies and practices.  It provides a common definition of open science that covers all scientific disciplines and scholarly practices while also encompassing the broad range of movements working to make scientific knowledge openly accessible and reusable for those within and outside the traditional scientific community….”

Application of tools to support Linked Open Data | Emerald Insight

Abstract:  Purpose

These projects aim to improve library services for users in the future by combining Link Open Data (LOD) technology with data visualization. It displays and analyses search results in an intuitive manner. These services are enhanced by integrating various LOD technologies into the authority control system.


The technology known as LOD is used to access, recycle, share, exchange and disseminate information, among other things. The applicability of Linked Data technologies for the development of library information services is evaluated in this study.


Apache Hadoop is used for rapidly storing and processing massive Linked Data data sets. Apache Spark is a free and open-source data processing tool. Hive is a SQL-based data warehouse that enables data scientists to write, read and manage petabytes of data.


The distributed large data storage system Apache HBase does not use SQL. This study’s goal is to search the geographic, authority and bibliographic databases for relevant links found on various websites. When data items are linked together, all of the data bits are linked together as well. The study observed and evaluated the tools and processes and recorded each data item’s URL. As a result, data can be combined across silos, enhanced by third-party data sources and contextualized.

Developing a sustainable cultural heritage information system | Emerald Insight

Abstract:  Purpose

The purpose of this paper is to emphasize the need for developing an Indian cultural heritage information system (CHIS) where the cultural heritages can efficiently document, manage and preserve and integrate with a searchable user interface mechanism. Further, the study scopes out the feasibility of developing single-window comprehensive national CHIS for all the cultural heritage properties of India enlisted in the United Nations Educational, Scientific and Cultural Organization (UNESCO’s) World Heritage list.


Conservation efforts and their sustenance require the support of a knowledge base cum digital archiving and information retrieval tool. The present study identifies the basic requirements, strategies and the execution of designing a reliable information system for cultural heritage inheritances to safeguard them to facilitate access to the current and future resilient communities. Approach on issues and challenges associated while developing such an information system has also been addressed with possible recommendations.


In India, even though regional level conservation efforts are occurring, no comprehensive information system, which gives the whole perspective of the item or environment of heritage site, has been developed for the heritage sites recognized by UNESCO in its World Heritage list from India. Developing such a comprehensive digital archive for cultural heritage helps to showcase its assets and ensures its visibility globally without hampering the physical form. Application Information and Communication Technology and digital technologies can extensively be used coupled with mechanisms such as mobile devices, digital systems and content visualization techniques to support the efficient and effective management in a systemized way.

Research limitations/implications

As a pilot study, this paper examined the cultural heritage properties incorporated in the UNESCO World list. There are many lesser-known and unprotected cultural heritages in different parts of the country having artistic value and the unique characteristics, and the possibility of building the similar kind of information system for them with innovative technological solutions are not covered under this study.

Practical implications

Access to such an exclusive digital archive in a single-window platform would greatly support administrators, tourist departments, culture departments, development administration and conservation activists. The digital version of cultural inheritances created under the cultural heritage of India must have relevance to different subject fields such as history, archeology, manuscript logy, art, administration, knowledge management, computer science and library science. Also, it ensures that the resources remain accessible to the public without any restrictions provided with a comprehensive recapitulation.


To the authors’ best knowledge, no such comprehensive system envisages or is practiced in the country. Developing such a system with technological and data infrastructure also helps to understand the value, support the activities related to cultural heritage and bring the local community to support and initiate such heritage conservation activities.

Will preprint servers disrupt scientific publishing, reference work and information science? | Emerald Insight

Abstract:  The purpose of this paper is to discuss whether preprint servers are a disruptive technology for science, librarians or information seeking among the general population.


This column explores what preprint servers are, how they are used in the world of science, how their usage changed in response to the deluge of COVID-19 related research papers and how they might impact the work of librarians and society in general.


Preprint servers are not a highly disruptive technology, but they do challenge both scientists and librarians to understand them better, use the information they find on them with care and educate society in general on topics such as peer review and the importance of using well-vetted, good quality science in making important decisions.


Up until the past year and a half, only a small segment of the librarian profession needed to be concerned with preprint servers. With the increasing presence of references to non-peer-reviewed articles from preprint servers in popular media reports, most librarians now need to know something about this technology. It is also useful to consider how the technology might benefit and create challenges for their work.

Unveiling the veiled: Wikipedia collaborating with academic libraries in Africa in creating visibility for African women through Art+Feminism Wikipedia edit-a-thon | Emerald Insight

Abstract:  Purpose

This study aims to show that digital literacy can serve as a tool for effecting social change and highlights the achievements of an academic library in digital content creation using the Wikipedia platform.


The study adopted qualitative research method, Interview and document analysis were used for data gathering. Data gathered were analysed using content (conceptual) analysis.


Findings showed that the library has created or edited digital content for various categories of women, such as women in academia, industry and politics. These entries have received more than eight million views over a period of two years, which shows that the entries are being utilised. However, the editing exercise had been confronted with challenges such as accessing reliable citations in terms of the notability and verifiability policy of Wikipedia amongst others.

Practical implications

Currently, people rely more on online resources for their research, leaving physical library resources unused. Even, more students start their research online using Wikipedia. Thus, libraries could create visibility for their physical material using regularly visited sites like Wikipedia and its sister projects such as Wikidata; otherwise, these physical materials will remain invisible to the people that needed them.


Contributing to Wikipedia by creating a new entry or editing an existing one can help students to deepen their knowledge about a subject; Wikipedia editing may serve as an avenue for improving information literacy skills. Drawing from the theory of cyberfeminism as used in the study, information and communications technology has the potential to empower women and transform gender relations.

Barcamp Open Science 2022

Save the date! – Online 7th March 2022 #oscibar Barcamp Open Science is a friendly and open scpace for those interested in making open science happen and to connect with open science communities. In true Barcamp style the day long event is made up of session suggested by the wider community. If you want to test out an idea, share a project, or have a question you think the open science community…


Building a Tool to Find Translated Scientific Articles

You know an article exists, but cannot read its language. So you go to our tool, paste the Digital Object Identifier of the article and get a list with translated versions. You manage your articles in a reference manager and notice that an article on your reading list is now also available in your mother tongue. You are really enthusiastic about a new article that was just published…


Can I use this publicly available dataset to build commercial AI software? Most likely not

Abstract:  Publicly available datasets are one of the key drivers for commercial AI software. The use of publicly available datasets (particularly for commercial purposes) is governed by dataset licenses. These dataset licenses outline the rights one is entitled to on a given dataset and the obligations that one must fulfil to enjoy such rights without any license compliance violations. However, unlike standardized Open Source Software (OSS) licenses, existing dataset licenses are defined in an ad-hoc manner and do not clearly outline the rights and obligations associated with their usage. This makes checking for potential license compliance violations difficult. Further, a public dataset may be hosted in multiple locations and created from multiple data sources each of which may have different licenses. Hence, existing approaches on checking OSS license compliance cannot be used. In this paper, we propose a new approach to assess the potential license compliance violations if a given publicly available dataset were to be used for building commercial AI software. We conduct trials of our approach on two product groups within Huawei on 6 commonly used publicly available datasets. Our results show that there are risks of license violations on 5 of these 6 studied datasets if they were used for commercial purposes. Consequently, we provide recommendations for AI engineers on how to better assess publicly available datasets for license compliance violations.


Scientists sharing Omicron data were heroic. Let’s ensure they don’t regret it | Jeffrey Barrett | The Guardian

“The global scientific community has also carried out “genomic surveillance” – sequencing the genome of the virus to track how it evolves and spreads at an unprecedented level: the public genome database has more than 5.5m genomes. The great value of that genomic surveillance, underpinned by a commitment to rapid and open sharing of the data by all countries in near-real time, has been seen in the last few days as we’ve learned of the Covid variant called Omicron. 

The surveillance requires a remarkable amount of cooperation between scientists to build compatible laboratory protocols, software systems and databases. Many of these scientists are not directly paid for this work and do it in addition to their existing jobs. They are motivated by a belief that sharing data relevant to public health, especially in a pandemic, can help speed up scientific understanding, aid in decision-making and contribute to the next generation of medicines.

This commitment to rapid data sharing has deep roots in genomics. At a 1996 summit in Bermuda, the leaders of the Human Genome Project established a set of principles to release a new DNA sequence to public databases within 24 hours. This approach departed from the established convention that experimental data only needed to be released when a study was published, months or years later. Sir John Sulston, founding director of the Wellcome Sanger Institute, said: “All of this [genome data] should be in the public domain… I think we need a public social welfare attitude to the use of this information.”


That attitude now prevails around the world, as evidenced by the rapid sharing of more than 1m Sars-CoV-2 sequences by the Sanger Institute since March 2020….”

Will there be any transformation or are we stuck with the transformative agreements? | UKSG

“In Sweden there is a government directive to reach 100% immediate Open Access during 2021. We won´t reach it this year – but we have come far as we today can count approximately 75% immediate Open Access among corresponding authors affiliated to a Swedish university. As early adoptors of transformative agreements we are quite experienced having negotiated them for roughly five years. This has been a bumpy road along which we have cancelled agreements, made mistakes, gained knowledge and also have had some success in our negotiations. Today, through the Bibsam consortia, there are 21 transformative agreements and a handful of agreements with pure Open Access publishers in place. Many Swedish universities also have local agreements with smaller publishers and societies. During these years we have seen a cultural shift from the authors – some were initially somewhat skeptical to Open Access but are now able to embrace that their research results should be openly published. Through our different agreements we are near the goal of 100% immediate Open Access – but to reach this far has led to a high increase of costs. Another subject of discussion is how we divide the costs within the consortia when we move from paying for reading to paying for publishing – and as we calculate the cost based on publishing the research-intensive institutions have seen a substantial rise.

The Swedish universities are committed to reach the goal but we don´t find the transformative agreements sustainable for the future. When Plan S came up it stated that they should be temporary, and the recommendations were for a short transitional period in order for the publishers to find new ways and models to provide Open Access. According to the funders that have signed Plan S they will cease funding publishing within such agreements on the 31st of December 2024. As an early adoptor we also believe that the transition period should be over at the end of 2024. …”

How (not) to incentivise open research | The Bibliomagician

“Lizzie Gadd makes the case for open research being required not rewarded.

There’s no glory associated with running due diligence on your research partners and following GDPR legislation won’t give you an advantage in a promotion case. These are basic professional expectations placed on every self-respecting researcher. And whilst there are no prizes for those who adhere to them, there are serious consequences for those that don’t.  Surely this is what we want for open research? Not that it should be treated as an above-and-beyond option for the savvy few, but that it should be a bread-and-butter expectation on everyone.

Now I appreciate there is probably an interim period where institutions want to raise awareness of open research practices (as I said before, they need to be enabled before they can be incentivised).  And during this period, running some ‘Open Research Culture Awards’ or offering ‘Open research hero badges’ to web pages might have their place. But we can’t dwell here for long.  We need to move quite rapidly to this being a basic expectation on researchers. We have to define what open research expectations are relevant to each discipline. Add these expectations to our Codes of Good Research Practice. Train researchers in their obligations. Monitor (at discipline/HEI level) engagement with these expectations. And hold research leads accountable for the practices of their research groups.”