A Survey on the Semi-Structured Data Models

2011 ◽  
pp. 257-266 ◽  
Author(s):  
Supriya Chakraborty ◽  
Nabendu Chaki
Keyword(s):  
Data Models ◽  
Structured Data

Representation of Map Objects with Semi-Structured Data Models

2002 ◽  
pp. 547-562 ◽  
Author(s):  
Emmanuel Stefanakis
Keyword(s):  
Data Models ◽  
Structured Data ◽  
Map Objects

Representation of Generalized Map Series Using Semi-Structured Data Models

2003 ◽  
Vol 30 (1) ◽  
pp. 51-68 ◽  
Author(s):  
Emmanuel Stefanakis
Keyword(s):  
Data Models ◽  
Structured Data ◽  
Map Series

scholarly journals Structured Data for Performing Arts History: An Introduction to a Special Issue of Data Papers

2020 ◽  
Vol 5 (2) ◽  
pp. 1-12
Author(s):  
Thunnis van Oort ◽  
Julia Noordegraaf
Keyword(s):  
Social Sciences ◽  
Performing Arts ◽  
Research Data ◽  
Data Models ◽  
Structured Data ◽  
Data Sets ◽  
Special Issue ◽  
Humanities And Social Sciences

Abstract This introduction to the special issue of performing arts data papers starts off by dwelling on the purpose of the (re-)use of structured data for performing arts history, and on the benefits of publishing data papers about these data sets. The authors present several observations on the general characteristics of data models in this scholarly domain and conclude by discussing each of the contributions to this special issue of the Research Data Journal for the Humanities and Social Sciences.

An interdisciplinary ocean prediction system: Assimilation strategies ana structured data models

1996 ◽  
pp. 413-452 ◽  
Author(s):  
Carlos J. Lozano ◽  
Allan R. Robinson ◽  
Hernan G. Arango ◽  
Avijit Gangopadhyay ◽  
Quinn Sloan ◽  
...  
Keyword(s):  
Data Models ◽  
Structured Data ◽  
Prediction System ◽  
Ocean Prediction

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.

Structured Reporting of Medical Findings: Evaluation of a System in Gastroenterology

1992 ◽  
Vol 31 (04) ◽  
pp. 268-274 ◽  
Author(s):  
W. Gaus ◽  
J. G. Wechsler ◽  
P. Janowitz ◽  
J. Tudyka ◽  
W. Kratzer ◽  
...  
Keyword(s):  
Structured Data ◽  
Structured Reporting ◽  
Free Text ◽  
Clinical Documentation ◽  
Abdominal Sonography ◽  
Technical Examination ◽  
Medical Reports ◽  
Time Required ◽  
Upper Abdominal ◽  
Structured Approach

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.

Structured Data Entry for Reliable Acquisition of Pharmacokinetic Data

1996 ◽  
Vol 35 (03) ◽  
pp. 261-264 ◽  
Author(s):  
T. Schromm ◽  
T. Frankewitsch ◽  
M. Giehl ◽  
F. Keller ◽  
D. Zellner
Keyword(s):  
Text Processing ◽  
Data Entry ◽  
Processing System ◽  
Database System ◽  
Structured Data ◽  
Pharmacokinetic Parameters ◽  
Pharmacokinetic Data ◽  
Probability Of Error ◽  
Error Frequency ◽  
Estimated Error

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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