Data Curation Profiles Research Articles

Data Curation Profiling to Assess Data Management Training Needs and Practices to Inform a Toolkit

The purpose of this paper is to explore current data management training needs and practices for Belmont Forum member agencies and researchers to inform a Toolkit. Fourteen Belmont Forum affiliated individuals were interviewed following a predetermined set of questions to create data curation profiles of their funded work. The data curation profile questionnaire includes questions related to data management, storage, stakeholders, costs, training, and credentials. The interview findings highlight gaps in existing knowledge of data management theory and practice that could impact data re-use. Results of these interviews were used to populate a Toolkit of data management training and effective practice resources specifically developed to train Belmont Forum grant awardees. The results also highlight some attitudes and behaviours of current scientists, researchers, and agency representatives, and the impact of the implementation of data management plans on the open science movement.

Functional Requirements for Research Data Repositories

Research data must be testable. Science is all about verification and testing. To make data testable, tools used to produce, collect, and examine data during the research must be available. Quite often, however, these data become inaccessible once the work is over and the results being published. Hence, information and the related context must be provided on how research data are preserved and how they can be reproduced. Open Science is the international movement for making scientific research data properly accessible for research community. One of its major goals is building data repositories to foster wide dissemination of open data. The objectives of this research are to examine the features of research data, common repository platforms, and community requests for the purpose of designing functional requirements for research data repositories. To analyze the features of the research data, we use data curation profiles available from the Data Curation Center of the Purdue University, USA. For common repository platforms we examine Fedora Commons, iRODS, DataONE, Dataverse, Open Science Data Cloud (OSDC), and Figshare. We also analyze the requests from research community. To design a technical solution that would meet public needs for data accessibility and sharing, we take the requirements of RDA Repository Interest Group and the requests for the DataNest Community Platform developed by the Korea Institute of Science and Technology Information (KISTI). As a result, we particularize 75 requirement items grouped into 13 categories (metadata; identifiers; authentication and permission management; data access, policy support; publication; submission/ingest/management, data configuration, location; integration, preservation and sustainability, user interface; data and product quality). We hope that functional requirements set down in this study will be of help to organizations that consider deploying or designing data repositories. URL: http://ijkcdt.net/xml/13281/13281.pdf

Research data services

The paper reports on an exploratory study of researchers’ needs for effective research data management at two Swedish universities, conducted in order to inform the ongoing development of research data services. Twelve researchers from diverse fields have been interviewed, including biology, cultural studies, economics, environmental studies, geography, history, linguistics, media and psychology. The interviews were structured, guided by the Data Curation Profiles Toolkit developed at Purdue University, with added questions regarding subject metadata. The preliminary analysis indicates that the research data management practices vary greatly among the respondents, and therefore so do the implications for research data services. The added questions on subject metadata indicate needs of services guiding researchers in describing their datasets with adequate metadata.

Data curation profiling of biocollections

ABSTRACTIn the contexts of the data deluge and open data, scientists studying biodiversity benefit from online access to global datasets of existing vouchered biological and paleontological collections. Using biocollections collected over time across the world allows for the advancement of scientific knowledge concerning evolution in process as well as species poleward migrations, an indicator of climate change. This study's purpose was to validate and expand the Data Curation Profiles (DCP) to digital biocollections and inform a DCP framework for worldwide biota. Ten biocollection producers, curating various types of specimens affiliated with the project building the United States' national biodiversity infrastructure, were interviewed using the DCP questionnaire. Results indicate there is extreme diversity in the curation of biocollections and additional DCP questions should be added to reflect the complicated approaches to biological data curation. Although discipline specific metadata creation tools, standards, and practices enable long‐term sustainability of the U.S. digitization effort, some scientists would benefit from further clarification and guidance on the information needs of consumers beyond designated communities of expert users, and the long‐term preservation of biocollections.

Research Data Integration in the Purdue Libraries

EDITOR'S SUMMARYAt the 2015 ASIS&T Research Data Access and Preservation (RDAP) Summit, panelists from Research Data @ Purdue University Libraries discussed the organizational structure intended to promote campus‐wide collaboration among diverse data specialists. Amy Barton explained her role as metadata specialist for research data and the importance of being engaged with evolving standards and best practices. As digital user experience specialist, Tao Zhang evaluated the Data Curation Profiles Toolkit, including an interview protocol librarians use to explore researchers’ data needs and a web application for researchers to create data management plans. Line Pouchard, an information specialist focusing on big data, explored the data curation lifecycle model in general and its unique aspects in the context of big data. Information specialist for molecular biosciences, Pete Pascuzzi addressed the importance of bioinformatics for data reuse and having librarians work in an embedded position with researchers.

Assessing Perceived Usability of the Data Curation Profile Toolkit Using the Technology Acceptance Model

The Data Curation Profiles Toolkit (DCPT) emerged out of a Purdue University Libraries’ 2004 initiative to engage in multidisciplinary research. It is a tool developed to assist librarians and other information professionals to conduct data interviews and identify the needs of researchers when managing, sharing, or curating their data. The DCPT has been widely adopted and applied in various contexts but its usability as a tool has not been formally assessed. To address this need, we have conducted a survey of users of the DCPT. The survey included quantitative measures of potential influencing factors of using the DCPT and its perceived usability (its usefulness as a tool and its ease of use). Open-ended questions about users’ experiences with the DCPT were also included to better understand the strengths and weaknesses of the tool, as well as areas that could be improved. Factor analysis of the quantitative results and subsequent regression models revealed several underlying factors that affect the perceived usability of the DCPT. Responses to the open-ended questions revealed several themes of users’ concerns: the amount of time required to use the DCPT, the structure and format of the DCPT, alignment of the DCPT with particular contexts, and the use of the DCPT to engage faculty and the library community. By correlating themes identified from the open-ended questions with the analysis of quantitative data, this paper provides the first empirical assessment of the DCPT that could help further improve the toolkit’s usability based on user needs and expectations. The methodology used in the study could readily be applied to assess and improve the utility of other tools used by data and information professional.

“Personas” to Support Development of Cyberinfrastructure for Scientific Data Sharing

Objective: To ensure that cyberinfrastructure for sharing scientific data is useful, system developers need to understand what scientists and other intended users do as well as the attitudes and beliefs that shape their behaviours. This paper introduces personas — detailed descriptions of an “archetypical user of a system” — as an approach for capturing and sharing knowledge about potential system users. Setting: Personas were developed to support development of the ‘DataONE’ (Data Observation Network for Earth) project, which has developed and deployed a sustainable long-term data preservation and access network to ensure the preservation and access to multi-scale, multi-discipline, and multi-national environmental and biological science data (https://www.dataone.org/what-dataone) (Michener et al. 2012). Methods: Personas for DataONE were developed based on data from surveys and interviews done by members of DataONE working groups along with sources such as usage scenarios for DataONE and the Data Conservancy project and the Purdue Data Curation Profiles (Witt et al. 2009). Results: A total of 11 personas were developed: five for various kinds of research scientists (e.g., at different career stages and using different types of data); a science data librarian; and five for secondary roles. Conclusion: Personas were found to be useful for helping developers and other project members to understand users and their needs. The developed DataONE personas may be useful for others trying to develop systems or programs for scientists involved in data sharing.

Book Review: Data Management for Libraries: A LITA Guide

Data Management for Libraries: A LITA Guide. By Laura Krier and Carly A. Strasser. Chicago: ALA TechSource, 2014. 112 p. $58 paperback (ISBN: 978-1-55570-969-3). Data Management for Libraries provides a brief guide to data management for librarians who are novices in this emerging area. The book is organized into eight chapters, with three appendixes. Chapter 1 provides a basic overview of data, data management, and the data curation lifecycle. Chapter 2 a variety of considerations for starting a new service: developing a new service as a pilot project; collaborating with other colleagues within both the library and the institution during the entire data lifecycle; training scholars to better manage their data; and staffing, particularly when that staffing requires that existing librarians take on responsibilities without relinquishing others. The general information regarding starting a new service includes several considerations that are worthwhile for initiating any new service. Particular to data management are planning for data preservation as a part of the service, and also data training for researchers that may not have experience in data management. Chapter 3 is devoted to an overview of data management plans. Librarians are well-poised to assist researchers in this particular capacity, especially since many researchers currently lack the skills to write a data management plan. Some researchers may need extra motivation to create a data management plan, and this chapter provides useful suggestions to help researchers find value in writing a plan. This chapter also provides an overview of the components of a data management plan, including: description of data/metadata; security, ethics and intellectual property; plans for data access, sharing and reuse; plans for short-term management and storage; plans for long-term management/ storage; resources needed to implement the plan. The chapter offers several questions to generate the readers' ideas of what may need to be considered in a data management plan, and concludes with some advice for complying with funder requirements. Chapter 4 discusses the data management interview, which is similar to a reference interview. The chapter summarizes previous research into data curation profiles and personas of researchers that may require assistance with data management. It also stresses the importance of involving liaison/reference librarians in data management since they are likely the colleagues that already have strong relationships with researchers at the institution. An important role for librarians may be to raise components of data management when interviewing researchers. Like the reference interview, data management interviews require active listening. Chapters 5 and 6 address facets of data management wherein librarians clearly lead their institutions regarding expertise: metadata and preservation. In chapter five, the authors provide an overview of the three different types of metadata that can describe a dataset: descriptive, administrative, and structural. …

Data Curation: A Study of Researcher Practices and Needs

Colorado State University librarians conducted five focus groups with thirty-one faculty, research scientists, and research associates. The groups explored: (1) The nature of data sets that these researchers create or maintain; (2) How participants manage their data; (3) Needs for support that the participants identify in relation to sharing, curating, and preserving their data; and (4) The feasibility of adapting the Purdue University Libraries’ Data Curation Profiles Toolkit interview protocol for use in focus groups with researchers. The authors report their review of related literature, themes that emerged from analysis of the focus groups, and implications for related library services.

Data curation profiles as a means to explore managing, sharing, disseminating or preserving digital outcomes

While the concept of a digital archive is familiar to almost everyone, it may be less understood how to identify digital outcomes as candidates for archiving. The Data Curation Profiles Toolkit is an instrument designed to interview data producers about their data, what they are doing with it and what they would like to do with it. Currently used primarily in the realm of academic scientific research, the Toolkit is agnostic to discipline and could be used to interview anyone who creates and/or produces digital outputs that may be managed, shared, disseminated or preserved. An example looking at dance, its digital outputs and artist expectations is discussed.

Data narratives: Increasing scholarly value

Data narratives or data stories have emerged as a new form of the scholarly communication focused on data. In this paper, we explore the potential value of data narratives and the requirements for data stories to enhance scholarly communication. We examine three types of data stories that form a continuum from the less to the more structured: the DataONE data stories, the Data Curation Profiles, and the Data Descriptors from the journal Scientific Data. We take the position that these data stories will increase the value of scholarly communication if they are linked to the datasets and to the publications that describe results, and have instructional value.

Data Management and Sharing from the Perspective of Graduate Students: An Examination of the Culture and Practice at the Water Quality Field Station

Libraries are actively seeking to identify and respond to the data management and curation needs of researchers. One important perspective often overlooked in acquiring an understanding is that of graduate students. This case study used the Data Curation Profile Toolkit to interview six graduate students working for agronomy researchers at the Water Quality Field Station (WQFS) research lab to understand the students’ practices with data, the challenges they face, and their attitudes toward managing and sharing data. Though a small study, this research could provide new insights for libraries creating data services, particularly in regard to graduate students.

Opportunities and Barriers for Librarians in Exploring Data: Observations from the Data Curation Profile Workshops

Setting and Objective: The Purdue University Libraries offered a series of professional development workshops in 2011-2012 to provide librarians with a broad understanding of issues in data curation and to train them in the use of the Data Curation Profiles Toolkit (DCP Toolkit). An additional goal of the workshop was to develop a better understanding of the experiences, attitudes, and needs of librarians as they explore new roles. Design and Methods: Workshop participants were asked to complete three surveys: one before the workshop, one right afterwards, and one delivered three months after they had attended the workshop. Participants’ responses to the survey questions that pertained to demographic information, confidence levels, and levels of engagement before and after the workshop were reviewed and analyzed. Results: The results of the survey indicated that participants’ confidence levels in multiple areas increased after the workshop, but that their levels of engagement remained relatively stagnant. An analysis of the free text comments made in the survey revealed multiple issues in librarians’ efforts to increase their engagement in working with data including time, staffing, and organizational support from their library. Conclusions: The challenges encountered by librarians seeking to engage in data management and curation issues are found at the individual level (acquiring skills and confidence) and at the organizational level (creating a supportive environment). Both levels will need to be addressed by libraries seeking to develop data services.

Using data profiles to select digital asset management systems (DAMS)

AbstractMany grants, including grants from the National Science Foundation (NSF) require recipients to utilize data management plans; some grants, like those given by NSF, require recipients to place their data in searchable data repositories. It is difficult to find one data repository that meets every researcher's needs. To solve this problem, we utilized Purdue's Data Curation Profile Toolkit to interview researchers at our university and assist in developing data profiles/plans. These profiles provided the Digital Asset Management (DAM) project team with valuable information about the researchers' data needs. The DAM project team created a matrix of the researchers' data needs and used the matrix to evaluate the credentials of 24 Digital Asset Management Systems (DAMS). The team was able to select the DAMS that met the needs of researchers. Using this method, any university could select a DAMS and be confident that it would meet the needs of the researchers it was intended to serve.

Demystifying the data interview

PurposeAs libraries become more involved in curating research data, reference librarians will need to be trained in conducting data interviews with researchers to better understand their data and associated needs. This article seeks to identify and provide definitions for the basic terms and concepts of data curation for librarians to properly frame and carry out a data interview using the Data Curation Profiles (DCP) Toolkit.Design/methodology/approachThe DCP Toolkit is a semi‐structured interview designed to assist librarians in identifying the data curation needs of researchers. The components of the DCP Toolkit were analyzed to determine the base level of knowledge needed for librarians to conduct effective data interviews. Specific concepts, definitions, and examples were sought through a review of articles, case studies, practitioner resources and from the experiences of the Purdue University Libraries.FindingsData curation concepts and terminology are not yet well‐defined and often vary across, or even within fields of study. This research informed the development of a workshop to train librarians in using the DCP Toolkit. The definitions and concepts addressed in the workshop include: data, data set, data lifecycle, data curation, data sharing, and roles for reference librarians.Practical implicationsConducting a data interview can be a daunting task given the complexity of data curation and the lack of shared definitions. Practical tools and training are needed to help librarians develop capacity in data curation.Originality/valueThis article provides practical information for public service librarians to help them conceptualize and conduct a data interview with researchers.

Data sharing, small science and institutional repositories

Results are presented from the Data Curation Profiles project research, on who is willing to share what data with whom and when. Emerging from scientists' discussions on sharing are several dimensions suggestive of the variation in both what it means 'to share' and how these processes are carried out. This research indicates that data curation services will need to accommodate a wide range of subdisciplinary data characteristics and sharing practices. As part of a larger set of strategies emerging across academic institutions, institutional repositories (IRs) will contribute to the stewardship and mobilization of scientific research data for e-Research and learning. There will be particular types of data that can be managed well in an IR context when characteristics and practices are well understood. Findings from this study elucidate scientists' views on 'sharable' forms of data-the particular representation that they view as most valued for reuse by others within their own research areas-and the anticipated duration for such reuse. Reported sharing incidents that provide insights into barriers to sharing and related concerns on data misuse are included.

Constructing Data Curation Profiles

This paper presents a brief literature review and then introduces the methods, design, and construction of the Data Curation Profile, an instrument that can be used to provide detailed information on particular data forms that might be curated by an academic library. These data forms are presented in the context of the related sub-disciplinary research area, and they provide the flow of the research process from which these data are generated. The profiles also represent the needs for data curation from the perspective of the data producers, using their own language. As such, they support the exploration of data curation across different research domains in real and practical terms. With the sponsorship of the Institute of Museum and Library Services, investigators from Purdue University and the University of Illinois interviewed 19 faculty subjects to identify needs for discovery, access, preservation, and reuse of their research data. For each subject, a profile was constructed that includes information about his or her general research, data forms and stages, value of data, data ingest, intellectual property, organization and description of data, tools, interoperability, impact and prestige, data management, and preservation. Each profile also presents a specific dataset supplied by the subject to serve as a concrete example. The Data Curation Profiles are being published to a public wiki for questions and discussion, and a blank template will be disseminated with guidelines for others to create and share their own profiles. This study was conducted primarily from the viewpoint of librarians interacting with faculty researchers; however, it is expected that these findings will complement a wide variety of data curation research and practice outside of librarianship and the university environment.