Étiquette : data reuse

Catégories
EN

Integrative data reuse at scientifically significant sites: Case studies at Yellowstone National Park and the La Brea Tar Pits

Author : Andrea K. Thomer

Scientifically significant sites are the source of, and long-term repository for, considerable amounts of data—particularly in the natural sciences. However, the unique data practices of the researchers and resource managers at these sites have been relatively understudied.

Through case studies of two scientifically significant sites (the hot springs at Yellowstone National Park and the fossil deposits at the La Brea Tar Pits), I developed rich descriptions of site-based research and data curation, and high-level data models of information classes needed to support integrative data reuse.

Each framework treats the geospatial site and its changing natural characteristics as a distinct class of information; more commonly considered information classes such as observational and sampling data, and project metadata, are defined in relation to the site itself.

This work contributes (a) case studies of the values and data needs for researchers and resource managers at scientifically significant sites, (b) an information framework to support integrative reuse at these sites, and (c) a discussion of data practices at scientifically significant sites.

URL : Integrative data reuse at scientifically significant sites: Case studies at Yellowstone National Park and the La Brea Tar Pits

DOI : https://doi.org/10.1002/asi.24620

Catégories
EN

An overview of biomedical platforms for managing research data

Authors : Vivek Navale, Denis von Kaeppler, Matthew McAuliffe

Biomedical platforms provide the hardware and software to securely ingest, process, validate, curate, store, and share data. Many large-scale biomedical platforms use secure cloud computing technology for analyzing, integrating, and storing phenotypic, clinical, and genomic data. Several web-based platforms are available for researchers to access services and tools for biomedical research.

The use of bio-containers can facilitate the integration of bioinformatics software with various data analysis pipelines. Adoption of Common Data Models, Common Data Elements, and Ontologies can increase the likelihood of data reuse. Managing biomedical Big Data will require the development of strategies that can efficiently leverage public cloud computing resources.

The use of the research community developed standards for data collection can foster the development of machine learning methods for data processing and analysis. Increasingly platforms will need to support the integration of data from multiple disease area research.

URL : An overview of biomedical platforms for managing research data

DOI : https://doi.org/10.1007/s42488-020-00040-0

Catégories
EN

Evaluation of Data Sharing After Implementation of the International Committee of Medical Journal Editors Data Sharing Statement Requirement

Authors : Valentin Danchev, Yan Min, John Borghi, Mike Baiocchi, John P. A. Ioann

Importance

The benefits of responsible sharing of individual-participant data (IPD) from clinical studies are well recognized, but stakeholders often disagree on how to align those benefits with privacy risks, costs, and incentives for clinical trialists and sponsors.

The International Committee of Medical Journal Editors (ICMJE) required a data sharing statement (DSS) from submissions reporting clinical trials effective July 1, 2018. The required DSSs provide a window into current data sharing rates, practices, and norms among trialists and sponsors.

Objective

To evaluate the implementation of the ICMJE DSS requirement in 3 leading medical journals: JAMA, Lancet, and New England Journal of Medicine (NEJM).

Design, Setting, and Participants

This is a cross-sectional study of clinical trial reports published as articles in JAMA, Lancet, and NEJM between July 1, 2018, and April 4, 2020. Articles not eligible for DSS, including observational studies and letters or correspondence, were excluded.

A MEDLINE/PubMed search identified 487 eligible clinical trials in JAMA (112 trials), Lancet (147 trials), and NEJM (228 trials). Two reviewers evaluated each of the 487 articles independently.

Exposure

Publication of clinical trial reports in an ICMJE medical journal requiring a DSS.

Main Outcomes and Measures

The primary outcomes of the study were declared data availability and actual data availability in repositories. Other captured outcomes were data type, access, and conditions and reasons for data availability or unavailability. Associations with funding sources were examined.

Results

A total of 334 of 487 articles (68.6%; 95% CI, 64%-73%) declared data sharing, with nonindustry NIH-funded trials exhibiting the highest rates of declared data sharing (89%; 95% CI, 80%-98%) and industry-funded trials the lowest (61%; 95% CI, 54%-68%).

However, only 2 IPD sets (0.6%; 95% CI, 0.0%-1.5%) were actually deidentified and publicly available as of April 10, 2020. The remaining were supposedly accessible via request to authors (143 of 334 articles [42.8%]), repository (89 of 334 articles [26.6%]), and company (78 of 334 articles [23.4%]).

Among the 89 articles declaring that IPD would be stored in repositories, only 17 (19.1%) deposited data, mostly because of embargo and regulatory approval. Embargo was set in 47.3% of data-sharing articles (158 of 334), and in half of them the period exceeded 1 year or was unspecified.

Conclusions and Relevance

Most trials published in JAMA, Lancet, and NEJM after the implementation of the ICMJE policy declared their intent to make clinical data available. However, a wide gap between declared and actual data sharing exists.

To improve transparency and data reuse, journals should promote the use of unique pointers to data set location and standardized choices for embargo periods and access requirements.

URL : Evaluation of Data Sharing After Implementation of the International Committee of Medical Journal Editors Data Sharing Statement Requirement

DOI :10.1001/jamanetworkopen.2020.33972

Catégories
EN

Improving Opportunities for New Value of Open Data: Assessing and Certifying Research Data Repositories

Author : Robert R. Downs

Investments in research that produce scientific and scholarly data can be leveraged by enabling the resulting research data products and services to be used by broader communities and for new purposes, extending reuse beyond the initial users and purposes for which the data were originally collected.

Submitting research data to a data repository offers opportunities for the data to be used in the future, providing ways for new benefits to be realized from data reuse. Improvements to data repositories that facilitate new uses of data increase the potential for data reuse and for gains in the value of open data products and services that are associated with such reuse.

Assessing and certifying the capabilities and services offered by data repositories provides opportunities for improving the repositories and for realizing the value to be attained from new uses of data.

The evolution of data repository certification instruments is described and discussed in terms of the implications for the curation and continuing use of research data.

URL : Improving Opportunities for New Value of Open Data: Assessing and Certifying Research Data Repositories

DOI : http://doi.org/10.5334/dsj-2021-001

Catégories
EN

Research Data Management Status of Science and Technology Research Institutes in Korea

Authors : Myung-seok Choi, Sanghwan Lee

Recent advances in digital technology and the data-driven science paradigm has led to a proliferation of research data, which are becoming more important in scholarly communications.

The sharing and reuse of research data can play a key role in enhancing the reusability and reproducibility of research, and data from publicly funded projects are assumed to be public goods. This is seen as a movement of open science and, more specifically, open research data.

Many countries, such as the USA, UK, and Australia, are pushing ahead with implementing policies and infrastructure for open research data. In this paper, we present survey results pertaining to the creation, management, and utilization of data for researchers from government-funded research institutes of science and technology in Korea.

We then introduce recent regulations stipulating a mandated data management plan for national R&D projects and on-going efforts to realize open research data in Korea.

URL : Research Data Management Status of Science and Technology Research Institutes in Korea

DOI : http://doi.org/10.5334/dsj-2020-029

Catégories
EN

Research Data Management as an Integral Part of the Research Process of Empirical Disciplines Using Landscape Ecology as an Example

Authors : Winfried Schröder, Stefan Nickel

Research Data Management (RDM) is regarded as an elementary component of empirical disciplines. Taking Landscape Ecology in Germany as an example the article demonstrates how to integrate RDM into the research design as a complement of the classic quality control and assurance in empirical research that has, so far, generally been limited to data production.

Sharing and reuse of empirical data by scientists as well as thorough peer reviews of knowledge produced by empirical research requires that the problem of the research in question, the operationalized definitions of the objects of investigation and their representative selection are documented and archived as well as the methods of data production including indicators for data quality and all data collected and produced.

On this basis, the extent to which this complemented design of research processes has already been realized is demonstrated by research projects of the Chair of Landscape Ecology at the University of Vechta, Germany.

This study is part of a joined research project on Research Data Management funded by the German Federal Ministry of Education and Research.

URL : Research Data Management as an Integral Part of the Research Process of Empirical Disciplines Using Landscape Ecology as an Example

DOI : http://doi.org/10.5334/dsj-2020-026

Catégories
Non classé

Alter-Value in Data Reuse: Non-Designated Communities and Creative Processes

Author : Guillaume Boutard

This paper builds on the investigation of data reuse in creative processes to discuss ‘epistemic pluralism’ and data ‘alter-value’ in research data management. Focussing on a specific non-designated community, we conducted semi-structured interviews with five artists in relation to five works.

Data reuse is a critical component of all these works. The qualitative content analysis brings to light agonistic-antagonistic practices in data reuse and shows multiple deconstructions of the notion of data value as it is portrayed in the data reuse literature.

Finally, the paper brings to light the benefits of including such practices in the conceptualization of data curation.

URL : Alter-Value in Data Reuse: Non-Designated Communities and Creative Processes

DOI : http://doi.org/10.5334/dsj-2020-023