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While molecular visualization has been recognized as a threshold concept in biology education, the explicit assessment of students' visual literacy skills is rare. To facilitate the evaluation of this fundamental ability, a series of NSF-IUSE-sponsored workshops brought together a community of faculty engaged in creating instruments to assess students' biomolecular visualization skills. These efforts expanded our earlier work in which we created a rubric describing overarching themes, learning goals, and learning objectives that address student progress toward biomolecular visual literacy. Here, the BioMolViz Steering Committee (BioMolViz.org) documents the results of those workshops and uses social network analysis to examine the growth of a community of practice. We also share many of the lessons we learned as our workshops evolved, as they may be instructive to other members of the scientific community as they organize workshops of their own.

Our climate is changing due to anthropogenic emissions of greenhouse gases from the production and use of fossil fuels. Present atmospheric levels of CO2 were last seen 3 million years ago, when planetary temperature sustained high Arctic camels. As scientists and educators, we should feel a professional responsibility to discuss major scientific issues like climate change, and its profound consequences for humanity, with students who look up to us for knowledge and leadership, and who will be most affected in the future. We offer simple to complex backgrounds and examples to enable and encourage biochemistry educators to routinely incorporate this most important topic into their classrooms.

Over the past decade, megajournals have expanded in popularity and established a legitimate niche in academic publishing. Leveraging advantages of digital publishing, megajournals are characterized by large publication volume, broad interdisciplinary scope, and peer review filters that select primarily on scientific soundness as opposed to novelty or originality. These publishing innovations are complementary and/or competitive vis-à-vis traditional journals. We analyze how megajournals (PLOS ONE, Scientific Reports) are represented in different fields relative to prominent generalist journals (Nature, PNAS, Science) and ‘quasi-megajournals’ (Nature Communications, PeerJ). Our results show that both megajournals and prominent traditional journals have distinctive niches, despite the similar interdisciplinary scopes of such journals. These niches – defined by publishing volume and disciplinary diversity – are dynamic and varied over the relatively brief histories of the analyzed megajournals. Although the life sciences are the predominant contributor to megajournals, there is variation in the disciplinary composition of different megajournals. The growth trajectories and disciplinary composition of generalist journals – including megajournals – reflect changing knowledge dissemination and reward structures in science.

Social media has become integrated into the fabric of the scholarly communication system in fundamental ways: principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics -- that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of two main parts: the first examines the use of social media in academia, examining the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system., preprint, submitted to JASIST

In 2015, Public Administration Review celebrated its 75th year of publication. For this milestone, the PAR Editorial Board selected the 75 most influential articles in the history of the journal and invited scholars to “revisit a selection of these articles” in order “to take stock of what these articles meant for the field.” Bibliometrics offers a complementary view of the history of a discipline and the evolution of its research and practice agendas through an analysis of its published literature. This article examines the changes over time in PAR from 1940 through 2013 in authorship: contributions, impact, gender composition, institutional and national affiliation, profession as scholar or practitioner, collaboration networks, and the status of the 75 influential articles. Through an extensive quantitative analysis of scholarly production, this article demonstrates PAR’s centrality to the discipline of public administration and its bridging role between public administration and political science.

Recognizing that undergraduate students can benefit from analysis of 3D protein structure and function, we have developed a multiweek, inquiry-based molecular visualization project for Biochemistry I students. This project uses a virtual model of cyclooxygenase-1 (COX-1) to guide students through multiple levels of protein structure analysis. The first assignment explores primary structure by generating and examining a protein sequence alignment. Subsequent assignments introduce 3D visualization software to explore secondary, tertiary, and quaternary structure. Students design an inhibitor, based on scrutiny of the enzyme active site, and evaluate the fit of the molecule using computed binding energies. In the last assignment, students introduce a point mutation to model the active site of the related COX-2 enzyme and analyze the impact of the mutation on inhibitor binding. With this project we aim to increase knowledge about, and confidence in using, online databases and computational tools. Here, we share results of our mixed methods pre- and postsurvey demonstrating student gains in knowledge about, and confidence using, online databases and computational tools. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):318–328, 2017.

Biochemistry students misconceptions related to enzyme-substrate interactions can stem from prior knowledge in biology and chemistry where this and related concepts are inadequately represented vis...

Biochemistry students experience extraneous cognitive load when presented with distracting information while learning a new task. Consequently, the students struggle to create and store connections...

Research has shown students have significant difficulty understanding enzyme-substrate relationships. One way instructors have suggested to support students while learning this content is through t...

Understanding “Structure and Function” relationships is foundational to learning biology, chemistry, and biochemistry. However, exploring and using biochemical data resources, especially the Protei...

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific articles deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics altmetrics, where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. Our results show that automated Twitter accounts create a considerable amount of tweets to scientific articles and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose distinguishing between different levels of engagement-that is, differentiating between tweeting only bibliographic information to discussing or commenting on the content of a scientific work.

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain-specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention-autonomy, opacity, generativity, disparity, and futurity-leading to questions and ideas for moving beyond dilemmas.

Calls for interdisciplinary collaboration have become increasingly common in the face of large-scale complex problems (including climate change, economic inequality, and education, among others); however, outcomes of such collaborations have been mixed, due, among other things, to the so-called “translation problem” in interdisciplinary research. This article presents a potential solution: an empirical approach to quantitatively measure both the degree and nature of differences among disciplinary tongues through the social and epistemic terms used (a research area we refer to as discourse epistemetrics), in a case study comparing dissertations in philosophy, psychology, and physics. Using a support-vector model of machine learning to classify disciplines based on relative frequencies of social and epistemic terms, we were able to markedly improve accuracy over a random selection baseline (distinguishing between disciplines with as high as 90% accuracy) as well as acquire sets of most indicative terms for each discipline by their relative presence or absence. These lists were then considered in light of findings of sociological and epistemological studies of disciplines and found to validate the approach's measure of social and epistemic disciplinary identities and contrasts. Based on the findings of our study, we conclude by considering the beneficiaries of research in this area, including bibliometricians, students, and science policy makers, among others, as well as laying out a research program that expands the number of disciplines, considers shifts in socio-epistemic identities over time and applies these methods to nonacademic epistemological communities (e.g., political groups).

It is well known that a number of research outcomes are not reported (the so-called ‘file drawer problem’). It is generally assumed that what is not reported are ‘negative results’. Our study approaches the issue from a new angle by exploring what researchers perceive to be ‘unpublishable’. A survey regarding ‘unpublishables’ was sent out to 2,535 faculty members at Indiana University. Forty of these individuals consented to in-depth interviews, which more fully explored these academics' views on the issue of unpublishable work. Our results indicate that there are several types of research besides negative results that are perceived to be unpublishable yet worthy of publication. Moreover, there is a great diversity within and across disciplines as to what constitutes ‘unpublishable’ research. Respondents indicated that academic discourse would benefit from the formal dissemination of papers that included inconclusive or null results, as well as replication and refutation studies. The results of our study suggest that there is a perceived gap in scholarly communication, which is to the detriment of science. These results can be used by administrators, educators, and publishers in order to refine scholarly communication practices so as to create a more robust, accurate literature and to inform future generations of researchers.

Since its creation in 1991, arXiv has become central to the diffusion of research in a number of fields. Combining data from the entirety of arXiv and the Web of Science (WoS), this paper investigates (a) the proportion of papers across all disciplines that are on arXiv and the proportion of arXiv papers that are in the WoS, (b) elapsed time between arXiv submission and journal publication, and (c) the aging characteristics and scientific impact of arXiv e-prints and their published version. It shows that the proportion of WoS papers found on arXiv varies across the specialties of physics and mathematics, and that only a few specialties make extensive use of the repository. Elapsed time between arXiv submission and journal publication has shortened but remains longer in mathematics than in physics. In physics, mathematics, as well as in astronomy and astrophysics, arXiv versions are cited more promptly and decay faster than WoS papers. The arXiv versions of papers - both published and unpublished - have lower citation rates than published papers, although there is almost no difference in the impact of the arXiv versions of both published and unpublished papers.