The research data life cycle, legacy data, and dilemmas in research data management

Authors : Jenny Bossaller, Anthony J. Million

This paper presents findings from an interview study of research data managers in academic data archives. Our study examined policies and professional autonomy with a focus on dilemmas encountered in everyday work by data managers.

We found that dilemmas arose at every stage of the research data lifecycle, and legacy data presents particularly vexing challenges. The iFields’ emphasis on knowledge organization and representation provides insight into how data, used by scientists, are used to create knowledge.

The iFields’ disciplinary emphasis also encompasses the sociotechnical complexity of dilemmas that we found arise in research data management. Therefore, we posit that iSchools are positioned to contribute to data science education by teaching about ethics and infrastructure used to collect, organize, and disseminate data through problem-based learning.

URL : The research data life cycle, legacy data, and dilemmas in research data management


Facilitating and Improving Environmental Research Data Repository Interoperability

Authors : Corinna Gries, Amber Budden, Christine Laney, Margaret O’Brien, Mark Servilla, Wade Sheldon, Kristin Vanderbilt, David Vieglais

Environmental research data repositories provide much needed services for data preservation and data dissemination to diverse communities with domain specific or programmatic data needs and standards.

Due to independent development these repositories serve their communities well, but were developed with different technologies, data models and using different ontologies. Hence, the effectiveness and efficiency of these services can be vastly improved if repositories work together adhering to a shared community platform that focuses on the implementation of agreed upon standards and best practices for curation and dissemination of data.

Such a community platform drives forward the convergence of technologies and practices that will advance cross-domain interoperability. It will also facilitate contributions from investigators through standardized and streamlined workflows and provide increased visibility for the role of data managers and the curation services provided by data repositories, beyond preservation infrastructure.

Ten specific suggestions for such standardizations are outlined without any suggestions for priority or technical implementation. Although the recommendations are for repositories to implement, they have been chosen specifically with the data provider/data curator and synthesis scientist in mind.

URL : Facilitating and Improving Environmental Research Data Repository Interoperability


IISH Guidelines for preserving research …

IISH Guidelines for preserving research data: a framework for preserving collaborative data collections for future research :

“Our guidelines highlight the iterative process of data collection, data processing, data analysis and publication of (interim) research results. The iterative process is best analyzed and illustrated by following the dynamics of data collection in online collaboratories. The production of data sets in such large scale data collection projects, typically takes a lot of time, whilst in the meantime research may already be performed on data sub-sets. If this leads to a publication a proper citation is required. Publishers and readers need to know exactly in what stage of the data collection process specific conclusions on these data were drawn. During this iterative process, research data need to be maintained, managed and disseminated in different forms and versions during the successive stages of the work carried out, in order to validate the outcomes and research results. These practices drive the requirements for data archiving and show that data archiving is not a once off data transfer transaction or even a linear process. Therefore from the perspective of the research process, we recommend the interconnection and interfacing between data collection and data archiving, in order to ensure the most effective and loss-less preservation of the research data.”