scholarly journals Using the Rhizomer Platform for Semantic Decision Support Systems Development

2012 ◽  
pp. 62-82
Author(s):  
Roberto García
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
User Interaction ◽  
Data Publishing ◽  
Semantic Web Technologies ◽  
Financial Reports ◽  
Semantic Data ◽  
Semantic Decision ◽  
The Cost

Decision support systems get more useful as they manage to make decisions more informed. However, the cost of information and of combining and making it available in the appropriate context make this a tricky trade-off. Fortunately, Semantic Web technologies make it possible to easily publish and reuse data. But this is not simple data, it is semantic data, which makes it easier to query, browse and combine it. Apart from semantic data, it is also important a user interface that carries all this potential to the user. Rhizomer is a framework for semantic data publishing and user interaction that facilitates building semantic dashboards. It is possible, for instance, to build a simple dashboard on top of semantic data generated from financial reports and incorporate web services that provide specialised ways to interact with semantic data, like showing geo-located resources in a map or events in a timeline.

Using the Rhizomer Platform for Semantic Decision Support Systems Development

2010 ◽  
Vol 2 (1) ◽  
pp. 60-80 ◽  
Author(s):  
Roberto García
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
User Interaction ◽  
Data Publishing ◽  
Semantic Web Technologies ◽  
Financial Reports ◽  
Semantic Data ◽  
Semantic Decision ◽  
The Cost

Decision support systems get more useful as they manage to make decisions more informed. However, the cost of information and of combining and making it available in the appropriate context make this a tricky trade-off. Fortunately, Semantic Web technologies make it possible to easily publish and reuse data. But this is not simple data, it is semantic data, which makes it easier to query, browse and combine it. Apart from semantic data, it is also important a user interface that carries all this potential to the user. Rhizomer is a framework for semantic data publishing and user interaction that facilitates building semantic dashboards. It is possible, for instance, to build a simple dashboard on top of semantic data generated from financial reports and incorporate web services that provide specialised ways to interact with semantic data, like showing geo-located resources in a map or events in a timeline.

Overview of Decision Support Systems Applied to Construction

2016 ◽  
pp. 77-94
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Markov Decision Processes ◽  
Support Systems ◽  
Decision Processes ◽  
Rule Based ◽  
Markov Decision ◽  
Knowledge Intensive ◽  
The Cost ◽  
Rule Based Systems

The domain of construction is a very knowledge-intensive domain with so many factors involved. This implies undertaking any action requires an understanding of the different factors and how best to combine them to achieve a favourable and optimal outcome. Thus decision-making has been extensively used in the domain of construction. The aim of this chapter is to undertake a review of various decision support systems and to provide insights into their applications in the domain of construction. Specifically, the principle of cost index, sub-work chaining diagram method, linear regression and cost over-runs in time-overrun context (CCOTOV) model and Markov decision processes (MDP), ontology and rule-based systems have been reviewed. Based on the review the Markov decision processes (MDP), ontology and rule-based systems were chosen as the more suitable for the cost control case considered in this study.

scholarly journals Cost and economic benefit of clinical decision support systems for cardiovascular disease prevention: a community guide systematic review

2017 ◽  
Vol 24 (3) ◽  
pp. 669-676 ◽  
Author(s):  
Verughese Jacob ◽  
Anilkrishna B Thota ◽  
Sajal K Chattopadhyay ◽  
Gibril J Njie ◽  
Krista K Proia ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Costs And Benefits ◽  
The Cost

Objective: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). Materials and Methods: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. Results: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies (n = 12) due to considerable heterogeneity. Several studies (n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. Discussion: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. Conclusion: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period.

Deploying Decision Support Systems Using Semantic Web Technologies

2012 ◽  
pp. 51-61
Author(s):  
Lars Ludwig ◽  
David O’Sullivan
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Decision Support Systems ◽  
Programming Languages ◽  
Support Systems ◽  
Web Technology ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Semantic Web Technology ◽  
Technology Industry

Decision support systems are deployed in a wide variety of business applications using a variety of core technologies and programming languages. One of the more promising technologies to evolve in recent year has been the semantic web. The semantic web aims to create more intelligent and machine readable web pages and online applications. The technologies, programming languages and methods of the semantic web are now maturing and standards have emerged that allow semantic web technology to be deployed broadly across information technology industry and the programming community in particular. This paper outlines a set of requirements for programmers considering the development of decision support systems using semantic web technology. Current strategies across the research community are surveyed that deploy semantic web applications. From the discussion of these strategies, ten basic requirements are derived. These requirements combine technological, psychological and philosophical research ideas. By crossing traditional research boundaries, a broad perspective on deploying decision support systems that utilize semantic web technologies is created.

scholarly journals Experiences in Building and Using Decision Support Systems in Postgraduate University Courses

10.28945/3084 ◽  
2007 ◽  
Author(s):  
Arthur Tatnall ◽  
Stephen Burgess
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Visual Basic ◽  
University Courses ◽  
Visual Basic For Applications ◽  
The Cost ◽  
Simple Systems

In this paper we will relate some of our experiences in building and using simple Decision Support Systems (DSS) for use in two postgraduate subjects at Victoria University in Melbourne. These subjects are not about Decision Support Systems, but are Information Systems (IS) subjects that introduce, amongst other things, concepts of decision support and DSS. It has been our experience that the complexity, an inability to examine the logic behind decisions that have been recommended, the proprietary nature and the cost of commercial DSS make their use in teaching less than ideal. Our solution was to produce our own simple systems using Excel, Visual Basic and Visual Basic for Applications, and this has proved to be quite successful. The paper reports on building and using Decision Support Systems in this way.

scholarly journals Predictive Models for Agricultural Management

2021 ◽  
Vol 12 (7) ◽  
pp. 220-225
Author(s):  
Natalia N. Bakhtadze ◽  
◽  
Evgeny M. Maximov ◽  
Natalia E. Maximova ◽  
Lamara N. Kozlovskaya
Keyword(s):  
Decision Support ◽  
Grain Yield ◽  
Decision Support Systems ◽  
Knowledge Base ◽  
Predictive Models ◽  
Agricultural Production ◽  
Support Systems ◽  
Ecological Effect ◽  
The Cost

This paper is devoted to the development of predictive models for decision support systems applied in precision farming. Application of predictive models makes it possible to use resources effectively, which reduces the cost of production and increases the efficiency of agricultural production. In addition, the forecast makes it possible to reach a long-term agronomic and ecological effect due to more careful tillage and reduced use of fertilizers. The algorithms using knowledge base for creating models of grain yield are described and the results of applying these models are presented.

Deploying Decision Support Systems Using Semantic Web Technologies

2010 ◽  
Vol 2 (1) ◽  
pp. 49-59
Author(s):  
Lars Ludwig ◽  
David O'Sullivan
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Decision Support Systems ◽  
Programming Languages ◽  
Support Systems ◽  
Web Technology ◽  
Semantic Web Technologies ◽  
Broad Perspective ◽  
Web Technologies ◽  
Semantic Web Technology

Decision support systems are deployed in a wide variety of business applications using a variety of core technologies and programming languages. One of the more promising technologies to evolve in recent year has been the semantic web. The semantic web aims to create more intelligent and machine readable web pages and online applications. The technologies, programming languages and methods of the semantic web are now maturing and standards have emerged that allow semantic web technology to be deployed broadly across information technology industry and the programming community in particular. This paper outlines a set of requirements for programmers considering the development of decision support systems using semantic web technology. Current strategies across the research community are surveyed that deploy semantic web applications. From the discussion of these strategies, ten basic requirements are derived. These requirements combine technological, psychological and philosophical research ideas. By crossing traditional research boundaries, a broad perspective on deploying decision support systems that utilize semantic web technologies is created.

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