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Universalizing science: alternative indices to direct research

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Authors : Ari Melo Mariano, Maíra Rocha Santos

Measurement is a complicated but very necessary task. Many indices have been created in an effort to define the quality of knowledge produced but they have attracted strong criticism, having become synonymous with individualism, competition and mere productivity and, furthermore, they fail to head science towards addressing local demands or towards producing international knowledge by means of collaboration.

Institutions, countries, publishers, governments and authors have a latent need to create quality and productivity indices because they can serve as filters that influence far-reaching decision making and even decisions on the professional promotion of university teachers.

Even so, in the present-day context, the very creators of those indices admit that they were not designed for that purpose, given that different research areas, the age of the researcher, the country and the language spoken all have an influence on the index calculations.

Accordingly, this research sets out three indices designed to head science towards its universal objective by valuing collaboration and the dissemination of knowledge.

It is hoped that the proposed indices may provoke new discussions and the proposal of new, more assertive indicators for the analysis of scientific research quality.

URL : https://arxiv.org/abs/1807.07595

Health Sciences Libraries Advancing Collaborative Clinical Research Data Management in Universities

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Authors : Tania P. Bardyn, Emily F. Patridge, Michael T. Moore, Jane J. Koh

Purpose

Medical libraries need to actively review their service models and explore partnerships with other campus entities to provide better-coordinated clinical research management services to faculty and researchers. TRAIL (Translational Research and Information Lab), a five-partner initiative at the University of Washington (UW), explores how best to leverage existing expertise and space to deliver clinical research data management (CRDM) services and emerging technology support to clinical researchers at UW and collaborating institutions in the Pacific Northwest.

Methods

The initiative offers 14 services and a technology-enhanced innovation lab located in the Health Sciences Library (HSL) to support the University of Washington clinical and research enterprise.

Sharing of staff and resources merges library and non-library workflows, better coordinating data and innovation services to clinical researchers. Librarians have adopted new roles in CRDM, such as providing user support and training for UW’s Research Electronic Data Capture (REDCap) instance.

Results

TRAIL staff are quickly adapting to changing workflows and shared services, including teaching classes on tools used to manage clinical research data. Researcher interest in TRAIL has sparked new collaborative initiatives and service offerings. Marketing and promotion will be important for raising researchers’ awareness of available services.

Conclusions

Medical librarians are developing new skills by supporting and teaching CRDM. Clinical and data librarians better understand the information needs of clinical and translational researchers by being involved in the earlier stages of the research cycle and identifying technologies that can improve healthcare outcomes.

At health sciences libraries, leveraging existing resources and bringing services together is central to how university medical librarians will operate in the future.

DOI : https://doi.org/10.7191/jeslib.2018.1130

What Can a Knowledge Complexity Approach Reveal About Big Data and Archival Practice?

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Author : Nicola Horsley

As one of the major technological concepts driving ICT development today, big data has been touted as offering new forms of analysis of research data. Its application has reached out across disciplines but some research sources and archival practices do not sit comfortably within the computational turn and this has sparked concerns that cultural heritage collections that cannot be structured, represented, or, indeed, digitised accordingly may be excluded and marginalised by this new paradigm.

This work-in-progress paper reports on the contribution of the KPLEX project’s knowledge complexity approach to understanding the relationship between big data and archival practice.

URL : https://hal.archives-ouvertes.fr/hal-01831129

Clinical Trial Participants’ Views of the Risks and Benefits of Data Sharing

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Authors : Michelle M. Mello, Van Lieou, Steven N. Goodman

Background

Sharing of participant-level clinical trial data has potential benefits, but concerns about potential harms to research participants have led some pharmaceutical sponsors and investigators to urge caution. Little is known about clinical trial participants’ perceptions of the risks of data sharing.

Methods

We conducted a structured survey of 771 current and recent participants from a diverse sample of clinical trials at three academic medical centers in the United States. Surveys were distributed by mail (350 completed surveys) and in clinic waiting rooms (421 completed surveys) (overall response rate, 79%).

Results

Less than 8% of respondents felt that the potential negative consequences of data sharing outweighed the benefits. A total of 93% were very or somewhat likely to allow their own data to be shared with university scientists, and 82% were very or somewhat likely to share with scientists in for-profit companies.

Willingness to share data did not vary appreciably with the purpose for which the data would be used, with the exception that fewer participants were willing to share their data for use in litigation.

The respondents’ greatest concerns were that data sharing might make others less willing to enroll in clinical trials (37% very or somewhat concerned), that data would be used for marketing purposes (34%), or that data could be stolen (30%). Less concern was expressed about discrimination (22%) and exploitation of data for profit (20%).

Conclusions

In our study, few clinical trial participants had strong concerns about the risks of data sharing. Provided that adequate security safeguards were in place, most participants were willing to share their data for a wide range of uses. (Funded by the Greenwall Foundation.)

URL : https://www.nejm.org/doi/full/10.1056/NEJMsa1713258

Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

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Authors : John A. Borghi, Ana E. Van Gulick

Neuroimaging methods such as magnetic resonance imaging (MRI) involve complex data collection and analysis protocols, which necessitate the establishment of good research data management (RDM). Despite efforts within the field to address issues related to rigor and reproducibility, information about the RDM-related practices and perceptions of neuroimaging researchers remains largely anecdotal.

To inform such efforts, we conducted an online survey of active MRI researchers that covered a range of RDM-related topics. Survey questions addressed the type(s) of data collected, tools used for data storage, organization, and analysis, and the degree to which practices are defined and standardized within a research group.

Our results demonstrate that neuroimaging data is acquired in multifarious forms, transformed and analyzed using a wide variety of software tools, and that RDM practices and perceptions vary considerably both within and between research groups, with trainees reporting less consistency than faculty.

Ratings of the maturity of RDM practices from ad-hoc to refined were relatively high during the data collection and analysis phases of a project and significantly lower during the data sharing phase.

Perceptions of emerging practices including open access publishing and preregistration were largely positive, but demonstrated little adoption into current practice.

URL : Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

DOI : https://doi.org/10.1371/journal.pone.0200562

Unveiling Scholarly Communities over Knowledge Graphs

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Authors : Sahar Vahdati, Guillermo Palma, Rahul Jyoti Nath, Christoph Lange, Sören Auer, Maria-Esther Vidal

Knowledge graphs represent the meaning of properties of real-world entities and relationships among them in a natural way. Exploiting semantics encoded in knowledge graphs enables the implementation of knowledge-driven tasks such as semantic retrieval, query processing, and question answering, as well as solutions to knowledge discovery tasks including pattern discovery and link prediction.

In this paper, we tackle the problem of knowledge discovery in scholarly knowledge graphs, i.e., graphs that integrate scholarly data, and present Korona, a knowledge-driven framework able to unveil scholarly communities for the prediction of scholarly networks.

Korona implements a graph partition approach and relies on semantic similarity measures to determine relatedness between scholarly entities. As a proof of concept, we built a scholarly knowledge graph with data from researchers, conferences, and papers of the Semantic Web area, and apply Korona to uncover co-authorship networks.

Results observed from our empirical evaluation suggest that exploiting semantics in scholarly knowledge graphs enables the identification of previously unknown relations between researchers.

By extending the ontology, these observations can be generalized to other scholarly entities, e.g., articles or institutions, for the prediction of other scholarly patterns, e.g., co-citations or academic collaboration.

URL : https://arxiv.org/abs/1807.06816

Open Education Science

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Authors : Tim van der Zee, Justin Reich

Scientific progress is built on research that is reliable, accurate, and verifiable. The methods and evidentiary reasoning that underlie scientific claims must be available for scrutiny.

Like other fields, the education sciences suffer from problems such as failure to replicate, validity and generalization issues, publication bias, and high costs of access to publications—all of which are symptoms of a nontransparent approach to research. Each aspect of the scientific cycle—research design, data collection, analysis, and publication—can and should be made more transparent and accessible.

Open Education Science is a set of practices designed to increase the transparency of evidentiary reasoning and access to scientific research in a domain characterized by diverse disciplinary traditions and a commitment to impact in policy and practice.

Transparency and accessibility are functional imperatives that come with many benefits for the individual researcher, scientific community, and society at large—Open Education Science is the way forward.

URL : Open Education Science

Alternative location : http://journals.sagepub.com/doi/10.1177/2332858418787466