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Objective: Evaluate and examine Data Literacy (DL) in the supported disciplines of four liaison librarians at a large research university. Methods: Using a framework developed by Prado and Marzal (2013), the study analyzed 378 syllabi from a two-year period across six departments—Criminal Justice, Geography, Geology, Journalism, Political Science, and Sociology—to see which classes included DLs. Results: The study was able to determine which classes hit on specific DLs and where those classes might need more support in other DLs. The most common DLs being taught in courses are Reading, Interpreting, and Evaluating Data, and Using Data. The least commonly taught are Understanding Data and Managing Data skills. Conclusions: While all disciplines touched on data in some way, there is clear room for librarians to support DLs in the areas of Understanding Data and Managing Data.

Background: Data visualization is a growing topic of discussion and area of educational programming in health sciences libraries. This paper synthesizes information on eight institutions’ experiences in offering Excel-focused data visualization workshops with the goal of providing an overview of the current state of educational offerings in this area. Methods: Semi-structured interviews were conducted by phone and email with librarians at institutions that offer Excel-focused workshops, which were identified by reviewing the websites of Association of Academic Health Sciences Libraries members and the 2019 Medical Library Association annual meeting program. Results: Librarians from six institutions were interviewed, online class materials from one institution were reviewed, and information from the author’s institution was included, resulting in a total of eight institutions. Educational offerings in Excel-focused data visualization ranged from one workshop to five workshops in a series, which typically first presented information for beginners and then progressed to more advanced data visualization skills. Regarding motivations for offering these workshops, librarians stated that they were committed to providing instruction in software programs that were already familiar to users. Workshop evaluations, when available, were generally positive. Discussion: Because of its widespread availability and usage, Excel offers a compelling opportunity for providing hands-on data visualization instruction in health sciences libraries.

Objective: This paper aims to inform on opportunities for librarians to assist faculty with research data management by examining practices and attitudes among life sciences faculty at a tier one research university. Methods: The authors issued a survey to estimate actual and perceived research data management needs of New York University (NYU) life sciences faculty in order to understand how the library could best contribute to the research life cycle. Results: Survey responses indicate that over half of the respondents were aware of publisher and funder mandates, and most are willing to share their data, but many indicated they do not utilize data repositories. Respondents were largely unaware of data services available through the library, but the majority were open to considering such services. Survey results largely mimic those of similar studies, in that storing data (and the subsequent ability to share it) is the most easily recognized barrier to sound data management practices. Conclusions: At NYU, as with other institutions, the library is not immediately recognized as a valuable partner in managing research output. This study suggests that faculty are largely unaware of, but are open to, existent library services, indicating that immediate outreach efforts should be aimed at promoting them.

Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies.

Research data management practices have gained momentum the world over. This is due to increased demands by governments and other funding agencies to have research data archived and shared as widely as possible. This paper sought to establish the data sharing practices of researchers in South Africa. The study further sought to establish the level of collaboration among researchers in sharing research data at the university level. The outcomes of the survey will help the researchers to develop appropriate data literacy awareness programmes meant to stimulate growth in data sharing practices for the benefit of research, not only in South Africa, but the world at large. A survey research method was used to gather data from willing public universities in South Africa. A similar study was conducted in other countries such as the United Kingdom, France and Turkey but the Researchers believe that circumstances in the developed world may differ with the South African research environment, hence the current study. The major finding of this study was that most researchers preferred to use data produced by others but less keen on sharing their own data. This study is the first of its kind in South Africa which investigates data sharing practices of researchers from multi-disciplinary fields at the university level and will contribute immensely to the growing body of literature in the area of research data management.

Background: Librarians developed a pilot program to provide training, resources, strategies, and support for medical libraries seeking to establish research data management (RDM) services. Participants were required to complete eight educational modules to provide the necessary background in RDM. Each participating institution was then required to use two of the following three elements: (1) a template and strategies for data interviews, (2) a teaching tool kit to teach an introductory RDM class, or (3) strategies for hosting a data class series. Case Presentation: Six libraries participated in the pilot, with between two and eight librarians participating from each institution. Librarians from each institution completed the online training modules. Each institution conducted between six and fifteen data interviews, which helped build connections with researchers, and taught between one and five introductory RDM classes. All classes received very positive evaluations from attendees. Two libraries conducted a data series, with one bringing in instructors from outside the library. Conclusion: The pilot program proved successful in helping participating librarians learn about and engage with their research communities, jump-start their teaching of RDM, and develop institutional partnerships around RDM services. The practical, hands-on approach of this pilot proved to be successful in helping libraries with different environments establish RDM services. The success of this pilot provides a proven path forward for libraries that are developing data services at their own institutions.

Marine data are needed for many purposes: for acquiring a better scientific understanding of the marine environment, but also, increasingly, as marine knowledge for decision making as well as developing products and services supporting economic growth. Data must be of sufficient quality to meet the specific users' needs. It must also be accessible in a timely manner. And yet, despite being critical, this timely access to known-quality data proves challenging. Europe's marine data have traditionally been collected by a myriad of entities with the result that much of our data are scattered throughout unconnected databases and repositories. Even when data are available, they are often not compatible, making the sharing of the information and data aggregation particularly challenging. In this paper, we present how the European Marine Observation and Data network (EMODnet) has developed over the last decade to tackle these issues. Today, EMODnet is comprised of more than 150 organizations which gather marine data, metadata, and data products and make them more easily accessible for a wider range of users. EMODnet currently consists of seven sub-portals: bathymetry, geology, physics, chemistry, biology, seabed habitats, and human activities. In addition, Sea-basin Checkpoints have been established to assess the observation capacity in the North Sea, Mediterranean, Atlantic, Baltic, Artic, and Black Sea. The Checkpoints identify whether the observation infrastructure in Europe meets the needs of users by undertaking a number of challenges. To complement this, a Data Ingestion Service has been set up to tackle the problem of the wealth of marine data that remain unavailable, by reaching out to data holders, explaining the benefits of sharing their data and offering a support service to assist them in releasing their data and making them available through EMODnet. The EMODnet Central Portal (www.emodnet.eu) provides a single point of access to these services, which are free to access and use. The strategic vision of EMODnet in the next decade is also presented, together with key focal areas toward a more user-oriented service, including EMODnet for business, internationalization for global users, and stakeholder engagement to connect the diverse communities across the marine knowledge value chain.

As data skills are incorporated into academic curriculum and data becomes more widely available and used in everyday life, many librarians find themselves serving as 'accidental' data librarians in their subject areas. Due to this evolving landscape and growing data need, it is increasingly important for librarians to be familiar with data resources and able to answer secondary data reference questions. To learn more about this area of librarianship, this study uses survey responses from librarians who answer data questions to explore the challenges and frustrations that arise from data reference questions and interactions. Our key findings reveal that frustrations are ever present in data reference regardless of how much experience a librarian has, and many frustrations arise due to factors such as patron expectations, subject-specific and data-related jargon, and data formats and accessibility.

The study primarily aims to explore visualisation approaches used by libraries in visualising analytics to present their value and impact on the academic community. It attempts to investigate and answer the following research questions: (1) What are the current practices of academic libraries in data sharing and visualisation?; (2) What kinds of data are displayed on library websites and dashboards?; and, (3) How do libraries visualise their data on the web? This study is a descriptive survey research design that employed content analysis to examine the library websites of the top 500 universities based on QS World University Ranking 2018 and ascertain the presence of public-facing data and availability of library dashboards. Website investigation and capturing of web pages were conducted from September 2018 to March 2019. A total of 157 universities published their library data on the web. Many libraries of top-ranking universities published their data online using textual facts and figures. Surprisingly, data show that only a few academic libraries around the world have developed their data dashboards. It implies that librarians have not taken full advantage of the benefits of data visualisation. Library data in dashboards are presented in a visually less appealing and interactive report using visualisation tools that delivers clear insights to library patrons, university administrators, and accrediting agencies. Published library data include reference transactions, usage of services, collections and spaces, library visits (physical and virtual), numbers of eBooks, online journals, open access resources and other collections, interlibrary and document delivery transactions, staffing, budget and expenditures, items checked out, library instruction sessions and attendees, equipment loans, digital image documents, new acquisition, and digitisation. Most data are text, numbers, and graphs, thus, not-interactive and real-time. The results of this study may prescribe best practices in communicating library data to its stakeholders, in which Filipino librarians may benchmark. Librarians can make better, more data-driven decisions to drive continuous improvement of library operations. [ABSTRACT FROM AUTHOR]

Academic Libraries are ideally positioned to teach data literacy. What is 'data literacy' in the first place? Is it the new information literacy? Will the ways we teach information literacy limit imaginative ways to teach data literacy?. With those questions in mind, the Library of New York University Shanghai has explored multiple ways to teach data literacy to undergraduate students through university events, 'for-class' instruction and workshops, and online casebooks. (1) We initiated the yearlong series of events titled 'Lying with Data', inviting faculty across disciplines to each address one core data literacy question that students of data science may misunderstand (2) We offered workshops and in-class instruction that are up-to-date with the latest technology and that fit with the curriculum. (3) We created online casebooks on various topics in the data lifecycle, tackling user needs at different levels. Essential to our teaching activities are two core values: 'let the quality speak for itself', and 'outreach by teaching'. [ABSTRACT FROM AUTHOR]

This study examines the essential and desirable knowledge, skills, abilities, and experience for data librarians and related positions in academic libraries. It also aims to explore the duties and responsibilities of these positions to define the profession of data librarianship clearly. This paper attempted to address the following research questions: (1) What are the common competencies and duties of data librarians and related positions as stated in job advertisements?; (2) What are the specific duties and tasks related to research data management are being performed by librarians in Philippine academic libraries?; and, (3) Based on the job advertisement data, what are the training needs of data librarians? This study employed content analysis approach to explore the patterns in library hiring trends and recognise the wide range of competencies needed by data librarians. Various online job search sites were used to collect job advertisements for data librarians and other positions related to data management in libraries. Job descriptions and qualifications were examined based on the following characteristics: position titles, degree requirements, expected years of experience, and salary range. The content analysis was performed using NVivo drag and drop coding technique based on the pre-set categories and sub-categories of qualifications, duties and responsibilities adopted from the job analysis frameworks used by previous studies. The findings of this study are quite interesting as it presents an increasing demand for data librarian positions in many libraries abroad. However, data librarian is not an emerging position in selected Philippine academic libraries. Librarians with research data services responsibilities are commonly known as data librarians. Many job announcements require at least three-year work experience in research data management. The results of this study provide useful information for librarians seeking for positions and library managers who wish to hire data librarians as well as for LIS school administrators who desire to produce LIS graduates with the necessary skills to provide data services. It is also unique as Filipino librarians are included in this study to determine if existing librarian positions perform duties and tasks related to research data management and services. [ABSTRACT FROM AUTHOR]

Data sharing and reuse are regarded as important components of the research workflow and key elements in open science. While reuse is well-documented in some circumstances, the utility of data sharing for all domains is less clear, and limited evidence of wide-spread demand can make it challenging to justify effort and funds required to format, document, share, and preserve data. This paper describes a project that: (1) surveyed authors of highly cited papers published in 2015 at the University of Illinois at Urbana-Champaign in nine STEM disciplines to determine if data were generated for their article and their knowledge of reuse by other researchers, and (2) surveyed authors who cited these 2015 articles to ascertain whether they reused data from the original article and how that data was obtained. The project goal was to better understand data reuse in practice and to explore if research data from an initial publication was reused in subsequent publications. While the results revealed reuse in many situations (and deemed important in these cases), the survey results and researcher supplied comments also indicated that data does not play the same role in all studies or even in studies that build on previous ones. [ABSTRACT FROM AUTHOR]

Being able to obtain various environmental and driving data from vehicles is becoming more and more important for current and future intelligent transportation systems (ITSs) to operate efficiently and economically. However, the limitations of privacy protection and security of the current ITSs are hindering users and vehicles from providing data. In this paper, we propose a new ITS architecture by using blockchain technology solving the privacy protection and security problems, and promoting users and vehicles to provide data to ITSs. The proposed architecture uses blockchain as a trust infrastructure to protect users’ privacy and provide trustworthy services to users. It is also compatible with the legacy ITS infrastructure and services. In addition, the hierarchical organization of chains enables the scalability of the system, and the use of smart contracts provides a flexible way for introducing new services in the ITS. The proposed architecture is demonstrated by a proof of concept implementation based on Ethereum. The test results show that the proposed architecture is feasible.

Background: The authors’ main university library and affiliated academic medical center library sought to increase library programming around data visualization, a new service area for both libraries. Additionally, our institution is home to many researchers with a strong interest in data visualization but who are generally working in isolation of one another. Case Presentation: This case study describes an innovative workshop, the “Data Visualization Clinic,” where members of our library’s community bring in data visualization projects such as figures in papers, projects hosted online, and handouts and receive constructive feedback from a group of peers. The authors detail the process of hosting a clinic and the feedback that we received from participants. Conclusions: The “Data Visualization Clinic” offers a viable workshop to leverage expertise of library users and build the library’s reputation as a hub of data visualization services without heavy investment in infrastructure like special monitors or coding skills. That said, it faces the challenge of relying on the participation of the broader community, which is often pressed for time. The event can also serve as an opportunity for researchers who have an interest in data visualization to meet and network.

As data skills are incorporated into academic curriculum and data becomes more widely available and used in everyday life, many librarians find themselves serving as 'accidental' data librarians in their subject areas, a phenomenon widely discussed at conferences (including IASSIST), in publications, and in the field at large. Due to this evolving landscape and growing data need, it is increasingly important for librarians to be familiar with data resources and able to answer secondary data reference questions. To learn more about this area of librarianship, this study uses survey responses from librarians who answer data questions to explore the challenges and frustrations that arise from data reference questions and interactions. Our key findings reveal that frustrations are ever present in data reference regardless of how much experience a librarian has, and many frustrations arise due to factors such as patron expectations, subject-specific and data-related jargon, and data formats and accessibility, some of which are beyond the data librarian's control. [ABSTRACT FROM AUTHOR]