Data Literacy and Research Data Management: The Croatian State of Affairs

Author(s):  
Sonja Špiranec ◽  
Denis Kos
2018 ◽  
Vol 17 (32) ◽  
pp. 12
Author(s):  
Гордана Стокић Симончић ◽  
Драгана Сабовљев

У раду су представљени резултати истраживања које је спроведено током 2017. године на Универзитету у Београду, а имало је за циљ да утврди ниво информационе писмености наставника и сарадника, испитујући њихову оспособљеност за руковање истраживачким подацима. Истоветном онлајн анкетом (Вештина коришћења података и управљање истраживачким подацима – Data Literacy and Research Data Management Research) прикупљани су подаци о навикама истраживача (професора, сарадника, докторанада, библиотекара), у академским срединама већег броја европских држава упоредо, да би се омогућило компаративно сагледавање проблематике.Узорак од 85 испитаника потврдио је полазну претпоставку анкетара да ниво информационе писмености наставника и сарадника на Универзитету у Београду треба систематски унапређивати. Но, показао је и мањак институционалне инфраструктуре (политике, сервиси, средства, репозиторијуми, процедуре), па и недостатак, односно непознавање стручне терминологије у области управљања истраживачким подацима, што све заједно директно утиче на ефективност научног процеса.


2019 ◽  
Vol 75 (1) ◽  
pp. 24-43 ◽  
Author(s):  
Polona Vilar ◽  
Vlasta Zabukovec

PurposeThe purpose of this paper is to investigate the differences between scientific disciplines (SDs) in Slovenia in research data literacy (RDL) and research data management (RDM) to form recommendations regarding how to move things forward on the institutional and national level.Design/methodology/approachPurposive sample of active researchers was used from widest possible range of SD. Data were collected from April 21 to August 7, 2017, using 24-question online survey (5 demographic, 19 content questions (single/multiple choice and Likert scale type). Bivariate (ANOVA) and multivariate methods (clustering) were used.FindingsThe authors identified three perception-related and four behavior-related connections; this gave three clusters per area. First, perceptions – skeptical group, mainly social (SocS) and natural sciences (NatS): no clear RDM and ethical issues standpoints, do not agree that every university needs a data management plan (DMP). Careful group, again including mainly SocS and NatS: RDM is problematic and linked to ethical dilemmas, positive toward institutional DMPs. Convinced group, mainly from humanities (HUM), NatS, engineering (ENG) and medicine and health sciences (MedHeS): no problems regarding RDM, agrees this is an ethical question, is positive toward institutional DMP’s. Second, behaviors – sparse group, mainly from MedHeS, NatS and HUM, some agricultural scientists (AgS), and some SocS and ENG: do not tag data sets with metadata, do not use file-naming conventions/standards. Frequent group – many ENG, SocS, moderate numbers of NatS, very few AgS and only a few MedHeS and HUM: often use file-naming conventions/standards, version-control systems, have experience with public-domain data, are reluctant to use metadata with their RD. Slender group, mainly from AgS and NatS, moderate numbers of ENG, SocS and HUM, but no MedHeS: often use public-domain data, other three activities are rare.Research limitations/implicationsResearch could be expanded to a wider population, include other stakeholders and use qualitative methods.Practical implicationsResults are useful for international comparisons but also give foundations and recommendations on institutional and national RDM and RDL policies, implementations, and how to bring academic libraries into the picture. Identified differences suggest that different educational, awareness-raising and participatory approaches are needed for each group.Originality/valueThe findings offer valuable insight into RDM and RDL of Slovenian scientists, which have not yet been investigated in Slovenia.


2016 ◽  
Vol 49 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Tibor Koltay

This paper describes data literacy and emphasizes its importance. Data literacy is vital for researchers who need to become data literate science workers and also for (potential) data management professionals. Its important characteristic is a close connection and similarity to information literacy. To support this argument, a review of literature was undertaken on the importance of data, and the data-intensive paradigm of scientific research, researchers’ expected and real behaviour, the nature of research data management, the possible roles of the academic library, data quality and data citation, Besides describing the nature of data literacy and enumerating the related skills, the application of phenomenographic approaches to data literacy and its relationship to the digital humanities have been identified as subjects for further investigation.


2019 ◽  
Vol 29 (1) ◽  
pp. 1
Author(s):  
Tom Willaert ◽  
Jacob Cottyn ◽  
Ulrike Kenens ◽  
Thomas Vandendriessche ◽  
Demmy Verbeke ◽  
...  

2018 ◽  
Vol 82 ◽  
pp. 115-130
Author(s):  
Jurgita Rudžionienė ◽  
Vincas Grigas ◽  
Heidi Enwald ◽  
Terttu Kortelainen

2018 ◽  
Author(s):  
Chealsye Bowley

This poster was presented at the Research Data and Access Preservation Summit 2018. Teaching research data management and data literacy can be a challenge. How can one know if the information is being retained and will be applied? Using game techniques and role playing can give the presenter immediate feedback on if the information regarding data management and/or data literacy is being retained, and allow students to immediately apply the information to increase their chances of retaining and using the information when conducting research.


IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 303-312 ◽  
Author(s):  
Tibor Koltay

Data governance and data literacy are two important building blocks in the knowledge base of information professionals involved in supporting data-intensive research, and both address data quality and research data management. Applying data governance to research data management processes and data literacy education helps in delineating decision domains and defining accountability for decision making. Adopting data governance is advantageous, because it is a service based on standardised, repeatable processes and is designed to enable the transparency of data-related processes and cost reduction. It is also useful, because it refers to rules, policies, standards; decision rights; accountabilities and methods of enforcement. Therefore, although it received more attention in corporate settings and some of the skills related to it are already possessed by librarians, knowledge on data governance is foundational for research data services, especially as it appears on all levels of research data services, and is applicable to big data.


Author(s):  
Fabian Cremer ◽  
Silvia Daniel ◽  
Marina Lemaire ◽  
Katrin Moeller ◽  
Matthias Razum ◽  
...  

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