scholarly journals Research on the Path of Data Literacy Cultivation for College Students

2020 ◽  
Author(s):  
Hao Liang ◽  
Wang Beibei ◽  
Shang Jun
Keyword(s):  
College Students ◽  
Data Management ◽  
Bibliometric Analysis ◽  
Literacy Education ◽  
Literacy Assessment ◽  
Data Literacy ◽  
Literacy Teaching ◽  
Data Culture ◽  
Working Out

The theoretical and practical achievements in domestic studies on data literacy are summarized by bibliometric analysis and network investigation in aspects of the connotation of data literacy, requirements of data literacy, assessment of data literacy and education of data literacy with suggestions proposed for working out the policies of data management and data literacy education, implementing the embedded data literacy education, designing the data literacy teaching contents and constructing the data culture.

scholarly journals Incremental Innovation towards Business Performance: Data Management Challenges in Healthcare Industry in Indonesia

2018 ◽  
Vol 218 ◽  
pp. 04015 ◽  
Author(s):  
Muharman Lubis ◽  
Lubis Arif Ridho ◽  
Bastian Lubis ◽  
Asmin Lubis
Keyword(s):  
Data Management ◽  
Business Performance ◽  
New Technology ◽  
Incremental Innovation ◽  
Quality Data ◽  
Data Handling ◽  
Data Ownership ◽  
Fragmented Data ◽  
Data Culture ◽  
Business Flow

The Industry 4.0 indicate the increases in competitive pressures, the margins reduction, the availability of new technology and the marketing development techniques suggest making more complex decisions to make and sustain the success. Data management is essential for organizations because the administrative process, which data is acquired, validated, stored, protected and processed through its accessibility, reliability and timeliness ensures that the needs of data are met. It is also a process of developing data architectures, practices and procedures that address the data and then implement these aspects on a regular basis. All these process will ease and smoothen the business flow. Therefore, there are number of data management challenges to maintain sheer volume of data, taking reactive approach, lack of process and data handling, fragmented data ownership and driving a data culture. This study investigate the current issues in health industry to overcome through recognizing both the importance of quality data and having more sophisticated approach to manage data as the organization begin shifting to be more data centric model.

Parental influences on Chinese literacy development: A comparison of preschoolers in Beijing, Hong Kong, and Singapore

2000 ◽  
Vol 24 (1) ◽  
pp. 82-90 ◽  
Author(s):  
Hui Li ◽  
Nirmala Rao
Keyword(s):  
Hong Kong ◽  
Language Learning ◽  
Literacy Education ◽  
Home Literacy Environment ◽  
Home Literacy ◽  
Older Children ◽  
Literacy Environment ◽  
Literacy Teaching ◽  
Character Identification ◽  
Better Than

Parents of 480 Chinese preschoolers in Beijing, Hong Kong, and Singapore reported on their involvement in literacy teaching, the home literacy environment, and their beliefs about language learning. The preschoolers, ranging in age from 2 to 6 years, completed the Preschool and Primary Chinese Literacy Scale (PPCLS), in individual sessions. Results indicated significant age and societal differences on the total PPCLS score and also on the following subscales: Character Identification, Visual and Auditory Discrimination, and Word Recognition. In all three societies, older children outperformed younger children on these subscales. Preschoolers from Hong Kong and Singapore did significantly better than those from Beijing. Despite sociocultural variations (e.g., status of the Chinese language, government directives regarding the age at which to start literacy teaching, documented goals of the preschool curriculum), which contributed to societal differences, home literacy education significantly contributed to the prediction of Chinese literacy attainment in Beijing, Hong Kong, and Singapore.

Data literacy: in search of a name and identity

2015 ◽  
Vol 71 (2) ◽  
pp. 401-415 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Data Management ◽  
Information Literacy ◽  
Academic Library ◽  
The Body ◽  
Quality Data ◽  
Content Type ◽  
Data Literacy ◽  
Body Of Knowledge ◽  
Data Citation ◽  
Close Relationship

Purpose – The role of data literacy is discussed in the light of such activities as data a quality, data management, data curation, and data citation. The differing terms and their relationship to the most important literacies are examined. The paper aims to discuss these issues. Design/methodology/approach – By stressing the importance of data literacy in fulfilling the mission of the contemporary academic library, the paper centres on information literacy, while the characteristics of other relevant literacies are also examined. The content of data literacy education is explained in the context of data-related activities. Findings – It can be concluded that there is a need for data literacy and it is advantageous to have a unified terminology. Data literacy can be offered both to researchers, who need to become data literate science workers and have the goal to educate data management professionals. Several lists of competencies contain important skills and abilities, many of them indicating the close relationship between data literacy and information literacy. It is vital to take a critical stance on hopes and fears, related to the promises of widespread ability of (big) data. Originality/value – The paper intends to be an add-on to the body of knowledge about information literacy and other literacies in the light of research data and data literacy.

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.

scholarly journals Identifying new roles for academic libraries in supporting data-intensive research

Bibliosphere ◽  
2020 ◽  
pp. 97-102 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Academic Libraries ◽  
Recent Literature ◽  
Service Providers ◽  
Literacy Education ◽  
Research Data ◽  
Service Development ◽  
Data Literacy ◽  
Intensive Research ◽  
Data Intensive ◽  
Research Data Management

Reacting to the appearance of data-intensive research prompts academic libraries to become service providers for scholars, who work with research data. Although this is an imperative for libraries worldwide, due to the differences between countries and institutions, the level of readiness to engage in related activities differs from country to country. While some of the related tasks are fairly novel, others heavily build on librarians’ traditional, well-known skills. To identify these tasks, as well as making an inventory of the required skills and abilities, this paper, based on a non-exhaustive review of the recent literature, presents both theoretical and practical issues. It is demonstrated that the most obvious directions of the service development in academic libraries to support data-intensive science are research data management, data curation, data literacy education for users, and data literacy education for librarians.

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