Integrating domain knowledge, requirements, and specifications

1991 ◽  
Vol 1 (3-4) ◽  
pp. 283-320 ◽  
Author(s):  
W. Lewis Johnson ◽  
Martin S. Feather ◽  
David R. Harris
Keyword(s):  
Domain Knowledge ◽  
Knowledge Requirements

scholarly journals Semiautomatic Generation of Code Ontology Using ifcOWL in Compliance Checking

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yuchao Li ◽  
Qin Zhao ◽  
Yunhe Liu ◽  
Xinhong Hei ◽  
Zongjian Li
Keyword(s):  
Domain Knowledge ◽  
Engineering Construction ◽  
Semantic Web Technology ◽  
Hierarchical Relationship ◽  
Knowledge Requirements ◽  
Compliance Checking ◽  
Relationship Of ◽  
Code Compliance ◽  
Manual Review ◽  
Compliance Check

Code compliance checking is a very important step in engineering construction, but most of code compliance checking relies on manual review at present. With the development of semantic web technology, ontology can be used to represent code information and check the code automatically. However, code ontology is established manually by researchers who have sufficient domain knowledge, in which it is easy to cause poor hierarchical structure of classes. It is also possible for code ontology not being suitable for compliance check. This paper proposes a semiautomatic construction method of railway code ontology based on ifcOWL. The railway code ontology is developed by converting ifcOWL which extends semantic information of railway code. This method can ensure the completeness of the hierarchical relationship of the classes in code ontology with good scalability, which makes use of taxonomy in ifcOWL. The establishment of ontology is divided into two processes with low coupling, namely, extension and conversion, which reduces the domain knowledge requirements of the researchers. Finally, a practical specification is selected to generate a code ontology that achieves some clauses checking.

scholarly journals Data science skills and domain knowledge requirements in the manufacturing industry: A gap analysis

2021 ◽  
Vol 60 ◽  
pp. 692-706
Author(s):  
Guoyan Li ◽  
Chenxi Yuan ◽  
Sagar Kamarthi ◽  
Mohsen Moghaddam ◽  
Xiaoning Jin
Keyword(s):  
Domain Knowledge ◽  
Manufacturing Industry ◽  
Data Science ◽  
Gap Analysis ◽  
Knowledge Requirements

scholarly journals DataSite: Proactive visual data exploration with computation of insight-based recommendations

2018 ◽  
Vol 18 (2) ◽  
pp. 251-267 ◽  
Author(s):  
Zhe Cui ◽  
Sriram Karthik Badam ◽  
M Adil Yalçin ◽  
Niklas Elmqvist
Keyword(s):  
Data Analysis ◽  
Visual Analytics ◽  
Domain Knowledge ◽  
Recommendation System ◽  
User Study ◽  
Data Exploration ◽  
Server Side ◽  
Knowledge Requirements ◽  
High Knowledge ◽  
Visual Data Exploration

Effective data analysis ideally requires the analyst to have high expertise as well as high knowledge of the data. Even with such familiarity, manually pursuing all potential hypotheses and exploring all possible views is impractical. We present DataSite, a proactive visual analytics system where the burden of selecting and executing appropriate computations is shared by an automatic server-side computation engine. Salient features identified by these automatic background processes are surfaced as notifications in a feed timeline. DataSite effectively turns data analysis into a conversation between analyst and computer, thereby reducing the cognitive load and domain knowledge requirements. We validate the system with a user study comparing it to a recent visualization recommendation system, yielding significant improvement, particularly for complex analyses that existing analytics systems do not support well.

Integrating Domain Knowledge, Requirements, and Specifications

1991 ◽  
pp. 21-58
Author(s):  
W. Lewis Johnson ◽  
Martin S. Feather ◽  
David R. Harris
Keyword(s):  
Domain Knowledge ◽  
Knowledge Requirements

Mining Domain Knowledge [Requirements]

IEEE Software ◽  
2015 ◽  
Vol 32 (3) ◽  
pp. 16-19 ◽  
Author(s):  
Jane Cleland-Huang
Keyword(s):  
Domain Knowledge ◽  
Knowledge Requirements

Automated Assessment of Domain Knowledge With Online Knowledge Mapping

2006 ◽  
Author(s):  
Gregory K. W. K. Chung ◽  
Eva L. Baker ◽  
David G. Brill ◽  
Ravi Sinha ◽  
Farzad Saadat ◽  
...  
Keyword(s):  
Domain Knowledge ◽  
Knowledge Mapping ◽  
Automated Assessment

A Model for Structured Data Entry Based on Explicit Descriptional Knowledge

1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman
Keyword(s):  
Domain Knowledge ◽  
Data Entry ◽  
Knowledge Bases ◽  
Structured Data ◽  
Research Quality ◽  
Free Text ◽  
Specific Knowledge ◽  
User Input ◽  
The One ◽  
Research Quality Assessment

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

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