The Experts below are selected from a list of 14211 Experts worldwide ranked by ideXlab platform
Marta Teperek - One of the best experts on this subject based on the ideXlab platform.
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On a Quest for Cultural Change - Surveying Research Data Management Practices at Delft University of Technology
LIBER Quarterly, 2019Co-Authors: Heather Andrews Mancilla, Marta Teperek, Yasemin Turkyilmaz-van Der Velden, Jasper Van Dijck, Kees Den Heijer, Robbert Eggermont, Esther Plomp, Shalini KurapatiAbstract:The Data Stewardship project is a new initiative from the Delft University of Technology (TU Delft) in the Netherlands. Its aim is to create mature working practices and policies regarding research Data management across all TU Delft faculties. The novelty of this project relies on having a dedicated person, the so-called ‘Data Steward’, embedded in each faculty to approach research Data management from a more discipline-specific perspective. It is within this framework that a research Data management survey was carried out at the faculties that had a Data Steward in place by July 2018. The goal was to get an overview of the general Data management practices, and use its results as a benchmark for the project. The total response rate was 11 to 37% depending on the faculty. Overall, the results show similar trends in all faculties, and indicate lack of awareness regarding different Data management topics such as automatic Data backups, Data ownership, relevance of Data management plans, awareness of FAIR Data principles and usage of research Data repositories. The results also show great interest towards Data management, as more than ~80% of the respondents in each faculty claimed to be interested in Data management training and wished to see the summary of survey results. Thus, the survey helped identified the topics the Data Stewardship project is currently focusing on, by carrying out awareness campaigns and providing training at both university and faculty levels.
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Data Roles of the Future at TU Delft
2019Co-Authors: Alastair Dunning, Marta TeperekAbstract:This Dataset is cited in the LCRDM task group Data Stewardship report, DOI 10.5281/zenodo.2642066 (April 2019).
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Data Stewardship addressing disciplinary Data management needs
International Journal of Digital Curation, 2018Co-Authors: Marta Teperek, Maria J. Cruz, Ellen Verbakel, Jasmin Böhmer, Alastair DunningAbstract:One of the biggest challenges for multidisciplinary research institutions which provide Data management support to researchers is addressing disciplinary differences (Akers and Doty,2013). Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address Data management needs across a multi-disciplinary campus. In this article we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, identify the key challenges and explain our plans for the future.
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Views on Data Stewardship - report of preliminary findings at the Faculty of Technology, Policy and Management (TPM) at TU Delft
2018Co-Authors: Marta TeperekAbstract:Qualitative interviews with nine researchers at the Faculty of Technology, Policy and Management (TPM) at TU Delft were undertaken in order to get an understanding of Data management needs at the faculty in advance of appointing a dedicated Data Steward. The purpose of this was to aid the recruitment of the Data Steward and to define the skills and experience of an ideal candidate, as well as help deciding on the work priority areas for the Data Steward. The results of this research can be also used as a point in time reference to monitor changes in Data management practice at the faculty.The main Data management challenges identified were: handling personal sensitive research Data; working with big Data, managing and sharing commercially confidential information and software management issues. Despite the diversity of problems, some common issues were identified as well: need for improving daily Data management practice, as well as the need for revising workflows for students’ research Data. With the exception of one researcher, who was in opposition to the Data Stewardship project, all other researchers expressed their support for the project and welcomed the idea of having a dedicated Data Steward at the faculty.Additionally, several follow up actions were already undertaken as a follow up of these interviews: the Data Stewardship Coordinator was invited to give two talks about Data Stewardship to two different groups of researchers;a member of the Research Data Support from the Library team was asked to deliver a training course for students;the Data Stewardship Coordinator was asked to discuss the best way of rolling our Data management training for PhD students at TPM in coordination with the TPM Graduate School.Given that the financial allocation for the Data Steward at TPM faculty is currently at 0,5 FTE for the first year and 1,0 FTE for the two subsequent years (until December 2020), it is recommended that the first year is spent on continuing and extending this research to better understand the needs of the faculty. It is suggested that at the same time, the Data Steward starts addressing the most urgent Data management needs at TPM faculty, in particular the development of a Data management policy, as well as the development of solutions and recommendations for working with personal sensitive research Data.The two subsequent years could be devoted to developing resources and solutions for the remaining problems and for critical evaluation of the project and its effect on Data management practice at the faculty. This approach should provide the faculty with enough resources and information to decide on the best strategy for Data Stewardship beyond December 2020.
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Data Stewardship – addressing disciplinary Data management needs
2018Co-Authors: Marta Teperek, Maria J. Cruz, Ellen Verbakel, Jasmin K. Böhmer, Alastair DunningAbstract:One of the biggest challenges for multidisciplinary research institutions which provide Data management support to researchers is addressing disciplinary differences1. Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address Data management needs across a multi-disciplinary campus. In this practice paper, we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, we identify the key challenges and explain our plans for the future.
Carly Strasser - One of the best experts on this subject based on the ideXlab platform.
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Recommendations for the role of publishers in access to Data.
PLoS biology, 2014Co-Authors: Jennifer Lin, Carly StrasserAbstract:As appeals for public access of research Data continue to proliferate, many scholarly publishers-alongside funders, institutions, and libraries-are expanding their role to address this need. Here we outline eight recommendations and a set of suggested action items for publishers to promote and contribute to increasing access to Data. This call to action emerged from a summit that brought together Data Stewardship leaders across stakeholder groups. The recommendations were subsequently refined by the community as a result of public input gathered online and in meetings.
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Spatially explicit Data: Stewardship and ethical challenges in science.
PLoS biology, 2013Co-Authors: Joel Hartter, Sadie J. Ryan, Catrina A. Mackenzie, John N. Parker, Carly StrasserAbstract:Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of Data Stewardship and Data sharing. Formal Data management plans represent a new emphasis in research, enabling access to Data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific Data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, Stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration.
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Dataup enabling Data Stewardship for researchers
2013Co-Authors: Carly StrasserAbstract:The move towards digital Data is ubiquitous across all domains in academic research (Interagency Working Group on Digital Data, 2009; Carlson, 2006; C. L. Borgman, 2009; Faniel & Zimmerman, 2011; C. L. Borgman, 2008), and these Data can be made available and distributed more quickly than ever before. This is often called the Data deluge, and is a phenomenon that has been explored in the traditional academic literature (Carlson, 2006; Faniel & Zimmerman, 2011; C. Borgman, Wallis, & Enyedy, 2007), as well as in several major media outlets (Editors, 2010; Pollack, 2011; G Bell, 2009). Among the most pressing problems associated with the Data deluge is good Data management: how does one handle the huge volume of available information effectively and efficiently to solve important problems? Knowledge of good Data management techniques and software development lags behind the progression of the Data deluge. Consequently, although researchers of all fields are faced with huge volumes of Data from increasingly diverse sources, they do not have the skills to handle their Data sets. This challenge is amplified by the fact that research Data are seldom shared, re-used, or preserved (Nelson, 2009; Tenopir et al., 2011; LeClere, 2010). There is a growing awareness among practitioners and funders that this situation represents inefficient use of research dollars, missed opportunities to exploit prior investment, and a general loss for the scholarly community (Editors, 2009). Michener, Brunt, Helly, Kirchner, and Stafford (1997) described the loss of valuable Data and insight about those Datasets as “information entropy”. This loss of information is becoming increasingly worrisome as Data management practices improve very slowly, while the volume of Data grows exponentially. Recognizing that most Earth, environmental, and ecological scientists use spreadsheets at some point in the life cycles of their Data, the California Digital Library partnered with Microsoft Research Connections and the Gordon and Betty Moore Foundation to create a tool for Microsoft Excel that would encourage and enable good Data Stewardship practices. To optimize the tool, we first identified the needs of the community via surveys of researchers. We found that, on average, researchers had poor Data management practices, were not aware of Data centers or metaData standards, and did not understand the benefits of Data management or sharing. We used the survey results to compose a list of desirable components and solicited feedback from the community to prioritize potential features. The result of this effort was a document outlining the requirements for DataUp; these requirements were made publicly available for comment on the DataUp blog, and were provided to developers who then created the DataUp software. The resulting DataUp tool (Dataup.cdlib.org) facilitates documenting, managing, and archiving tabular scientific Data. It comes in two forms, both open-source: an add-in for Excel and a web-based application. The add-in operates within the well-known program, Excel; the web application allows users to upload tabular Data to the web-based tool in either Excel format or comma-separated value (CSV) format. Both the add-in and the web application provide users with the ability to (1) Perform a “best practices check” to ensure Data are well formatted and organized; (2) Create standardized metaData, or a description of the Data, using a wizard-style template; (3) Retrieve a unique identifier for their Dataset from their Data repository, and (4) Post their Datasets and associated metaData to the repository. ________________________________________ Acknowledgments: Microsoft Research Connections and the Gordon and Betty Moore Foundation provided funding for this work. Strasser, C. (2013). DataUp: Enabling Data Stewardship for researchers. IConference 2013 Proceedings (pp. 657-658). doi:10.9776/13300 Copyright is held by the author/owner(s). iConference 2013 February 12-15, 2013 Fort Worth, TX, USA 658 Although there are hundreds of Data repositories available to researchers for Data archiving, the majority of scientists are not aware of their existence or how to access them. One of the major outcomes of the DataUp project is the ONEShare repository, created specifically for DataUp. Users can deposit their tabular Data and metaData directly into the ONEShare repository from within the tool, allowing for seamless Data archiving within the researcherOs current workflow. An added advantage of ONEShare is its connection to the DataONE network of repositories (Michener, 2009). DataONE links together existing Data centers and enables its users to search for Data across all participating repositories using a single search interface. Data deposited into ONEShare will be indexed and made discoverable by any DataONE user, facilitating collaboration and enabling Data re-use. CDL envisions the future of DataUp to be directed by the participating community at large. Code for both the add-in and web application is open source 1 and participation in its improvement is strongly encouraged. Interested developers can expand upon and increase the tool’s functionality to meet the needs of a broad array of researchers. To facilitate this effort, a list of requested improvements, bugs, and feature requests is maintained by CDL 2 . Although the target audience for the tools that result from the DataUp project will be Earth, environmental, oceanographic, and ecological scientists, we believe that any tools developed will be adaptable to other research communities, such as the social sciences.
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Promoting Data Stewardship Through Best Practices
2011Co-Authors: Carly Strasser, Robert B. Cook, William K. Michener, Amber E. Budden, Rebecca KoskelaAbstract:The ecological and environmental sciences are comprised of many different disciplines, each with their own methods, theories, and culture. A characteristic that most of these different disciplines share, however, is a lack of culture for good Stewardship of Data. Characteristics of good Data Stewardship include understanding the importance of Data management, using best practices for managing Data, and recognizing the value of Data sharing and Data reuse for the future of ecology and the environmental sciences. The Data Observation Network for Earth (DataONE) is actively developing a community Database of best practices that can be easily accessed and adopted by scientists to promote good Data Stewardship practices and lead to high quality Data products. Here we introduce DataONE s approach to developing the best practices Database and provide a Data management primer that contains examples relevant to all elements of the Data life cycle.
Alastair Dunning - One of the best experts on this subject based on the ideXlab platform.
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Data Roles of the Future at TU Delft
2019Co-Authors: Alastair Dunning, Marta TeperekAbstract:This Dataset is cited in the LCRDM task group Data Stewardship report, DOI 10.5281/zenodo.2642066 (April 2019).
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Data Stewardship addressing disciplinary Data management needs
International Journal of Digital Curation, 2018Co-Authors: Marta Teperek, Maria J. Cruz, Ellen Verbakel, Jasmin Böhmer, Alastair DunningAbstract:One of the biggest challenges for multidisciplinary research institutions which provide Data management support to researchers is addressing disciplinary differences (Akers and Doty,2013). Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address Data management needs across a multi-disciplinary campus. In this article we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, identify the key challenges and explain our plans for the future.
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Data Stewardship – addressing disciplinary Data management needs
2018Co-Authors: Marta Teperek, Maria J. Cruz, Ellen Verbakel, Jasmin K. Böhmer, Alastair DunningAbstract:One of the biggest challenges for multidisciplinary research institutions which provide Data management support to researchers is addressing disciplinary differences1. Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address Data management needs across a multi-disciplinary campus. In this practice paper, we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, we identify the key challenges and explain our plans for the future.
Darrell S. Kaufman - One of the best experts on this subject based on the ideXlab platform.
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Technical note: Open-paleo-Data implementation pilot - The PAGES 2k special issue
Climate of the Past, 2018Co-Authors: Darrell S. KaufmanAbstract:Abstract. Data Stewardship is an essential element of the publication process. Knowing how to enact Data polices that are described only in general terms can be difficult, however. Examples are needed to model the implementation of open-Data polices in actual studies. Here we explain the procedure used to attain a high and consistent level of Data Stewardship across a special issue of the journal Climate of the Past. We discuss the challenges related to (1) determining which Data are essential for public archival, (2) using Data generated by others, and (3) understanding Data citations. We anticipate that open-Data sharing in paleo sciences will accelerate as the advantages become more evident and as practices that reduce Data loss become the accepted convention.
Yi Shen - One of the best experts on this subject based on the ideXlab platform.
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Research Data Sharing and Reuse Practices of Academic Faculty Researchers: A Study of the Virginia Tech Data Landscape
International Journal of Digital Curation, 2016Co-Authors: Yi ShenAbstract:This paper presents the results of a research Data assessment and landscape study in the institutional context of Virginia Tech to determine the Data sharing and reuse practices of academic faculty researchers. Through mapping the level of user engagement in “openness of Data,” “openness of methodologies and workflows,” and “reuse of existing Data,” this study contributes to the current knowledge in Data sharing and open access, and supports the strategic development of institutional Data Stewardship. Asking faculty researchers to self-reflect sharing and reuse from both Data producers’ and Data users’ perspectives, the study reveals a significant gap between the rather limited sharing activities and the highly perceived reuse or repurpose values regarding Data, indicating that potential values of Data for future research are lost right after the original work is done. The localized and sporadic Data management and documentation practices of researchers also contribute to the obstacles they themselves often encounter when reusing existing Data.
