Support methods for requirement identification of information systems using expert knowledge

2002 ◽  
Author(s):  
S. Soga ◽  
T. Ohkawa ◽  
N. Komoda
Keyword(s):  
Information Systems ◽  
Expert Knowledge ◽  
Support Methods

scholarly journals A Case Studies Approach to the Analysis of Profiling and Framing Structures for Pervasive Information Systems

2012 ◽  
Vol 4 (2) ◽  
pp. 1-18 ◽  
Author(s):  
José Eduardo Fernandes ◽  
Ricardo J. Machado ◽  
João Á. Carvalho
Keyword(s):  
Information Systems ◽  
Case Studies ◽  
Software Design ◽  
Expert Knowledge ◽  
Structural Approach ◽  
Technological Changes ◽  
Design And Development ◽  
Structure Approach ◽  
Model Based ◽  
Widespread Adoption

Model-Based/Driven Development (MDD) constitutes an approach to software design and development that potentially contributes to: concepts closer to domain and reduction of semantic gaps, automation and less sensitivity to technological changes, and the capture of expert knowledge and reuse. The widespread adoption of pervasive technologies as basis for new systems and applications lead to the need of effectively design pervasive information systems that properly fulfil the goals they were designed for. This paper presents a profiling and framing structure approach for the development of Pervasive Information Systems (PIS). This profiling and framing structure allows the organization of the functionality that can be assigned to computational devices in a system and of the corresponding development structures and models, being. The proposed approach enables a structural approach to PIS development. The paper also presents two case studies that allowed demonstrating the applicability of the approach.

Understanding Based Managing Support Systems

2010 ◽  
pp. 91-102
Author(s):  
Lidia Ogiela ◽  
Ryszard Tadeusiewicz ◽  
Marek R. Ogiela
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Semantic Analysis ◽  
Support Systems ◽  
Expert Knowledge ◽  
Management Support ◽  
Economic Data ◽  
Economic Information ◽  
Management Support Systems ◽  
Intelligent Information

This publication presents cognitive systems designed for analysing economic data. Such systems have been created as the next step in the development of classical DSS systems (Decision Support Systems), which are currently the most widespread tools providing computer support for economic decision-making. The increasing complexity of decision-making processes in business combined with increasing demands that managers put on IT tools supporting management cause DSS systems to evolve into intelligent information systems. This publication defines a new category of systems - UBMSS (Understanding Based Management Support Systems) which conduct in-depth analyses of data using on an apparatus for linguistic and meaning-based interpretation and reasoning. This type of interpretation and reasoning is inherent in the human way of perceiving the world. This is why the authors of this publication have striven to perfect the scope and depth of computer interpretation of economic information based on human processes of cognitive data analysis. As a result, they have created UBMSS systems for the automatic analysis and interpretation of economic data. The essence of the proposed approach to the cognitive analysis of economic data is the use of the apparatus for the linguistic description of data and for semantic analysis. This type of analysis is based on expectations generated automatically by a system which collects resources of expert knowledge, taking into account the information which can significantly characterise the analysed data. In this publication, the processes of classical data description and analysis are extended to include cognitive processes as well as reasoning and forecasting mechanisms. As a result of the analyses shown, we will present a new class of UBMSS cognitive economic information systems which automatically perform a semantic analysis of business data.

scholarly journals ISExpertNet: Facilitating Knowledge Sharina in the Information Systems Academic Community

10.28945/2888 ◽  
2005 ◽  
Author(s):  
Dennis Viehland
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Communities Of Practice ◽  
Community Of Practice ◽  
Expert Knowledge ◽  
Academic Community ◽  
Future Research ◽  
Global Information ◽  
Expert Network ◽  
Global Information Systems

In this study the global Information Systems academic community is viewed as a community of practice in which knowledge is resident but inadequately shared. The article begins by examining the application of knowledge management in communities of practice, especially the knowledge needs of shared work practitioners and conditions that facilitate knowledge sharing. The central part of the paper proposes an Information Systems Expert Network (ISExpertNet) as a solution for the global IS academic community to use in sharing expert knowledge. Especially, appropriate incentives to encourage knowledge contributions and operations of ISExpertNet are discussed. The article concludes by offering several suggestions for future research and development of ISExpertNet.

New venture planning using advanced information systems support

2001 ◽  
Vol 4 (2) ◽  
pp. 43-56
Author(s):  
Dorothy G. Dologite ◽  
Robert J. Mockler ◽  
Marc E. Gartenfeld
Keyword(s):  
Information Systems ◽  
Business Strategy ◽  
Expert Knowledge ◽  
New Venture ◽  
Knowledge Based Systems ◽  
Strategy Formulation ◽  
Research Project ◽  
Knowledge Based

This article describes a research project answering the question "Can advanced information systems, such as expert knowledge-based systems help in business strategy formulation?"

Land Evaluation - An Artificial Intelligence Approach

2001 ◽  
pp. 158-166
Author(s):  
G. Tsoumakas ◽  
I. Vlahavas
Keyword(s):  
Artificial Intelligence ◽  
Land Use ◽  
Information Systems ◽  
Expert Systems ◽  
Intelligent System ◽  
Expert Knowledge ◽  
Land Evaluation ◽  
Geographical Information ◽  
Machine Learning Techniques ◽  
Land Resource

A major environmental concern of today’s scientists is the inefficient exploitation of natural resources. The land is the ultimate source of wealth and the foundation on which civilization is constructed. Inappropriate land use, leads to destruction of the land resource, poverty and other social problems, and even to the destruction of civilization. To avoid such phenomena, land evaluation is employed, for rational land use planning and appropriate and sustainable use of natural and human resources (Rossiter, 1994). The management of land use is an interdisciplinary activity that relies on large amounts of information from different sources. Land evaluators need to collect information from soil surveyors, climatologists and census takers on land resource. They also need the expert knowledge of soil scientists, agronomists and economists on land use. In addition, land evaluators must select and apply the most appropriate analytical methods to evaluate land qualities and to combine these into overall physical and/or economic suitability. This evaluation is then calibrated against expert judgement and related experience. Finally they must present the results of the evaluation with reports and maps. This output has to be dynamic, considering the continuous refinement of the whole land evaluation process. The above characteristics of land evaluation denote that the management of such a process definitely requires the support of computer systems, especially expert systems, remote sensing and image processing systems, and geographical information systems (GIS). Such systems exist, but they are usually stand-alone units, hence human intervention (land evaluators) for the flow of information from one system towards the other is indispensable. Therefore, integrated systems are highly desirable. The latest research and development trends in this area progressively encompass Artificial Intelligence (AI) techniques to a greater extent, in order to achieve an optimal performance in the analysis of the vast geographical data. Expert systems were included early on, in an effort to model the domain knowledge of land evaluation from experts. Now, such systems introduce fuzzy logic to cope with uncertainty within the data sources and the inference procedure. Machine learning techniques are also included to model the land evaluation procedures when expert knowledge is insufficient or even absent. In general, there exists an amount of both symbolic and non-symbolic AI techniques, which scientists are keen on combining and integrating with traditional land information systems. This chapter is structured as follows. An overview of three of the most used AI techniques in land evaluation problems is given. Following that, the next section introduces ISLE (Tsoumakas and Vlahavas, 1999), an Intelligent System for Land Evaluation that is designed as a framework for the integration of AI techniques with a geographical information system. The final section discusses conclusions and future trends in this field.

scholarly journals Mapping and Analysing Potential Sources and Transmission Routes of Antimicrobial Resistant Organisms in the Environment using Geographic Information Systems—An Exploratory Study

Antibiotics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 16
Author(s):  
Carlos Chique ◽  
John Cullinan ◽  
Brigid Hooban ◽  
Dearbhaile Morris
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Spatial Data ◽  
Exploratory Study ◽  
Expert Knowledge ◽  
Spatial Dimension ◽  
Geographic Information ◽  
Sampling Locations ◽  
Increased Risk ◽  
Potential Sources

Antimicrobial resistance (AMR) is one of the leading threats to human health worldwide. The identification of potential sources of antimicrobial resistant organisms (AROs) and their transmission routes in the environment is important for improving our understanding of AMR and to inform and improve policy and monitoring systems, as well as the identification of suitable sampling locations and potential intervention points. This exploratory study uses geographic information systems (GIS) to analyse the spatial distribution of likely ARO sources and transmission routes in four local authority areas (LAAs) in Ireland. A review of relevant spatial data in each LAA, grouped into themes, and categorised into sources and transmission routes, was undertaken. A range of GIS techniques was used to extract, organise, and collate the spatial data into final products in the form of thematic maps for visual and spatial analysis. The results highlight the location of ‘clusters’ at increased risk of harbouring AMR in each LAA. They also demonstrate the relevance of aquatic transmission routes for ARO mobility and risk of human exposure. The integration of a GIS approach with expert knowledge of AMR is shown to be a useful tool to gain insights into the spatial dimension of AMR and to guide sampling campaigns and intervention points.

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