Towards a method of ontology population from heterogeneous sources of structured data

Author(s):  
Irina Leshcheva ◽  
Evgeny Blagov ◽  
Anastasiia Pleshkova
2020 ◽  
pp. 016555152095024
Author(s):  
Irina Leshcheva ◽  
Alena Begler

Organisations use data in different formats: Word documents, Excel spreadsheets, databases, HTML pages and so on. It is not easy to make decisions with such data due to the lack of integration between the different sources and built-in decision-making rules. Decisions can be reached with knowledge bases, which, unlike databases, make it possible to store not only objects, facts and attributes but also more sophisticated patterns such as rules and axioms. The article proposes an ontology-based method for knowledge base creation that allows for the simultaneous integration of semi-structured data sources and extendibility while remaining context independent. At the initial steps of the method, data specification should be performed with the Data Sources Ontology developed by the authors. This ontology provides data structure description that forms supportive knowledge graph. The graph’s schema should be mapped with the domain ontology to be populated. Finally, the data are inserted into the domain ontology according to the mapping rules. Manual input is needed during data specification and data-to-ontology schema mapping.


1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman

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.


1992 ◽  
Vol 31 (04) ◽  
pp. 268-274 ◽  
Author(s):  
W. Gaus ◽  
J. G. Wechsler ◽  
P. Janowitz ◽  
J. Tudyka ◽  
W. Kratzer ◽  
...  

Abstract:A system using structured reporting of findings was developed for the preparation of medical reports and for clinical documentation purposes in upper abdominal sonography, and evaluated in the course of routine use. The evaluation focussed on the following parameters: completeness and correctness of the entered data, the proportion of free text, the validity and objectivity of the documentation, user acceptance, and time required. The completeness in the case of two clinically relevant parameters could be compared with an already existing database containing freely dictated reports. The results confirmed the hypothesis that, for the description of results of a technical examination, structured data reporting is a viable alternative to free-text dictation. For the application evaluated, there is even evidence of the superiority of a structured approach. The system can be put to use in related areas of application.


1996 ◽  
Vol 35 (03) ◽  
pp. 261-264 ◽  
Author(s):  
T. Schromm ◽  
T. Frankewitsch ◽  
M. Giehl ◽  
F. Keller ◽  
D. Zellner

Abstract:A pharmacokinetic database was constructed that is as free of errors as possible. Pharmacokinetic parameters were derived from the literature using a text-processing system and a database system. A random data sample from each system was compared with the original literature. The estimated error frequencies using statistical methods differed significantly between the two systems. The estimated error frequency in the text-processing system was 7.2%, that in the database system 2.7%. Compared with the original values in the literature, the estimated probability of error for identical pharmacokinetic parameters recorded in both systems is 2.4% and is not significantly different from the error frequency in the database. Parallel data entry with a text-processing system and a database system is, therefore, not significantly better than structured data entry for reducing the error frequency.


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