Research Data Services Research Articles

Sharing Qualitative Interview Data in Dialogue with Research Participants

ABSTRACTResearch data sharing is embedded in policies, guidelines and requirements commonly promoted by research funding organizations that demand data to be “as open as possible, as closed as necessary” and FAIR. This paper discusses the challenges of balancing privacy protection with data sharing in a PhD project involving long‐tail, small‐sized qualitative human subjects' data. Based on experiences and feedback from project participants, we argue that privacy protection is about respecting the participants and their self‐image. This can be achieved through dialogue and involvement of the participants building on the principles of shared stewardship. Further, we suggest that de‐identification and plain language consent materials are better at protecting privacy than anonymisation, which in a digital data environment is difficult to achieve and not necessarily a sensible approach for qualitative data, where the gold is in the details. The literature indicates that it matters to participants whether data are reused for research or other purposes, and that they trust the institutions. This supports our claim that research data services must find better solutions for restricted sharing when necessary.

Research Data Management Curriculum of the Research Data Services at the University Library Duisburg-Essen

Reproducible and transparent science requires good research data management (RDM). However, researchers are often not familiar with how to appropriately handle research data, publication options, legal aspects, and the multitude of available software tools. To support scientists at the University of Duisburg-Essen in gaining RDM knowledge and competencies, the Research Data Services developed a structured teaching program – the RDM Curriculum – for researchers from different disciplines and career levels.
 The RDM Curriculum is separated into a basic and an advanced module. In the basic module, participants can select from three full-day courses that address the basics of RDM with different disciplinary focus. The advanced module consists of various 2 hour online hands-on courses on diverse RDM topics and tools. As incentive to attend multiple courses, participants can earn the RDM Badge of the University Library Duisburg-Essen. The curriculum program is complemented by specialized RDM courses and self-learning materials.
 With the RDM Curriculum, we created an easily accessible and individually selectable RDM course offer that enables researchers to gain discipline-specific and individually relevant RDM knowledge. The curriculum structure can gradually be expanded to further target groups (e.g. students) and allows for continuously adding new contents in the advanced module. The high request for the RDM Badge after the first iteration of the RDM Curriculum in the winter semester 2022/2023 confirmed the positive effect of incentives. Consequently, we are planning to establish a Data Champion Award as appreciation of RDM achievements and to showcase best-practice examples at the University of Duisburg-Essen.

Leveraging Terminology Services for FAIR Semantic Data Integration Across NFDI Domains

The National Research Data Infrastructure (NFDI) strives to develop FAIR research data and data services for major scientific disciplines, using terminologies as a key factor for semantic annotations and semantic interoperability of data. Several NFDI consortia provide domain-specific terminologies through Terminology services or registries, offering access, search capabilities, visualization, and downloads. Prioritizing user-friendly access, terminology services seamlessly integrate semantic concepts into applications, often operating in the background to enable smooth semantic annotation and data interoperability. We present exemplary fields of application from selected disciplines and how terminology services support semantic search, user experience, annotation workflows, terminology curation and design.

Computing corporate bond returns: a word (or two) of caution

AbstractWe offer several suggestions for researchers using corporate bond return data. First, despite clear instructions from older papers (e.g., Bessembinder et al., The Review of Financial Studies 22:4219–4258, 2009) about ways to compute credit excess returns, a lot of recent research simply subtracts a Treasury Bill return. We show that this imprecision is likely to contaminate inferences, as the rate component of returns is negatively correlated to the spread component. This is a problem for all research looking at corporate bond returns, especially time series analysis and safer corporate bonds (e.g., investment grade). We provide a simple approach using Wharton Research Data Services (WRDS) data to remove the interest rate component of corporate bond returns. Second, we note significant differences in the coverage of corporate bonds across the Trade Reporting and Compliance Engine (TRACE) platform and typical corporate bond indices. We provide some simple rules for researchers who are using TRACE to select a subset of bonds closest to those contained inside corporate bond indices used by institutional investors. Third, we note differential quality in the prices and hence returns between TRACE and typical corporate bond indices. Corporate bond returns provided by corporate bond indices (i) correctly estimate credit excess returns, (ii) are synchronous for the entire set of bonds, allowing for consistent cross-sectional comparability, and (iii) suffer less from stale pricing issues. Due to these coverage and data quality issues, researchers should try, where possible, to source return data from multiple sources to ensure the robustness of their results.

Informal Board Hierarchy and High-Quality Corporate Development: Evidence from China

Promoting and realizing high-quality economic development is a major development strategy in China, but realizing high-quality macroeconomic development must be implemented at the micro-enterprise level. This paper takes Shanghai and Shenzhen A-share listed companies from 2010 to 2020 as a sample. By collecting data from CSMAR (China Stock Market & Accounting Research Database), CSMAR (China Stock Market & Accounting Research Database), and CNRDS (Chinese Research Data Services) and using a fixed-effects model, this paper investigates the impact of informal board level on the high-quality development of enterprises. The results of the study show that the informal board hierarchy contributes to the high-quality development of firms and is stronger in non-SOEs and firms with lower quality of internal control; the mechanism study shows that the informal hierarchy can contribute to the high-quality development of firms by reducing agency costs and improving business performance. In addition, higher levels of environmental uncertainty and board interaction can weaken the role of the informal hierarchy in promoting high-quality corporate development. Based on the perspective of the informal system, this paper innovatively explores how the informal level of the board of directors can overcome the shortcomings and risks of the “people” in the formal system. It is of practical significance to optimize the corporate governance structure and improve the corporate governance system and promote the high-quality development of enterprises.

Research data services (RDS) in Spanish academic libraries

Research data services (RDS) are actions undertaken to provide researchers with support, advising, training, information, a technological infrastructure and a regulatory framework with respect to research data management (RDM) throughout the life cycle of the data. The implementation of RDS is an activity that is becoming increasingly important within the functions carried out by academic and research libraries. The aim of this study is to provide a snapshot of the research data services implemented in academic libraries in public universities in Spain, identifying the number and types of services deployed. We conducted a Website Content Analysis of the libraries of the 48 Spanish public universities to discover which RDS they are implementing and promoting. The results show that, despite a lack of institutional policies regarding research data, libraries are deploying these new services, albeit unevenly in terms of both the number of services and the type of support provided. Services related to development of the data management plan (DMP) and preservation of the data in repositories predominate. This inventory is presented as a first step towards learning the level of RDS implementation in Spanish academic libraries, providing a partial perspective and leading the way to exploring other aspects in greater depth in future studies.

Data Literacy in the Social Sciences: Findings from a Local Study on Teaching with Quantitative Data in Undergraduate Courses

Objective – The University of New Hampshire (UNH) Library conducted an exploratory study of the pedagogical practices of social science instructors at UNH who teach using quantitative data in undergraduate courses. This study is connected to a suite of parallel studies at other higher education institutions that was designed and coordinated by Ithaka S+R. The four aims of this study were to explore the ways in which instructors teach and engage undergraduates in the social sciences using quantitative data; understand the support needs of these instructors; develop actionable recommendations for campus stakeholders; and identify opportunities for the development of resources, services, or activities in the library to support the use of quantitative data in the classroom. Methods – For the UNH study, the research team recruited eleven participants through convenience sampling for one-on-one, semi-structured interviews. The study sample included lecturers, assistant professors, associate professors, and full professors across seven social science disciplines from the Durham and Manchester campuses. Results – Courses using data provide a unique opportunity for students to gain experience by working with hands-on examples. The two overarching themes identified speak to both the motivations of instructors who teach with data and the challenges and opportunities they face: teaching with data for data literacy and scientific literacy and teaching with data for statistical, data, and tools skill building. Conclusion – Data literacy is an important set of competencies in part because of the quality and quantity of data students encounter; they need to have the ability to critically evaluate data, methods, and claims. This study directed attention to an area that had not previously been examined at UNH and is an important first step toward creating greater awareness and community of practice for social science instructors teaching with data. The UNH Library offers research data services and is exploring new ways of supporting data literacy. UNH has opportunities to create additional supports for instructors and students that could improve student learning outcomes. Such efforts may require cross-college or cross-department coordination as well as administrative support.

Financial distress and service decisions: Empirical evidence from the US domestic airlines

AbstractUnderstanding the firm's service decisions under financial distress is of central importance to service quality regulators and operation management scholars. This study aims to add new evidence to the relationship between financial distress and airline services and reconcile the discrepancies between theory, practical implications, and empirical results. We examine if and how airlines in financial distress may change their service provisions to turn around, with a particular focus on the moderating role of operating unit costs and market share. In the study, four measures of service failure (the inverse of service quality) are constructed and evaluated: airline arrival delay minutes attributable to the carrier, cancelations attributable to the carrier, mishandled baggage, and involuntary denied boardings. In the US domestic airline business context, we estimate the mixed‐effects model using panel data from the Department of Transportation and Wharton Research Data Services. We find robust evidence that financial distress plays a vital role in airline service provisions, and the distress–service relationship is contingent upon the operating unit costs of airlines. The findings provide evidence to help explain the different and sometimes contradictory empirical findings. We depend on the aggressive strategy framework to understand the service effect of airline financial distress.

Developing a Centralized Hub for Research Data Services: Trainings and Resources in Health Sciences Contexts.

In 2021, a new national center was funded by the National Library of Medicine (NLM) to build capacity for providing data services within health sciences libraries by coordinating, developing, and disseminating trainings, curricular resources, and curated pathways for learning. Research data services has been a growing service component for health sciences libraries for over a decade, and efforts have come from individuals, professional societies, task forces, and interest groups; however, there is still a great deal of unrealized potential in this area as well as growing needs driven by new requirements from funders and publishers and increasing demand from institutions for data science skills and support for data-related research needs. The National Center for Data Services (NCDS) was established in July 2021 and is the newest of the Network of the National Library of Medicine (NNLM)'s national offices and centers. NCDS works with the NNLM's seven regional medical libraries and national offices and centers, and draws upon extensive connections with national data and library organizations, all toward the aim of developing capacity for data services in the health information community while centering efforts toward equity, diversity, and accessibility throughout.

Developing a Data Fellowship Program and Peer-to-Peer Support Model

Objectives: To support the library’s research data services program and provide opportunities for student employees to gain skills in supporting data science research and teaching, the author led the creation of a data fellowship program at their institution. The author describes the development of the program’s peer-to-peer support model and how that model was integrated into the library’s broader research data services program.Methods: There were two aspects to the fellowship’s peer-to-peer support model. First, the data fellows provided direct support to their peers—through instruction, reference support, and outreach—who were engaged in data-related research projects and class assignments. Second, the fellows engaged in professional development and learning opportunities led by library colleagues. Results: During the first year of the program, the data fellows provided virtual data reference support, developed two CANVAS modules, conducted an email outreach campaign, and authored several blog posts. Furthermore, the data fellows received data reference training and engaged in discussions with library experts on pertinent data-related topics. These discussions provide the fellows with knowledge and skills that can be utilized both during and after the fellowship.Conclusions: The first year of the STEM Data Fellowship program proved to be successful in establishing the foundation for a robust peer-to-peer learning and support model for research data services at the author’s institution. The author plans to further enhance and grow the program in future years by providing more opportunities for established and new data fellows to contribute to the library’s ongoing RDS efforts.

Inclusion in Data: Incorporating DEIA Components into Research Data Services Practices

The RDAP Summit 2022 theme of "Envisioning an Inclusive Data Future" reeled in various talks which provided ample avenues for incorporating DEIA components into data management strategies as well as outreach to diverse communities. This commentary will focus on a few of the strategies and initiatives discussed in presentations and talks at the conference that could and potentially should be integrated into established Research Data Services programs.

Corporate Financialization, ESG Performance and Sustainability Development: Evidence from Chinese-Listed Companies

With changing times as countries pursue sustainable development, traditional profit-driven strategic decisions are no longer sustainable. A well-planned financial investment may improve a business’s capital flow efficiency, but when short-term wealth overrides long-term value, the financialization of companies will inevitably impede their environmental, social, and governance (ESG) performance. This study examined how company financialization was related to its ESG performance by China Listed Companies between 2010 and 2019. According to empirical tests using data from the China Stock Market & Accounting Research database and the Wind Financial Terminal, corporate financialization negatively affects ESG performance. After a series of robustness tests, such as endogenous analysis, the conclusion still holds. Furthermore, financialization dampens ESG performance more in the private sector and in companies with high technology dependence. Mechanistic analysis shows that corporate financialization not only creates long-term value risks through crowding out real capital and appropriation of green resources but also undermines company ESG performance through a lack of balanced development to achieve objectives and capabilities. Lastly, using the green patent data provided by the Chinese Research Data Services Platform database, it is found that improved green technology innovation can mitigate the damage of corporate financialization on ESG performance, and this mitigation is more pronounced in regions with better green development. This study adds to the empirical evidence on the theoretical and controversial role of corporate financialization. It helps to warn of its short-sighted effects on sustainable development and provides implications through the positive effects of green technology innovations.

Ambulance Transport Destinations In The US Differ By Patient Race And Ethnicity.

Patients in the US belonging to racial or ethnic minority groups often receive medical care in different hospitals than White patients, which contributes to health care disparities. We explored whether ambulance transport destinations contribute to this phenomenon. Using a national emergency medical services research data set for calendar year 2020, we made within-ZIP code comparisons of the transport destinations for White patients and non-White patients transported by ambulance from emergency scenes. We used the dissimilarity index to measure transport destination discordances and decided a priori that a more than 5percent difference in transport destinations (that is, dissimilarity index >0.05) would be practically meaningful. We found meaningful differences in the destination hospitals for White and non-White patients transported by ambulance from locations in the same ZIP code. The median ZIP code dissimilarity index was 0.08, 64percent of ZIP codes had a dissimilarity index above 0.05, and 61percent of patients were transported from ZIP codes with a dissimilarity index above 0.05. Forty-one percent of ZIP codes had a dissimilarity index above 0.10, and one-third of the patients were transported from those ZIP codes. These data indicate that ambulance transport destinations contribute to discordances in where White and non-White patients receive medical care.

The landscape of research data management services in Malaysian academic libraries: librarians’ practices and roles

PurposeThe debate about academic librarians’ roles in research data management (RDM) services is currently relevant, especially in the context of making research data findable, accessible, interoperable and reproducible. This study aims to explore the RDM services offered by Malaysian academic libraries and the implementation progress based on the librarians’ practices and roles.Design/methodology/approachThis descriptive study involves three sequential forms of data collection: a website analysis of 20 academic libraries relating to RDM services, training and policy; an online survey of the academic libraries’ RDM implementation progress; and semi-structured interviews with three academic librarians to gauge their practices and roles in RDM services.FindingsMalaysian academic libraries provide RDM services based on their related or basic skills which are bibliographic management tools, institutional repository and openness of research data rather than impacted services to support RDM, such as data analysis, data citation, data mining or data visualisation services. Although the librarians were aware of RDM and their roles in research data services, the progress of practicing and implementation of the RDM services still has not been fully delivered to support the main RDM elements.Practical implicationsThis study illustrates the RDM roadmap on the current landscape of areas and types of services that the libraries are doing well. The list of services can be used and implemented as the best practices or strategies to be applied within Malaysian academic libraries.Originality/valueThis study highlights the gaps of RDM services in Malaysian academic libraries. To the best of the authors’ knowledge, as this is the first study in Malaysia that articulates the case of RDM services in academic libraries, it has paved the way for further research.

The Plant Phenomics and Genomics Research Data Repository: An On-Premise Approach for FAIR-Compliant Data Acquisition.

The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. However, although many established infrastructures provide comprehensive and long-term stable services and platforms, a large quantity of research data is still hidden. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, for example, time series of images or high-resolution hyperspectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institutional boundaries. To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements an on-premise approach, which allows research data to be kept in place and wrapped in FAIR-aware software infrastructure. In this chapter, the e!DAL infrastructure software and the PGP repository are presented as best practice on how to easily setup FAIR-compliant and intuitive research data services.

Book Review: Research Data Management and Data Literacies

This review offers a critical outline of Koltay Tibor’s Research Data Management and Data Literacies. Tibor’s insights on the current landscape of data ecologies and key components in research data management provide a creative connection between data governance and data management. The review identifies several key challenges in building comprehensive data ecologies and echoes Tibor’s recommendations for librarians on how to address these challenges and provide effective research data services in academic libraries worldwide.

Research Data Management: A Case Study Examining Aerospace, Industrial and Mechanical Science Engineering Faculty Research Practices

ABSTRACT This study explores data management perspectives of aerospace, industrial and mechanical science engineering faculty affiliated with (University of Illinois Urbana-Champaign (UIUC)). The author conducted fourteen semi-structured interviews and analyzed them using a qualitative inductive coding method. This study builds upon previous work and seeks to explore how the elements of data management planning align with researchers’ workflow, challenges, and awareness to research data services. Overall, the goal of this study is to gain a better understanding of these researcher’s data management practices and enhance the research data services provided to faculty and research groups. All these responses inform existing research data management services.

We talk data. We do data.

We talk data. We do data.

Big data-driven investigation into the maturity of library research data services (RDS)

Research data management (RDM) poses a significant challenge for academic organizations. The creation of library research data services (RDS) requires assessment of their maturity, i.e., the primary objective of this study. Its authors have set out to probe the nationwide level of library RDS maturity, based on the RDS maturity model, as proposed by Cox et al. (2019), while making use of natural language processing (NLP) tools, typical for big data analysis. The secondary objective consisted in determining the actual suitability of the above-referenced tools for this particular type of assessment. Web scraping, based on 72 keywords, and completed twice, allowed the authors to select from the list of 320 libraries that run RDS, i.e., 38 (2021) and 42 (2022), respectively. The content of the websites run by the academic libraries offering a scope of RDM services was then appraised in some depth. The findings allowed the authors to identify the geographical distribution of RDS (academic centers of various sizes), a scope of activities undertaken in the area of research data (divided into three clusters, i.e., compliance, stewardship, and transformation), and overall potential for their prospective enhancement. Although the present study was carried within a single country only (Poland), its protocol may easily be adapted for use in any other countries, with a view to making a viable comparison of pertinent findings.

Task information types related to data gathering in media studies

PurposeThe purpose of this paper is to examine what types of task information media scholars need while gathering research data to create new knowledge.Design/methodology/approachThe research design is qualitative and user-oriented. A total of 25 media scholars were interviewed about their research processes and interactions with their research data. The interviews were semi-structured, complemented by critical incident interviews. The analysis focused on the activity of gathering research data. A typology of information (task, domain and task-solving information) guided the analysis of information types related to data gathering, with further analysis focusing only on task information types.FindingsMedia scholars needed the following task information types while gathering research data to create new knowledge: (1) information about research data (aboutness of data, characteristics of data, metadata and secondary information about data), (2) information about sources of research data (characteristics of sources, local media landscapes) and (3) information about cases and their contexts (case information, contextual information). All the task information types should be considered when building data services and tools to support media scholars' work.Originality/valueThe paper increases understanding of the concept of task information in the context of gathering research data to create new knowledge and thereby informs the providers of research data services about the task information types that researchers need.