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Copyright of Cyber Security & Data Governance is the property of Editorial Office of Information Technology & Network Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Indian Telecommunication enterprise has grown into one thousand million-greenback industry. on this tremendously competitive enterprise, it isn't always simply doing some thing right that subjects, however it's also critical that a corporation is doing nothing wrong. Making profit no longer stays the sole reason of organizations, as focus now a day is on patron pride. therefore, it's far important for every business enterprise to research the existing level of satisfaction of their customers, as to bridge any gaps between the expectations of the patron and the products or services provided via the company. customer pleasure with numerous services presented by using cellular smartphone provider providers is a essential aspect in the telecommunications industry. It without delay influences consumer loyalty and the general achievement of the vendors. customers. nowadays assume seamless and dependable connectivity, high-velocity statistics offerings, excellent customer service, and competitive pricing. cell cellphone provider providers are continuously striving to fulfill and exceed those expectations to enhance consumer satisfaction. The pleasant of community coverage and get in touch with reception is a fundamental determinant of user satisfaction. A dependable community ensures that customers could make and receive calls, send texts, and get right of entry to the net with out disruptions or dropped calls. speedy and regular data services, such as 4G and 5G connectivity, also are pivotal in meeting the demands of modern-day phone customers. When customers encounter a problem or have a question; they expect immediate and effective support from their mobile phone provider. This is a descriptive study carried out in Krishnagiri district of Tamil Nadu. The study is mainly based on primary data collected from the mobile phones of customers in Krishnagiri district. The main objective of this study to investigate user satisfaction with mobile phone providers is a multifaceted concept that includes network quality, customer support, and price. To remain competitive in this industry, providers need to continuously improve their services to meet and exceed the evolving expectations of their customers. [ABSTRACT FROM AUTHOR]

Webometric assesses the user convenience and experience while interacting with web-based system. Businesses use websites to present their deliverables to a larger audience. The aim of which is to refocus and reshape a user's image of about a business. This has today, been extended to facilitate activities like recruitment etc. We investigate usability of the University of Delta Agbor (UniDEL) website with other select Nigerian varsities using expert review guideline, and to compare the achieved criterion scores against the selected varsities websites. The adopted methodology is the expert review guideline that is available by the World Ranking of Universities. Result shows the overall performance with UniDEL website performing poorly against the selected websites. These are based on the unique strengths and unique gaps. Unique features showed that selected websites successfully ensured that her trust/credibility section and homepages received highest scores. The UniDEL's website was found to struggle for good search usability, and data entry criteria among other flaws in her web design. Findings suggest UniDEL website needs to be reworked with home-pages, search, trust and content features in mind to ensure greater visibility and user experience. [ABSTRACT FROM AUTHOR]

Background: NYU Langone Health offers a collaborative research block for PGY3 Primary Care residents that employs a secondary data analysis methodology. As discussions of data reuse and secondary data analysis have grown in the data library literature, we sought to understand what attitudes internal medicine residents at a large urban academic medical center had around secondary data analysis. This case report describes a novel survey on resident attitudes around data sharing. Methods: We surveyed internal medicine residents in three tracks: Primary Care (PC), Categorical, and Clinician- Investigator (CI) tracks as part of a larger pilot study on implementation of a research block. All three tracks are in our institution's internal medicine program. In discussions with residency directors and the chief resident, the term "secondary data analysis" was chosen over "data reuse" due to this being more familiar to clinicians, but examples were given to define the concept. Results: We surveyed a population of 162 residents, and 67 residents responded, representing a 41.36% response rate. Strong majorities of residents exhibited positive views of secondary data analysis. Moreover, in our sample, those with exposure to secondary data analysis research opined that secondary data analysis takes less time and is less difficult to conduct compared to the other residents without curricular exposure to secondary analysis. Discussion: The survey reflects that residents believe secondary data analysis is worthwhile and this highlights opportunities for data librarians. As current residents matriculate into professional roles as clinicians, educators, and researchers, libraries have an opportunity to bolster support for data curation and education. [ABSTRACT FROM AUTHOR]

Research data management and data curation need strong relationships with colleagues, collaborators, and researchers. Because change comes fast, assessment of current services and practices are important so that new paths and initiatives can be developed. Creating strong metadata will support the FAIR Principles and provide a more equitable and accessible path to data.

Consultations are fundamental to data librarianship, serving as a vital means of one-on-one support for researchers. However, the topics and forms of support unique to data services consults are not always carefully considered. This commentary addresses five common services offered by data librarians—dataset reference, data management support, data analysis and software support, data curation, and data management (and sharing) plan writing—and considers strategies for successful patron support within the boundaries of a consultation.

A single map of meteorological basic information is a demonstration of the integration of meteorological data resources and industry data. By establishing a spatiotemporal linkage for meteorological big data applications, it solves the challenge of integrating multi-source meteorological data for application services. The information map enables unified access, processing, storage, and management of multi-source heterogeneous spatiotemporal data through three key technologies: Spatial processing of high-resolution meteorological grid data, retrieval of long sequences of massive grid data within arbitrary spatiotemporal ranges, and fusion services for meteorological data and three-dimensional terrain. It provides users with refined data acquisition services. The information map is created using the meteorological big data cloud platform. The virtual server resources, spatial database resources, and meteorological data resources utilized are all sourced from the meteorological big data cloud platform. The information map offers functions such as spatial analysis of multi-source data, layer management, online mapping, and scene application. It extends the data service mode of the meteorological big data cloud platform. For the first time in the meteorological industry, the Beidou grid location code technology has been utilized to create a map of fundamental meteorological information. Through spatial dimensionality reduction, two-dimensional longitude and latitude values are transformed into one-dimensional Beidou grid location codes. Through algorithms, rapid spatial positioning is achieved, addressing the issue of low efficiency in creating spatial indexes for massive data. The information map integrates five categories of data resources: Basic geography, natural resources, ecological environment, socio-economic, and meteorology. It can dynamically combine and construct thematic services based on various meteorological application scenarios, achieving fast and efficient multi-source data services and applications. A map of meteorological basic information provides business support through layer and geographic spatial retrieval services for the new generation of short-term and imminent forecasting and early warning systems. This promotes the development of business systems and ensures the efficient and stable operation of meteorological services. A single map of meteorological basic information supports spatial query services for public meteorological reality mini-programs and China Meteorological Data Network. It expands channels and methods for the public to access meteorological information through public meteorological services. A single map of meteorological basic information ensures the provision of customized grid data temporal query services for major events, achieving integrated meteorological data query services for historical, current, and forecasted events. Accurate meteorological data play a crucial role in ensuring the success of major national events, such as Beijing Winter Olympic Games and Winter Paralympic Games in 2022, as well as in providing essential weather forecasts for events like "7·20" extremely heavy rainstorm of Zhengzhou in 2021. Additionally, meteorological data is shared for social service purposes. A map of meteorological basic information provides effective support in ensuring "life safety, production development, a prosperous life, and a healthy ecology".

With an upsurge of data by global brands to interact/reach prospective clients, the birth of the Internet has today bridged the information gap. Usability is a webometric feature that seeks to ascertain the experience and convenience level of users who interact with a web-based system. It solicits user perception about a digital product and scores vital aspects therein, based on certain criteria. With the website as the digital product of choice, it will seek to score the design and architecture. Thus, the website's deployment must change, reshape and refocus a user's image while satisfying the user's search quest for data about the institution. Our study is an investigation of website usability based on some criteria that describes usability of academic websites with a focus on the Dennis Osadebay University Anwai-Asaba, Nigeria. Result shows the strengths and weaknesses (problems cum prospects) of the websites in relation to redesigning and improving the university website. Its major strength is in its content and architecture; While, the site struggled to ensure effective search, navigation, design and others. Findings suggest that the FUPRE websites is lacking in various usability areas. [ABSTRACT FROM AUTHOR]

Inherent challenges in IP-networks constitutes a major milestone in the convergence of info and communication technology. The advent of 3G and IP-telephony birthed Voice over Internet Protocol as a medium to effectively share data resources protocol amongst connected users. IP-telephony provides a range of multi-service technologies allowing the integration of data solutions onto a converged network via supporting hardware, software and open-source protocols used to control and manage data, voice and video sessions. We propose a VoIP-based telephony for the Federal University of Petroleum Resources Effurun - to help improve campus tele-penetration and provide users with a range of benefits while resolving the issues of latency, packet loss and jitters. Its benefits includes rich media streaming support for blended-learning, unified messaging etc - as it provides support network resilience, economy, flexibility, mobility and productivity for users. Result shows framework resolves the issues of latency, packet loss and jitters. [ABSTRACT FROM AUTHOR]

Cultural heritage (CH) contents are typically strongly interlinked, but published in heterogeneous, distributed local data silos, making it difficult to utilize the data on a global level. Furthermore, the content is usually available only for humans to read, and not as data for Digital Humanities (DH) analyses and application development. This application report addresses these problems by presenting a collaborative publication model for CH Linked Data and six design principles for creating shared data services and semantic portals for DH research and applications. This Sampo model has evolved gradually in 2002–2021 through lessons learned when developing the Sampo series of linked data services and semantic portals in use, including MuseumFinland (2004), CultureSampo (2009), BookSampo (2011), WarSampo (2015), Norssit Alumni (2017), U.S. Congress Prosopographer (2018), NameSampo (2019), BiographySampo (2019), WarVictimSampo 1914–1922 (2019), MMM (2020), AcademySampo (2021), FindSampo (2021), WarMemoirSampo (2021), and LetterSampo (2022). These Semantic Web applications surveyed in this paper cover a wide range of application domains in CH and have attracted up to millions of users on the Semantic Web, suggesting feasibility of the proposed Sampo model. This work shows a shift of focus in research on CH semantic portals from data aggregation and exploration systems (1. generation systems) to systems supporting DH research (2. generation systems) with data analytic tools, and finally to automatic knowledge discovery and Artificial Intelligence (3. generation systems). [ABSTRACT FROM AUTHOR]

Objective: We aimed to understand how medical and health sciences librarians engage with research reproducibility (RR) at their institutions. Methods: We conducted 11 semi-structured interviews with medical and health sciences librarians from different institutions across the United States who are engaged in RR work. We used template analysis to identify eight themes related to librarian engagement with RR. Results: Within medical and health sciences libraries, research reproducibility work and services are seldom described in those terms, and are often hidden within other data services. RR work is highly dependent on institutional context, such as availability of partners and institutional needs. Most of the RR work is handled by individuals or teams who tend to focus on data services broadly. Meaningful assessment of the work is not done well at present. Getting administrators, researchers, and other stakeholders to associate the library with RR is a particular challenge. Librarians who are interested in RR could learn from others who are doing the work, understand their institutional context, identify relevant institutional partners, and model RR practices in their own work.Conclusion: There are a variety of research reproducibility services in health sciences libraries. These services are dependent on institutional context and partners, and often integrated in other data services. More research is needed to understand various aspects of this work, including the impact of the NIH Data Management and Sharing Policy.Author Contributions: [PI initials MM]: Conceptualization, Project administration, Methodology, Investigation, Formal Analysis, Writing – original draft, Writing – review & editing; [Co-PI initials SS]: Methodology, Investigation, Formal Analysis, Data curation, Writing – original draft, Writing – review & editing

A 2018 business case study to provide recommendations and justification for the support of data services at the UC Irvine Libraries. Data curation is the management of data throughout its lifecycle, from creation, maintenance and then archived for future access and analysis. The main purpose of data curation is to ensure that data is reliably retrievable for future research purposes or reuse. At its most basic, what everyone (administrators, researchers, librarians, etc.) wants is for data to be findable, to be accessible, to be interoperable, and to be reusable.

As data services gain momentum in academic libraries, liaison librarians are expected to be part of the education force for data literacy. Nonetheless, due to the broad scope of data literacy, training librarians to improve data-related skills can be challenging. This article used consultation statistics to identify tools and resources employed to solve users’ data questions. The results offered insights into users’ data needs and provided librarians with a clear direction to further develop data skills in their assigned disciplines. The methodology used in this study can be replicated at other institutions to identify needs and to direct professional development. [ABSTRACT FROM AUTHOR]

The data librarianship as a profession produces on workloads can't give us the answers we seek. The library and information science literature wants two irreconcilable things out of its workload data: 1) aggregate comparable data to document and measure use of libraries and its value; and 2) accurate descriptions to document and measure the individual work done by librarians. That is our Gordian Knot. We propose here to change the question asked: how can we achieve a reasonable balance of workload within a group of librarians? That of course implies a focus on a library of a specific type: here a medium-sized academic library of an R2 institution. The goal was to answer a common and longstanding question: we are in continual process of assessing what needs to be done and how/where to shift workloads, but how do we know we're doing it in a reasonable and fair way beyond anecdotes and intuitions? We developed a weighted measure of public services workload in order to assess and track and assign a) areas of declining workload, b) areas of increasing workload (data services), and c) a balance between library divisions contributing to public services. [ABSTRACT FROM AUTHOR]

Main ways to obtain the internal structure and composition parameters of oil and gas drilling cores are CT and scanning electron microscopy. In order to reduce the experimental cost and improve the ability of data sharing, moreover, supporting the comprehensive analysis of different resolution data of CT and scanning electron microscopy, an formation system integrating core data management, visualization and data analysis is designed and developed. The system which is based on B/S structure is named Oil and Gas Drilling Core Digital Analysis System (OGDCDAS). A 4layer layered architecture including supporting environment layer, data resource layer, analysis and service layer, and application layer is established in OGDCDAS. In addition, some key technologies such as 3D pore network modeling based on maximum ball method, core image feature extraction method based on UNet deep learning model are applied in the system. The results demonstrate that the OGDCDAS can firstly manage different kinds of core data, secondly generate key parameters of source rock evaluation and reservoir physical properties of source rocks efficiently, thirdly offer the researchers core data conveniently, avoiding the repeated analysis and the information island of core data to some extent, and finally provide some geological survey services and supports for the petroleum exploration and development. [ABSTRACT FROM AUTHOR]

Nowadays, the role played by registries in monitoring and improving healthcare, including the quality of medical devices, is widely recognized. A well‐designed digital healthcare registry, in particular regarding data collection procedures and tools, can effectively support goals such as monitoring a (large) population subject to a specific condition, describing the natural history of diseases, supporting observational study methods, as well as evaluating the clinical effectiveness or cost effectiveness of healthcare products and services. This article describes the architecture of a new platform implementing a digital interoperable healthcare registry, the Italian Implantable Prostheses Registry (RIPI). One of the main goals of RIPI is to provide reliable and high‐quality data for monitoring surgery outcomes, performing survival analysis, assessing the safety of devices and procedures, and supporting the traceability of patients. The article focuses on the key aspects and choices that guided the design and implementation processes of the new platform. Most of the design choices came from specific requirements to fulfill, in particular concerning data quality, access policy, interoperability, extensibility and modularity. Overall, the article discusses the main challenges and the adopted solutions, proposing a design perspective and describing an experience of interest for computer scientists, engineers and practitioners, in particular in the area of healthcare information systems. [ABSTRACT FROM AUTHOR]

Motivation: Results of simulations with climate models form the most important basis for research and statements about possible changes in the future global, regional and local climate. These output volumes are increasing at an exponential rate (Balaji et al. 2018, Stevens et al. 2019). Efficiently handling these amounts of data is a challenge for researchers, mainly because the development of novel data and workflow handling approaches have not proceeded at the same rate as data volume has been increasing. This problem will only become more pronounced with the ever increasing performance of High Performance Computing (HPC) - systems used to perform weather and climate simulations (Lawrence et al. 2018). For example, in the framework of the European Commission's Destination Earth program the Digital Twins (Bauer et al. 2021) are expected to produce hundreds of terabytes of model output data every day at the EuroHPC computing sites. The described data challenge can be dissected into several aspects, two of which we will focus on in this contribution. Available data in the Earth System Sciences (ESS) are increasingly made openly accessible by various institutions, such as universities, research centres and government agencies, in addition to subject-specific repositories. Further, the exploitability of weather and climate simulation output beyond the expert community by humans and automated agents (as described by the FAIR data principles (F-Findable, AAccessable, I-Interoperable, R-Reusable), Wilkinson et al. 2016) is currently very limited if not impossible due to disorganized metadata or incomplete provenance information. Additionally, developments regarding globally available and FAIR workflows in the spirit of the FAIR Digital Object (FDO) framework (Schultes and Wittenburg 2019, Schwardmann 2020) are just at the beginning. Cultural Change: In order to address the challenges with respect to data mentioned above, current efforts at DKRZ (German Climate Computing Center) are aimed at a complete restructuring of the way research is performed in simulation-based climate research (Anders et al. 2022, Mozaffari et al. 2022, Weigel et al. 2020). DKRZ is perfectly suited for this endeavor, because researchers have the resources and services available to conduct the entire suite of their data-intensive workflows - ranging from planning and setting up of model simulations, analyzing the model output, reusing existing large-volume datasets to data publication and long-term archival. At the moment, DKRZ-users do not have the possibility to orchestrate their workflows via a central service, but rather use a plethora of different tools to piece them together. Framework Environment Freva: The central element of the new workflow environment at DKRZ shall be represented by the Freva (Free Evaluation System Framework) software infrastructure, which offers standardized data and tool solutions in ESS and is optimized for use on high-performance computer systems (Kadow et al. 2021). Freva is designed to be very well suited to the use of the FDO framework. The crucial aspects here are: 1. the standardisation of data objects as input for analysis and processing, 2. the already implemented remote access to data via a Persisitent Identifier (PID), 3. the currently still system-internal capture of analysis provenance and 4. the possibility of sharing results but also workflows by research groups up to large communities. It is planned to extend the functionality of Freva so that the system automatically determines the data required for a specific analysis from a researcher's research question (provided to the system via some interface), enquires available databases (local disk or tape, cloud or federated resources) for that data and retrieves the data if possible. If data are not available (yet), Freva shall be able to automatically configure, set up and submit model simulations to the HPC-System, so that the required data is created and becomes available (cf. Fig. 1). These data will in turn be ingested into Freva's data catalog for reuse. Next, Freva shall orchestrate and document the analysis performed. Results will be provided either as numerical fields, images or animations depending on the researcher's need. As a final step, the applied workflow and/or underlying data are published in accordance with the FAIR data guiding principles. FDOs - towards a global integrated Data Space: To make the process sketched out above a reality, application of the FDO concept is essential (Schwardmann 2020, Schultes and Wittenburg 2019). There is a long tradition in the ESS community of global dissemination and reuse of large-volume climate data sets. Community standards like those developed and applied in the framework of internationally coordinated model intercomparison studies (CMIP) allow for low-barrier reuse of data (Balaji et al. 2018). Globally resolvable PIDs are provided on a regular basis. Current community ESS standards and workflows are already close to being compatible with implementing FDOs, however, now we also have to work on open points in the FDO concept, which are: 1. the clear definition of community-specific FDO requirements including PID Kernel Types specifications, 2. the operation of data type registries and 3. the technical implementation requirements for global access to FDOs. With these in place and implemented in Freva following standardized implementation recommendations, automated data queries across spatially distributed or different types of local databases become possible. We introduce the concept of implementations in Freva and also use it to highlight the challenges we face. Using an example, we show the vision of the work of a scientist in earth system science. [ABSTRACT FROM AUTHOR]

With the evolution of Internet of Vehicles (IoV) and intelligent transportation systems, intelligent connected vehicles (ICV) are becoming the trend in automobile industry worldwide. Assisted by road-side infrastructure and vehicle-mounted sensors, in-vehicle infotainment (IVI) data services are gradually growing more popular with drivers and passengers. In particular, IVI data services are not only restricted to internal cabin, but also are being extended to the external environment (e.g., workplace and home). These data categories include personal demographics/bioinformatics, usage habits, travel patterns, real-time location, audio, video, etc., which in turn induce perceived risk concerns around the data privacy and security of occupants. In this paper, we collect answers from 500 valid respondents and then construct a structural equation model to investigate key factors influencing users' attitudes and behavioral intention (BI) towards IVI data services. Therein, trust is considered to play a vital role in attitude, and is assumed to be affected by perceived security risk (PSR), perceived privacy risk (PPR), and perceived performance risk (PFR). The results show that PSR and PPR have negative effects on user trust. The data breache anxiety positively influences PPR, which explain 75% of variance. In addition, trust can directly affect attitude and BI, which explain 28.6% of variance in attitudes towards IVI data services. Respondents score higher on average for attitude (Mean = 5.762, SD = 0.89) even where perceived risks exist. BI is influenced by the factors of PSR, PFR, trust, and attitude. Through this study, we intend to reveal the relationships among the factors of perceived risk, trust, attitude, and BI towards IVI data services, then provide guidelines for vehicular data governance in order to consolidate user trust for a safer mobility ecosystem. [ABSTRACT FROM AUTHOR]

Research data services have become a key feature of academic libraries. In this paper, we provide an internal assessment of consulting reach and effectiveness for our Data Services provided by the University Libraries at Virginia Tech and using client records from 2016 to 2020. Through this assessment, we explore how service growth and reach across Virginia Tech has evolved with time. We also look more closely at these aspects for one college and discuss how we will use this data to assess the impact of our services. Finally, through the lens of client outcomes, we examine the trends of client interactions over the term of the study. Initially, we envisioned a successful service as one useful to the largest number of entities (primarily colleges and institutes) across Virginia Tech. However, analysis of the data we have gathered over the past 4 years leads us to consider target ing our service growth where it might be most useful. Rather than prioritizing services that are useful to the largest number of researchers, we instead could (and perhaps should) prioritize engagement with researchers and research communities for whom our assistance can make the largest positive impact on their research projects. This assessment of our client data demonstrates the utility of detailed client management records for periodic formative and summative assessment of research data services.

What is qualitative research? Why should the library support qualitative researchers and what are ways the library can provide this support? How can a librarian learn more about qualitative research and data in order to build a support program? A social sciences librarian shares lessons she learned creating a program of services and tools to support qualitative researchers at her university. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper describes two successful approaches to quantitative data literacy training within the UK and the synergies and collaborations between these two programmes. The first is a data literacy training programme, being delivered by the UK Data Service, which focuses on training in basic data literacy skills. The second is a Data Fellows programme that has been developed to help undergraduate social science students gain real-world experience by applying their classroom skills in the workplace. The paper also discusses next steps in the global development of data literacy skills via the EmpoderaData project, which is trialling the Data Fellows programme in Latin America.

Objectives The complexities of the informed consent process for participating in cohort-based medical studies are well-recognised, and the pandemic presented specific challenges related to this. Our response in EXCEED was to build and deploy a local secure eConsent system that was simple to use, provided advanced functionality and improved data linkage. Approach The eConsent system is integrated into a web app (https://exceed.org.uk/) which was written in Python using the Django framework. A unique profile provides participant access to elements of the study, including two-way linkage to REDCap-based surveys and internal bespoke pages (for example an occupation questionnaire backed by a well-established classification) and access to consent to take part in sub-studies. This allowed participants to see which items have been completed or they have taken part in. Administrator tools were also built to enable advanced management and search functionality for dealing with participants queries or data quality issues. Results In 2020, backed by the new eConsent system, and driven by the COVID-19 pandemic, EXCEED undertook both a new wave of recruitment, and re-contacted existing participants to encourage them to take part in COVID related research. Profile registration and management of pre-2020 participants was also enabled by importing their contact details and consent data from legacy tools. Approximately 1000 EXCEED participants gave informed consent using the new system, while ~1000 existing participants registered. Facilitated by improved data quality using the eConsent system, we correctly linked 93% of consented participants to primary care health care records. This high level of data linkage enables research on the causes and consequences of COVID-19 infection, studies of the genomics of disease onset and progression and recall studies. Conclusion We developed a novel eConsent system, which as well as providing online participant registration and improved administration of participants has improved data linkage. Furthermore, the success of the approach has led it to be implemented in other studies with similar requirements.

UC Berkeley’s Library and the central Research InformationTechnologies unit have collaborated to develop a research datamanagement program that leverages each organization's expertiseand resources to create a unified service. The service offers a rangeof workshops, consultation, and an online resource. Because of thiscollaboration, service areas that are often fully embedded in IT,like backup and secure storage, as well as services in the Librarydomain, like resource discovery and instruction, are integrated intoa single research data management program. This case studydiscusses the establishment of the program, the obstacles inimplementing it, and outcomes of the collaborative model.

This paper describes two successful approaches to data literacy training within the UK and the synergies and collaborations between these two programmes. The first is a data literacy training programme, being delivered by the UK Data Service, which focuses on training in basic data literacy skills. The second is a Data Fellows programme that has been developed to help undergraduate social science students gain real-world experience by applying their classroom skills in the workplace. The paper also discusses next steps in the global development of data literacy skills via the EmpoderaData project, which is trialling the Data Fellows programme in Latin America. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to analyse the implementation of RDM at PDDI-LIPI and to assess its staff’s understanding about RDM services. This article also discusses the challenges and obstacles PDDI faces in providing RDM services. The data was collected via an online survey from 28 July to 7 August 2020. The survey consisted of 35 questions and was shared with 36 respondents via social media. The results identified categories such as research data management services, data management planning services, data archiving services, funding, and staff competency and training needs. In addition, this article also discusses the approach and assessment of RDM services, challenges in providing RDM services, and plans for further developing RDM services at PDDI-LIPI. The results showed that the PDDI staff's understanding of RDM services is adequate. As a new service, the implementation of RDM at PDDI-LIPI continues to develop toward optimisation. RIN is a platform used by PDDI to support this goal. The three biggest obstacles faced by PDDI-LIPI in developing RDM services are limited human resources, competence and budget. Various trainings related to RDM, both sending staff off campus and inviting trainers to campus, were carried out by PDDI to overcome these obstacles. It is recommended to conduct further research on the mapping and upskilling of staff in charge of RDM services.

Drawing on the concepts of Theory of Change and Participatory Impact Pathways Analysis, and our own experience of integrating gender and social inclusion in the Community Resilience Forest Management System in Nepal, we develop a five-step framework, which we call flexible, multidisciplinary and reflexive (FMR) approach to mainstreaming gender and social inclusion in the given context of data services. In this study, we demonstrate how this newly devised concept can be effectively implemented at different project stages—planning, monitoring and evaluation—to integrate gender and social inclusion in data services. As reflected in a Climate Resilient Forest Management System in Nepal, we present how the project has successfully harnessed an approach that has transformed a project team, improved understanding of the interface between the two disciplines and helped integrate gender and social inclusion in data services. This study contributes to many ongoing discussions and debates within academic literature about interdisciplinary research projects, and the integration of gender and social inclusion particularly into climate related research and data services.

It takes a strong data science community and many stakeholders to make disparate types of data work so that you and I can continue to explore and learn. Being proactive by including diversity, equity, inclusion, and accessibility (DEIA) policies and practices, along with evaluating liaison/outreach roles and established programs and tools, will go a long way in strengthening the library, its staff and services, and the institution. Fighting for the “food” you need to grow the profession and data services is key to the future of the RDM library community.

Research data management (RDM) is a growing field of practice within academic librarianship and information management. Research data are generated by researchers investigating and describing new information; often, the data that are generated are digital in nature, for example, in spreadsheets or computer code. Researchers are experts in their fields but may not possess the same skillset as librarians and other information professionals when it comes to organizing, preserving, and sharing information. As a field, RDM encompasses a wide range of activities that include documenting and managing research data during a research project as well as sharing and preserving data after the research project is completed. Academic libraries can offer a variety of services that support researchers during the research life cycle; these services vary among institutions. The faculty, staff, and graduate students at Clemson University were surveyed by the library about their RDM needs in the spring of 2021. The survey was based on previous surveys from 2012 and 2016 to allow for comparison, but language was updated, and additional questions were added because the field of RDM has evolved. Survey findings indicated that researchers are overall more likely to back up and share their data, but the process of cleaning and preparing the data for sharing was an obstacle. Few researchers reported including metadata when sharing or consulting the library for help with writing a Data Management Plan (DMP). Researchers want RDM resources; offering and effectively marketing those resources will enable libraries to both support researchers and encourage best practices. Understanding researcher needs and offering timesaving services and convenient training options makes following RDM best practices easier for researchers. Outreach and integrated partnerships that support the research life cycle are crucial next steps for ensuring effective data management. [ABSTRACT FROM AUTHOR]

Research data services have become a key feature of academic libraries. In this paper, we provide an internal assessment of consulting reach and effectiveness for our Data Services provided by the University Libraries at Virginia Tech and using client records from 2016 to 2020. Through this assessment, we explore how service growth and reach across Virginia Tech has evolved with time. We also look more closely at these aspects for one college and discuss how we will use this data to assess the impact of our services. Finally, through the lens of client outcomes, we examine the trends of client interactions over the term of the study. Initially, we envisioned a successful service as one useful to the largest number of entities (primarily colleges and institutes) across Virginia Tech. However, analysis of the data we have gathered over the past 4 years leads us to consider targeting our service growth where it might be most useful. Rather than prioritizing services that are useful to the largest number of researchers, we instead could (and perhaps should) prioritize engagement with researchers and research communities for whom our assistance can make the largest positive impact on their research projects. This assessment of our client data demonstrates the utility of detailed client management records for periodic formative and summative assessment of research data services. [ABSTRACT FROM AUTHOR]

This study describes the process of persona-creation in a liberal-arts university well-integrated within a global network of Geographic Information System researchers. We introduce the concept of personas as an effective user experience research methodology with potential applications to academic library services. We detail the collection of data from high-level researchers as a way to inform the library’s strategic planning and programming. We present the results of the study in the form of three personas: Rachel the Novice, A.J. the Professor, and Jean-Paul the Big-Thinker. These results are specific to our institution, but the method itself can transfer to other contexts. We note the study’s limitations in the final analysis, and make suggestions for maintaining and refining the personas to accurately represent the community of users.