Data Literacy and Research Data Management in Two Top Universities in Poland. Raising Awareness

2018 ◽  
pp. 205-214 ◽  
Author(s):  
Zuzanna Wiorogórska ◽  
Jędrzej Leśniewski ◽  
Ewa Rozkosz
Keyword(s):  
Data Management ◽  
Research Data ◽  
Data Literacy ◽  
Research Data Management ◽  
Raising Awareness

scholarly journals Информациона писменост наставника и сарадника на Универзитету у Београду

2018 ◽  
Vol 17 (32) ◽  
pp. 12
Author(s):  
Гордана Стокић Симончић ◽  
Драгана Сабовљев
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Research ◽  
Data Literacy ◽  
Research Data Management

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.

Research data management and research data literacy in Slovenian science

2019 ◽  
Vol 75 (1) ◽  
pp. 24-43 ◽  
Author(s):  
Polona Vilar ◽  
Vlasta Zabukovec
Keyword(s):  
Data Management ◽  
Online Survey ◽  
National Level ◽  
Public Domain ◽  
Research Data ◽  
Ethical Question ◽  
Valuable Insight ◽  
Content Type ◽  
Data Literacy ◽  
Research Data Management

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.

scholarly journals Data literacy for researchers and data librarians

2016 ◽  
Vol 49 (1) ◽  
pp. 3-14 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Literacy ◽  
Academic Library ◽  
Research Data ◽  
Review Of Literature ◽  
Data Literacy ◽  
Data Intensive ◽  
Research Data Management ◽  
Data Citation

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.

scholarly journals Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven

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

scholarly journals Making Sense: Talking Data Management with Researchers

2011 ◽  
Vol 6 (2) ◽  
pp. 265-273 ◽  
Author(s):  
Catharine Ward ◽  
Lesley Freiman ◽  
Sarah Jones ◽  
Laura Molloy ◽  
Kellie Snow
Keyword(s):  
Data Management ◽  
Management Practices ◽  
Ad Hoc ◽  
Research Data ◽  
Creative Commons ◽  
Digital Curation ◽  
Research Data Management ◽  
Making Sense ◽  
Raising Awareness ◽  
Technical Solutions

Incremental is one of eight projects in the JISC Managing Research Data programme funded to identify institutional requirements for digital research data management and pilot relevant infrastructure. Our findings concur with those of other Managing Research Data projects, as well as with several previous studies. We found that many researchers: (i) organise their data in an ad hoc fashion, posing difficulties with retrieval and re-use; (ii) store their data on all kinds of media without always considering security and back-up; (iii) are positive about data sharing in principle though reluctant in practice; (iv) believe back-up is equivalent to preservation. The key difference between our approach and that of other Managing Research Data projects is the type of infrastructure we are piloting. While the majority of these projects focus on developing technical solutions, we are focusing on the need for ‘soft’ infrastructure, such as one-to-one tailored support, training, and easy-to-find, concise guidance that breaks down some of the barriers information professionals have unintentionally built with their use of specialist terminology.We are employing a bottom-up approach as we feel that to support the step-by-step development of sound research data management practices, you must first understand researchers’ needs and perspectives. Over the life of the project, Incremental staff will act as mediators, assisting researchers and local support staff to understand the data management requirements within which they are expect to work, and will determine how these can be addressed within research workflows and the existing technical infrastructure.Our primary goal is to build data management capacity within the Universities of Cambridge and Glasgow by raising awareness of basic principles so everyone can manage their data to a certain extent. We will ensure our lessons can be picked up and used by other institutions. Our affiliation with the Digital Curation Centre and Digital Preservation Coalition will assist in this and all outputs will be released under a Creative Commons licence.

scholarly journals Drop out Factors in Data Literacy and Research Data Management Survey: Experiences from Lithuania and Finland

2018 ◽  
Vol 82 ◽  
pp. 115-130
Author(s):  
Jurgita Rudžionienė ◽  
Vincas Grigas ◽  
Heidi Enwald ◽  
Terttu Kortelainen
Keyword(s):  
Data Management ◽  
Research Data ◽  
Drop Out ◽  
Data Literacy ◽  
Research Data Management

Show Me the Data!

2018 ◽  
Author(s):  
Chealsye Bowley
Keyword(s):  
Data Management ◽  
Role Playing ◽  
Research Data ◽  
Immediate Feedback ◽  
Data Literacy ◽  
Research Data Management ◽  
Teaching Research ◽  
Conducting Research

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.

scholarly journals Data governance, data literacy and the management of data quality

IFLA Journal ◽  
2016 ◽  
Vol 42 (4) ◽  
pp. 303-312 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Building Blocks ◽  
Research Data ◽  
Data Governance ◽  
Data Literacy ◽  
Data Services ◽  
Data Intensive ◽  
Research Data Management ◽  
Address Data

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.

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