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Open access to scientific publications is in this study looked at from the perspective of Finnish biomedical research. In the study we outline the development of open access in Finland and the different channels for open access publishing as well as the recommendations from officials. We argue that the discipline-specific patterns of communicating research should be taken into account when studying open access adoption, and when planning for initiatives and recommendations. We have in the case study on the prevalence of open access articles on the Internet, in the field of biomedical research, found that incentives to publish in open access channels could be developed and that the impact of open access in research publishing is growing and therefore future research is needed.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

Xavier University of Louisiana has a national reputation for producing science, technology, engineering, and mathematics (STEM) graduates who go on to obtain MD and PhD degrees. According to a 2013 National Science Foundation report, Xavier is ranked first in producing African American graduates who go on to receive life sciences PhD degrees, fifth in the nation in producing African American graduates who go on to receive science and engineering PhD degrees, and seventh in producing African American graduates who go on to receive physical sciences PhD degrees. Xavier is currently third among the nation’s colleges and universities in the number of African American graduates enrolled in medical school, according to data compiled by the Association of American Medical Colleges, and ranked first in the number of African American alumni who successfully complete their medical degrees. The success of Xavier’s graduates is due to a combination of university-based student support initiatives and externally funded programs, in particular, the Building Infrastructure Leading to Diversity (BUILD), Maximizing Access to Biomedical Research Careers (MARC) U*STAR, and Research Initiative in Scientific Enhancement (RISE) programs. These three programs, funded by the Training, Workforce Development, and Diversity (TWD) Division at the National Institutes of Health (NIH), offer select trainees undergraduate research opportunities, support mechanisms, and a variety of activities designed to improve their potential for success in graduate school. The BUILD, MARC U*STAR, and RISE programs work closely together and with the University to leverage the resources provided by each in order to provide the best experience possible for their students with a minimum of redundancy of effort. This chapter focuses on the program components and how the programs work together.

Theories of platform strategy and adoption have been largely derived from studies of their application in the information and communications technology (ICT) sector. These platforms vary in openness, with the model of open source software providing the best-known exemplar for open platforms.

This exploratory field study examines the degree to which nine attributes of ICT platforms are applicable to open platforms in biotechnology. Using a combination of interview and secondary data, it identifies three patterns of such biotechnology platforms – IP commons, hackerspaces, and crowdsourced patient registries – and the degree to which these nine attributes apply. It shows the impact of ICT platforms and open source software on open source approaches to biotechnology, and how the latter are affected by the technical, legal, and institutional differences between information technology and biotechnology.

Instead of open source software platforms organized around modular interfaces, complements, ecosystems, and two-sided markets, this study instead suggests a model of open source knowledge platforms which benefits from economies of scale but not indirect network effects. From this, it discusses the generalizability of the ICT-derived models of open source platforms and offers suggestions for future research.

Big Data analysis is one of the key challenges to the provision of health care to emerge in the last few years. This challenge has been spearheaded by the huge interest in the “4Ps” of health care (predictive, preventive, personalized, and participatory). Big Data offers striking development opportunities in health care and life sciences. Healthcare research is already using Big Data to analyze the spatial distribution of diseases such as diabetes mellitus at detailed geographic levels. Big Data is also being used to assess location-specific risk factors based on data of health insurance claims. Other studies in systems medicine utilize bioinformatics approaches to human biology which necessitate Big Data statistical analysis and medical informatics tools. Big Data is also being used to develop electronic algorithms to forecast clinical events in real time, with the intent to improve patient outcomes and thus reduce costs.

Yet, this Big Data era also poses critically difficult ethical challenges, since it is breaking down the traditional divisions between what belongs to public and private domains in health care and health research. Big Data in health care raises complex ethical concerns due to use of huge datasets obtained from different sources for varying reasons. The clinical translation of this Big Data is thus resulting in key ethical and epistemological challenges for those who use these data to generate new knowledge and the clinicians who eventually apply it to improve patient care.

Underlying this challenge is the fact that patient consent often cannot be collected for the use of individuals’ personal data which then forms part of this Big Data. There is also the added dichotomy of healthcare providers which use such Big Data in attempts to reduce healthcare costs, and the negative impact this may have on the individual with respect to privacy issues and potential discrimination.

Big Data thus challenges societal norms of privacy and consent. Many questions are being raised on how these huge masses of data can be managed into valuable information and meaningful knowledge, while still maintaining ethical norms. Maintaining ethical integrity may lack behind in such a fast-changing sphere of knowledge. There is also an urgent need for international cooperation and standards when considering the ethical implications of the use of Big Data-intensive information.

This chapter will consider some of the main ethical aspects of this fast-developing field in the provision of health care, health research, and public health. It will use examples to concretize the discussion, such as the ethical aspects of the applications of Big Data obtained from clinical trials, and the use of Big Data obtained from the increasing popularity of health mobile apps and social media sites.

Peer-reviewed indexable journals have expanded in recent decades as a result, in part, of the value given to research productivity (measured through citations). Latin American journals have grown prompted by the open access (OA) movement, the emergence of regional repositories/indexes, and policies linking institutional rankings and faculty salaries/promotions to indexed publications. This study’s aim was to map the ways Chilean, Colombian, and Venezuelan universities support journal publication. This qualitative study uses Margison and Rhoades’ (2002) Glonacal Agency Heuristic to describe factors that shape higher education (i.e., global, national, and local dimensions), adding university as unit of analysis. Semi-structured in-depth interviews from a previous study, current institutional documents, and websites of 12 major universities from Chile, Venezuela, and Colombia conformed the data of the study. Besides the most prestigious global indexes (Web of Science and Scopus) three regional repositories/indexes, Latindex, SciELO, and RedALyC, have played an important role as countries link faculty salaries/promotions and university ranking systems to publications included in one or more of these services. Latindex collaborates with national science and technology agencies, SciELO has country chapters based at universities (Colombia and Venezuela), and RedALyC works with individual institutions and journals. At the national level, Chile has mechanisms to provide funding for the publication and/or upgrade of journals and incentives to institutions for publications in indexed journals. Colombia’s journal evaluation system Publindex links articles in indexed journals to salary increases in public universities, standard that is also used by private institutions to grant monetary incentives to faculty for publications. Venezuela used to have a funding and publication incentive system that was discontinued in the last decade. Latin American journals are mainly published by universities. Institutions in this study have implemented strategies to support journals such as institutional repositories, discontinuation of print journals, technology support for OA publication, and funding mechanisms.

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social media in research. There is also excellent work on challenges of postpublication sharing of social media, primarily focused on legal restrictions, technical infrastructure, and documentation. This chapter attempts to build upon and extend this work by using cases to deepen the analysis of ethical issues arising from publishing and sharing social media data. Publishing will refer to the presentation of data extracts, aggregations, or summaries, while sharing refers to the practice of making the underlying data available postpublication for others to use. It will look at the ethical questions that arise both for researchers (or others) sharing data, and those who are using data that has been made available by others, emphasizing the inherently relational nature of data sharing. The ethical challenges researchers face when considering sharing user-generated content collected from social media platforms are the focus of the cases. The chapter begins by summarizing the general principles of research ethics, then identifies the specific ethical challenges from sharing social media data and positions these challenges in the context of these general principles. These challenges are then analyzed in more detail with cases from research projects that drew upon several different genres of social media. The chapter concludes with some recommendations for practical guidance and considers the future of ethical practice in sharing social media data.

This chapter explores the interaction between different kinds of knowledge and representations in the making of the ‘fleshed’ female reproductive body in an Indian city. In particular, it analyzes how women perceive contraception and how the reproductive governance helped to produce the female sterilization as the most widely used contraceptive method in India. The study is based on the case of the city of Bhuj, in the state of Gujarat (India), where three anthropological fieldworks (15 months) were conducted. Modern contraceptive methods are based on a biomedical representation of the body, drawn from Western categories of knowledge and experience, whereas women live the ‘fleshed’ reproductive body through local categories of substance and fluids. How is this knowledge mobilized and affected in relation to reproductive technologies and the government of reproduction? This question is addressed through the analysis of women's embodied experiences of contraception. The narratives collected show a resistance to biomedicine, considered to be a model that alters the female body and its reproductive capacity. Nevertheless, even when sterilization was considered to be a deliberate act of tampering with the functioning of their bodies, women displayed a pragmatic agency in choosing this method. The experiences of respondents reflected complex negotiations between bodily suffering, socio-economic structures and the microphysics of power surrounding them, rather than a unilateral submission to medical authority and reproductive governance.