Total quality information management. Environmental data on-line: EPA's on-line services

1992 ◽  
Vol 1 (3) ◽  
pp. 283-294
Author(s):  
Chris FitzGerald
2012 ◽  
Vol 41 ◽  
pp. 1708-1713 ◽  
Author(s):  
Noor Azlina Mohd. Salleh ◽  
Salmiah Kasolang ◽  
Ahmed Jaffar

2007 ◽  
Vol 2 (2) ◽  
pp. 217 ◽  
Author(s):  
M. Sakthivel ◽  
S.R. Devadasan ◽  
S. Vinodh ◽  
A. Ramesh ◽  
S. Shyamsundar

Dependability ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 3-9 ◽  
Author(s):  
I. S. Shubinsky ◽  
A. M. Zamyshliaev ◽  
L. P. Papi

The paper examines the reliability of an information management system as its ability to provide the required services that can be justifiably trusted. It is assumed that the system functions without an operator. The aim is to ensure the dependability of a multimodule control system, when the problem-solving results are affected by failures, faults and errors of problem-solution by the system’s computation modules (CMs). Conventional fault tolerance methods do not provide the desired effect, as even under infinite structural redundancy yet real capabilities of on-line detection of CM failures or faults the system’s dependability is significantly lower than expected. The paper proposes and evaluates the methods of adaptive dependability. They are to ensure the observability of control systems under limited capabilities of component CM operability supervision, as well as achieving the required levels of dependability of information management systems in cases of insignificant float time and structural redundancy. These goals are achieved through active (and automatic) reassignment of the available computational resources for on-line information processing. The methods of adaptive dependability enable – with no interruption of computational processes and while solving real-world problems – timely automatic detection and elimination of failures, faults of CMs and errors in the solution of specified problems through on-line localization of faulty modules and subsequent automatic reconfiguration of the system with the elimination of such modules from operation.


Data quality is a main issue in quality information management. Data quality problems occur anywhere in information systems. These problems are solved by Data Cleaning (DC). DC is a process used to determine inaccurate, incomplete or unreasonable data and then improve the quality through correcting of detected errors and omissions. Various process of DC have been discussed in the previous studies, but there is no standard or formalized the DC process. The Domain Driven Data Mining (DDDM) is one of the KDD methodology often used for this purpose. This paper review and emphasize the important of DC in data preparation. The future works was also being highlight.


2020 ◽  
Vol 7 (4) ◽  
pp. 512-527 ◽  
Author(s):  
Botao Zhong ◽  
Haitao Wu ◽  
Lieyun Ding ◽  
Hanbin Luo ◽  
Ying Luo ◽  
...  

2020 ◽  
Vol 11 (6) ◽  
pp. 1175-1206 ◽  
Author(s):  
Rodrigo de Castro Freitas ◽  
Maria do Carmo Duarte Freitas

Purpose Lean office covers the improvement of administrative processes and information flows. In offices, one of the essential challenges is to coordinate the development of information management capabilities. Thus, this paper aims to identify the key factors of information management in lean office deployment contexts. Design/methodology/approach By adopting a qualitative approach, it consists of theoretical research that applies grounded theory's coding technique and exploits 27 scientific studies on lean office published in the past 20 years. Findings It identifies five key factors for managing information into an organizational structure that optimizes information flow, such as “information-seeking,” “access to information,” “information quality,” “information processing” and “use of information and communication technology”. Research limitations/implications Data analysis was restricted in scientific research regarding lean office deployment. Therefore, the accuracy of the concepts and categories of information management proposed in this paper can be adjusted and validated in future research, thus deepening the discussion of its findings. Practical implications It highlights issues for managing information in contemporary organizations such as failures in information retrieval, restrictions on access to information, lack of quality information, inadequate information processing criteria and inefficiency of information systems infrastructure. Originality/value It analyzes the lean office deployment from the theoretical framework of information management. Thus, it differs from other studies in this field because it is not limited to the operational aspects of lean management. Nevertheless, it shows that lean office reconfigures information flows and continually improves organizations’ strategic management.


1993 ◽  
Vol 19 (4) ◽  
pp. 259-265 ◽  
Author(s):  
John R. Brockman

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