Krankenhausdaten-Management der Universitäts-Augenklinik Graz - Hospital Data Management at the University of Graz Eye Hospital

2000 ◽  
Vol 45 (5) ◽  
pp. 126-130
Author(s):  
H. Zenz ◽  
J. Faulborn ◽  
Chr. Faschinger
Keyword(s):  
Data Management ◽  
Hospital Data ◽  
The University

scholarly journals Archiving South African digital research data: How ready are we?

2016 ◽  
Vol Volume 112 (Number 7/8) ◽  
Author(s):  
Margaret M. Koopman ◽  
Karin de Jager ◽  
◽  
Keyword(s):  
Data Management ◽  
South African ◽  
Academic Research ◽  
Research Data ◽  
Digital Data ◽  
Systematic Research ◽  
Data Archiving ◽  
Research Data Management ◽  
The University ◽  
Digital Research

Abstract Digital data archiving and research data management have become increasingly important for institutions in South Africa, particularly after the announcement by the National Research Foundation, one of the principal South African academic research funders, recommending these actions for the research that they fund. A case study undertaken during the latter half of 2014, among the biological sciences researchers at a South African university, explored the state of data management and archiving at this institution and the readiness of researchers to engage with sharing their digital research data through repositories. It was found that while some researchers were already engaged with digital data archiving in repositories, neither researchers nor the university had implemented systematic research data management.

scholarly journals From Project to Strategic Vision: Taking the Lead in Research Data Management Support at the University of Sydney Library

2014 ◽  
Vol 9 (1) ◽  
pp. 253-262 ◽  
Author(s):  
Belinda Norman ◽  
Kate Valentine Stanton
Keyword(s):  
Data Management ◽  
Research Data ◽  
Management Support ◽  
Policy And Practice ◽  
Roles And Responsibilities ◽  
Strategic Vision ◽  
Research Data Management ◽  
The Commons ◽  
The University ◽  
Project Partner

This paper explores three stories, each occurring a year apart, illustrating an evolution toward a strategic vision for Library leadership in supporting research data management at the University of Sydney. The three stories describe activities undertaken throughout the Seeding the Commons project and beyond, as the establishment of ongoing roles and responsibilities transition the Library from project partner to strategic leader in the delivery of research data management support. Each story exposes key ingredients that characterise research data management support: researcher engagement; partnerships; and the complementary roles of policy and practice.

scholarly journals A Collaborative Framework for Data Management Services: The Experience of the University of California

2012 ◽  
Vol 1 (2) ◽  
pp. 109-114 ◽  
Author(s):  
Joan Starr ◽  
Perry Willett ◽  
Lisa Federer ◽  
Claudia Horning ◽  
Mary Bergstrom
Keyword(s):  
Data Management ◽  
University Of California ◽  
The University ◽  
Management Services

ML-Enabled Informed Intervention for Crowdsourcing-Based Optimization of Medical Resources

2022 ◽  
pp. 291-315
Author(s):  
Irfan Siddavatam ◽  
Ashwini Dalvi ◽  
Abhishek Patel ◽  
Aditya Panchal ◽  
Aditya S. Vedpathak ◽  
...  
Keyword(s):  
Data Management ◽  
Patient Data ◽  
Hospital Data ◽  
Healthcare Resources ◽  
Medical Resources ◽  
Demand And Supply ◽  
Cooperative Approach ◽  
Open Mind ◽  
Medical Emergencies ◽  
Technology Assistance

It is said that every adversity presents the opportunity to grow. The current pandemic is a lesson to all healthcare infrastructure stakeholders to look at existing setups with an open mind. This chapter's proposed solution offers technology assistance to manage patient data effectively and extends the hospital data management system's capability to predict the upcoming need for healthcare resources. Further, the authors intend to supplement the proposed solution with crowdsourcing to meet hospital demand and supply for unprecedented medical emergencies. The proposed approach would demonstrate its need in the current pandemic scenario and prepare the healthcare infrastructure with a more streamlined and cooperative approach than before.

Personal Cloud System for Hospital Data Management to Store COVID-19 Patients Records

2021 ◽  
pp. 49-77
Author(s):  
Mousmi Ajay Chaurasia ◽  
Mohammed Usamah Moin ◽  
Syed Azeem Uddin ◽  
Mohammed Abdul Shoaib
Keyword(s):  
Data Management ◽  
Cloud System ◽  
Hospital Data

scholarly journals Managing Data Persistence in Network Enabled Servers

2005 ◽  
Vol 13 (4) ◽  
pp. 333-354 ◽  
Author(s):  
Eddy Caron ◽  
Bruno DelFabbro ◽  
Frédéric Desprez ◽  
Emmanuel Jeannot ◽  
Jean-Marc Nicod
Keyword(s):  
Data Management ◽  
Experimental Results ◽  
Model Data ◽  
Client Server ◽  
University Of Tennessee ◽  
Communication Time ◽  
Data Persistence ◽  
Remote Client ◽  
The University ◽  
Global Grid

The GridRPC model [17] is an emerging standard promoted by the Global Grid Forum (GGF) that defines how to perform remote client-server computations on a distributed architecture. In this model data are sent back to the client at the end of every computation. This implies unnecessary communications when computed data are needed by an other server in further computations. Since, communication time is sometimes the dominant cost of remote computations, this cost has to be lowered. Several tools instantiate the GridRPC model such as NetSolve developed at the University of Tennessee, Knoxville, USA, and DIET developed at LIP laboratory, ENS Lyon, France. They are usually called Network Enabled Servers (NES). In this paper, we present a discussion of the data management solutions chosen for these two NES (NetSolve and DIET) as well as experimental results.

scholarly journals A semi-automated pipeline for fulfillment of resource requests from a longitudinal Alzheimer's disease registry

JAMIA Open ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 516-520
Author(s):  
Katelyn A McKenzie ◽  
Suzanne L Hunt ◽  
Genevieve Hulshof ◽  
Dinesh Pal Mudaranthakam ◽  
Kayla Meyer ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Data Management ◽  
Reproducible Research ◽  
University Of Kansas ◽  
Data Set ◽  
Data Accessibility ◽  
Monthly Data ◽  
Variable List ◽  
The University

Abstract Objective Managing registries with continual data collection poses challenges, such as following reproducible research protocols and guaranteeing data accessibility. The University of Kansas (KU) Alzheimer’s Disease Center (ADC) maintains one such registry: Curated Clinical Cohort Phenotypes and Observations (C3PO). We created an automated and reproducible process by which investigators have access to C3PO data. Materials and Methods Data was input into Research Electronic Data Capture. Monthly, data part of the Uniform Data Set (UDS), that is data also collected at other ADCs, was uploaded to the National Alzheimer’s Coordinating Center (NACC). Quarterly, NACC cleaned, curated, and returned the UDS to the KU Data Management and Statistics (DMS) Core, where it was stored in C3PO with other quarterly curated site-specific data. Investigators seeking to utilize C3PO submitted a research proposal and requested variables via the publicly accessible and searchable data dictionary. The DMS Core used this variable list and an automated SAS program to create a subset of C3PO. Results C3PO contained 1913 variables stored in 15 datasets. From 2017 to 2018, 38 data requests were completed for several KU departments and other research institutions. Completing data requests became more efficient; C3PO subsets were produced in under 10 seconds. Discussion The data management strategy outlined above facilitated reproducible research practices, which is fundamental to the future of research as it allows replication and verification to occur. Conclusion We created a transparent, automated, and efficient process of extracting subsets of data from a registry where data was changing daily.

Data Management at the University of Iowa: A University Libraries Report on Campus Research Data Needs

2020 ◽  
Author(s):  
Shawn Averkamp ◽  
Xiaomei Gu ◽  
Ben Rogers
Keyword(s):  
Data Collection ◽  
Data Management ◽  
Data Storage ◽  
Analysis Data ◽  
Data Publishing ◽  
Second Phase ◽  
Sensitive Data ◽  
University Of Iowa ◽  
Challenges And Opportunities ◽  
The University

<p>This data management report was commissioned by the University of Iowa Libraries with the intention of performing a survey of the campus landscape and identifying gaps in data management services. The first stage of data collection consisted of a survey conducted during summer 2012 to which 784 responses were received. The second phase of data collection consisted of approximately 40 in-depth interviews with individuals from the campus and were completed during summer 2013. Findings are presented as challenges and opportunities within five broad areas of data management: data management planning, data storage, data organization and analysis, data publishing and dissemination and sensitive data and compliance, with additional findings reported in the areas of research culture and funding models.</p>

scholarly journals EVALUASI MANAJEMEN KESELAMATAN PADA PUSAT DATA (STUDI KASUS PERGURUAN TINGGI XYZ)

2017 ◽  
Vol 1 (3) ◽  
pp. 145
Author(s):  
Aniq Noviciatie Ulfah ◽  
Wing Wahyu Winarno
Keyword(s):  
Adverse Effects ◽  
Data Management ◽  
Data Security ◽  
Data Center ◽  
Safety Management ◽  
Data Distribution ◽  
Maturity Level ◽  
Storage Media ◽  
A Value ◽  
The University

Data center was developed related to data security as one of the assets of the organization in addressing the data management for operational purposes as secondary storage media and data distribution. Safety management is part of the framework of the data center that should be assessed by the manager to determine whether compliance with the standards so as to minimize the likelihood of the risk of adverse effects on the organization. This prompted the University XYZ to evaluate the safety management to determine the extent of the implementation of safety management in the data center in their environtment. In evaluating the safety management of the data center in the University XYZ is using the standard ISO 22301: 2012. ISO 22301 is a standard that specifically to plan, establish, implement, operate, monitor, review, maintain and improve a documented management system to protect or reduce the possibility of the risk, be on the alert, handle and recover the time of the incident. The sources of data was obtained from 9 respondents who are heads / staff from each division in the data center University XYZ. The data that have been obtained will be used to measure the maturity level of each clause of the ISO 22301: 2012 and as an evaluation tools. The results obtained in this study indicate that the University XYZ has been implementing safety management in the data center with a value for each clause 5, 6, 7, 8, and 9 are sequential ie 2:42, 2:41, 1:21, 1.67, and 1.65.

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