DESIGN OF RELIABILITY CENTRAL DATA MANAGEMENT SUBSYSTEM. VOLUME 2

1965 ◽  
Author(s):  
J. Sable
Keyword(s):  
Data Management ◽  
Central Data

scholarly journals MOSAIC – A Modular Approach to Data Management in Epidemiological Studies

2015 ◽  
Vol 54 (04) ◽  
pp. 364-371 ◽  
Author(s):  
M. Bialke ◽  
T. Bahls ◽  
C. Havemann ◽  
J. Piegsa ◽  
K. Weitmann ◽  
...  
Keyword(s):  
Cohort Studies ◽  
Data Management ◽  
Short Review ◽  
Epidemiological Studies ◽  
Data Types ◽  
Epidemiological Research ◽  
Protection Measures ◽  
Modular Software ◽  
Definition Of ◽  
Central Data

Summary Introduction: In the context of an increasing number of multi-centric studies providing data from different sites and sources the necessity for central data management (CDM) becomes undeniable. This is exacerbated by a multiplicity of featured data types, formats and interfaces. In relation to methodological medical research the definition of central data management needs to be broadened beyond the simple storage and archiving of research data. Objectives: This paper highlights typical requirements of CDM for cohort studies and registries and illustrates how orientation for CDM can be provided by addressing selected data management challenges. Methods: Therefore in the first part of this paper a short review summarises technical, organisational and legal challenges for CDM in cohort studies and registries. A deduced set of typical requirements of CDM in epidemiological research follows. Results: In the second part the MOSAIC project is introduced (a modular systematic approach to implement CDM). The modular nature of MOSAIC contributes to manage both technical and organisational challenges efficiently by providing practical tools. A short presentation of a first set of tools, aiming for selected CDM requirements in cohort studies and registries, comprises a template for comprehensive documentation of data protection measures, an interactive reference portal for gaining insights and sharing experiences, supplemented by modular software tools for generation and management of generic pseudonyms, for participant management and for sophisticated consent management. Conclusions: Altogether, work within MOSAIC addresses existing challenges in epidemiological research in the context of CDM and facilitates the standardized collection of data with pre-programmed modules and provided document templates. The necessary effort for in-house programming is reduced, which accelerates the start of data collection.

Improving Model and Data Integration Using MOSAIC as Central Data Management Platform

2014 ◽  
Vol 86 (7) ◽  
pp. 1130-1136 ◽  
Author(s):  
Robert Kraus ◽  
Sandra Fillinger ◽  
Gregor Tolksdorf ◽  
Duc H. Minh ◽  
Victor A. Merchan-Restrepo ◽  
...  
Keyword(s):  
Data Integration ◽  
Data Management ◽  
Management Platform ◽  
Data Management Platform ◽  
Central Data

scholarly journals A new hat for librarians: providing REDCap support to establish the library as a central data hub

2018 ◽  
Vol 106 (1) ◽  
Author(s):  
Kevin Read ◽  
Fred Willie Zametkin LaPolla
Keyword(s):  
Data Management ◽  
Clinical Data ◽  
Medical Center ◽  
Academic Medical Center ◽  
Data Series ◽  
Management Support ◽  
Support Unit ◽  
Data Services ◽  
Service Gap ◽  
Central Data

Background: REDCap, an electronic data capture tool, supports good research data management, but many researchers lack familiarity with the tool. While a REDCap administrator provided technical support and a clinical data management support unit provided study design support, a service gap existed.Case Presentation: Librarians with REDCap expertise sought to increase and improve usage through outreach, workshops, and consultations. In collaboration with a REDCap administrator and the director of the clinical data management support unit, the role of the library was established in providing REDCap training and consultations. REDCap trainings were offered to the medical center during the library’s quarterly data series, which served as a springboard for offering tailored REDCap support to researchers and research groups.Conclusions: Providing REDCap support has proved to be an effective way to associate the library with data-related activities in an academic medical center and identify new opportunities for offering data services in the library. By offering REDCap services, the library established strong partnerships with the Information Technology Department, Clinical Data Support Department, and Compliance Office by filling in training gaps, while simultaneously referring users back to these departments when additional expertise was required. These new partnerships continue to grow and serve to position the library as a central data hub in the institution.

scholarly journals Designing Across Borders

2000 ◽  
Vol 122 (09) ◽  
pp. 58-60
Author(s):  
Jean Thilmany
Keyword(s):  
Data Management ◽  
Computer Aided Design ◽  
Data Management System ◽  
Data Repository ◽  
Engineering Programs ◽  
Software Applications ◽  
Engineering Data ◽  
Aided Design ◽  
Design And Manufacture ◽  
Central Data

This article discusses that many companies are installing a companywide product data management (PDM) system, also known as an engineering data management system. These systems do several things, besides acting as a central data repository. Much of the data that overwhelms companies comes from engineers using a variety of software applications, such as computer-aided design, manufacturing, or engineering programs. The PDM systems manage engineering data that may come from a myriad of sources and applications but pertain to the development of one product. The chosen PDM system would have to track the design and manufacture of each part that would be assembled to form the finished printer. It would have to tell users what stage in the process each part had reached. But it would also have to serve as a virtual warehouse for all digital versions of a part and product, including older versions that could not be lost because they might be needed for reference at any time.

Integrated Monitoring in the Voordelta, The Netherlands

2016 ◽  
pp. 325-344
Author(s):  
Niels Kinneging ◽  
Meinte Blaas ◽  
Arjen Boon ◽  
Kees Borst ◽  
Gerrit Hendriksen ◽  
...  
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Google Earth ◽  
Management Approach ◽  
Integrated Monitoring ◽  
Raw Data ◽  
Team Members ◽  
Information Products ◽  
Set Up ◽  
Central Data

Monitoring of the environmental effects of a harbour extension and the compensation measures is a very complex task. The Voordelta area has high natural values, but is also of high economic importance. To implement a monitoring strategy for this area a multidisciplinary consortium has been formed, consisting of a number of institutes and companies. A central data management facility was set up for data storage and management. This chapter illustrates the data management approach using the Voordelta monitoring programme for the years 2004 to 2013. A central data management facility was set up for data storage and management. A repository gives access to raw data files to all team members. From the analysis of the raw data a number of information products have been developed and disseminated to the authorities and the public through Google Earth. It will be shown, that the presence of a strong multidisciplinary team and good collaboration is the key to success in this complex programme. The way the data have been managed supports this process enormously.

scholarly journals Toolbox for Research, or how to facilitate a central data management in small-scale research projects

2018 ◽  
Vol 16 (1) ◽  
Author(s):  
Martin Bialke ◽  
Henriette Rau ◽  
Oliver C. Thamm ◽  
Ronny Schuldt ◽  
Peter Penndorf ◽  
...  
Keyword(s):  
Data Management ◽  
Small Scale ◽  
Research Projects ◽  
Central Data
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