Knowledge Modeling in the Health Care Domain: Capturing Semantics to Bridge the Gap Between Complex Data Models and Object Models

2015 ◽  
pp. 328-338
Author(s):  
Thomas Reichherzer ◽  
John Coffey ◽  
Bilal Gonen ◽  
Irad Gillett
Keyword(s):  
Health Care ◽  
Data Models ◽  
Complex Data ◽  
Knowledge Modeling ◽  
Object Models

Model Transformations in Designing the ASSO Methodology

2011 ◽  
pp. 283-302 ◽  
Author(s):  
Elvira Locuratolo
Keyword(s):  
Formal Method ◽  
Dynamic Modelling ◽  
Data Models ◽  
Model Transformations ◽  
Conceptual Schema ◽  
Behavioural Modelling ◽  
Semantic Data ◽  
Object Models ◽  
Consistency Proofs ◽  
Formal Mapping

ASSO, an innovative conceptual methodology which combines features of database design with the formal method B, has been defined in order to ensure the flexibility of semantic data models, the efficiency of object models and design correctness. Starting from a directed acyclic graph of classes supported by semantic data models, a formal mapping generates classes supported by object models. The classes supported by semantic data models are then extended with aspects of behavioural modelling: a relationship with the B model is established and the consistency proofs of the whole schema are reduced to small obligations of B. This chapter evidences how ASSO is based on model transformations. These have been introduced with various purposes: to map semantic data models to object models, to integrate static and dynamic modelling, to link formal and informal notations and to relate the conceptual schema and the logical schema of the methodology.

scholarly journals The PlaNet Consortium: A Network of European Plant Databases Connecting Plant Genome Data in an Integrated Biological Knowledge Resource

2004 ◽  
Vol 5 (2) ◽  
pp. 184-189 ◽  
Author(s):  
H. Schoof ◽  
R. Ernst ◽  
K. F. X. Mayer
Keyword(s):  
Data Exchange ◽  
Data Representation ◽  
Data Models ◽  
Biological Data ◽  
Plant Genome ◽  
Data Sources ◽  
Direct Access ◽  
Biological Knowledge ◽  
Database Integration ◽  
Complex Data

The completion of theArabidopsisgenome and the large collections of other plant sequences generated in recent years have sparked extensive functional genomics efforts. However, the utilization of this data is inefficient, as data sources are distributed and heterogeneous and efforts at data integration are lagging behind. PlaNet aims to overcome the limitations of individual efforts as well as the limitations of heterogeneous, independent data collections. PlaNet is a distributed effort among European bioinformatics groups and plant molecular biologists to establish a comprehensive integrated database in a collaborative network. Objectives are the implementation of infrastructure and data sources to capture plant genomic information into a comprehensive, integrated platform. This will facilitate the systematic exploration ofArabidopsisand other plants. New methods for data exchange, database integration and access are being developed to create a highly integrated, federated data resource for research. The connection between the individual resources is realized with BioMOBY. BioMOBY provides an architecture for the discovery and distribution of biological data through web services. While knowledge is centralized, data is maintained at its primary source without a need for warehousing. To standardize nomenclature and data representation, ontologies and generic data models are defined in interaction with the relevant communities.Minimal data models should make it simple to allow broad integration, while inheritance allows detail and depth to be added to more complex data objects without losing integration. To allow expert annotation and keep databases curated, local and remote annotation interfaces are provided. Easy and direct access to all data is key to the project.

scholarly journals Transforming French Electronic Health Records into the Observational Medical Outcome Partnership's Common Data Model: A Feasibility Study

2020 ◽  
Vol 11 (01) ◽  
pp. 013-022 ◽  
Author(s):  
Antoine Lamer ◽  
Nicolas Depas ◽  
Matthieu Doutreligne ◽  
Adrien Parrot ◽  
David Verloop ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Health Care System ◽  
Data Models ◽  
Common Data Model ◽  
Medical Outcome ◽  
Health Records ◽  
Data Section ◽  
Electronic Health ◽  
Care System

Abstract Background Common data models (CDMs) enable data to be standardized, and facilitate data exchange, sharing, and storage, particularly when the data have been collected via distinct, heterogeneous systems. Moreover, CDMs provide tools for data quality assessment, integration into models, visualization, and analysis. The observational medical outcome partnership (OMOP) provides a CDM for organizing and standardizing databases. Common data models not only facilitate data integration but also (and especially for the OMOP model) extends the range of available statistical analyses. Objective This study aimed to evaluate the feasibility of implementing French national electronic health records in the OMOP CDM. Methods The OMOP's specifications were used to audit the source data, specify the transformation into the OMOP CDM, implement an extract–transform–load process to feed data from the French health care system into the OMOP CDM, and evaluate the final database. Results Seventeen vocabularies corresponding to the French context were added to the OMOP CDM's concepts. Three French terminologies were automatically mapped to standardized vocabularies. We loaded nine tables from the OMOP CDM's “standardized clinical data” section, and three tables from the “standardized health system data” section. Outpatient and inpatient data from 38,730 individuals were integrated. The median (interquartile range) number of outpatient and inpatient stays per patient was 160 (19–364). Conclusion Our results demonstrated that data from the French national health care system can be integrated into the OMOP CDM. One of the main challenges was the use of international OMOP concepts to annotate data recorded in a French context. The use of local terminologies was an obstacle to conceptual mapping; with the exception of an adaptation of the International Classification of Diseases 10th Revision, the French health care system does not use international terminologies. It would be interesting to extend our present findings to the 65 million people registered in the French health care system.

scholarly journals INDEED–Utilization and Cross-Sectoral Patterns of Care for Patients Admitted to Emergency Departments in Germany: Rationale and Study Design

2021 ◽  
Vol 9 ◽  
Author(s):  
Antje Fischer-Rosinský ◽  
Anna Slagman ◽  
Ryan King ◽  
Thomas Reinhold ◽  
Liane Schenk ◽  
...  
Keyword(s):  
Health Care ◽  
Emergency Departments ◽  
Outpatient Care ◽  
Large Scale ◽  
Health Care Use ◽  
Complex Data ◽  
Central Research ◽  
Hospital Data ◽  
Before And After ◽  
Research Institute

Introduction: The crowding of emergency departments (ED) has been a growing problem for years, putting the care of critically ill patients increasingly at risk. The INDEED project's overall aim is to get a better understanding of ED utilization and to evaluate corresponding primary health care use patterns before and after an ED visit while driving forward processes and methods of cross-sectoral data merging. We aim to identify adequate utilization of EDs and potentially avoidable patient contacts as well as subgroups and clusters of patients with similar care profiles.Methods: INDEED is a joint endeavor bringing together research institutions and hospitals with EDs in Germany. It is headed by the Charité–Universitätsmedizin Berlin, collaborating with Otto von Guericke University Magdeburg, Technische Universität Berlin, the Central Research Institute of Ambulatory/Outpatient Health Care in Germany (Zi), and the AOK Research Institute as part of the Federal Association of AOK, as well as experts in the technological, legal, and regulatory aspects of medical research (TMF). The Institute for Information Technology (OFFIS) was involved as the trusted third party of the project. INDEED is a retrospective study of approximately 400,000 adult patients with statutory health insurance who visited the ED of one of 16 participating hospitals in 2016. The routine hospital data contain information about treatment in the ED and, if applicable, about the subsequent hospital stay. After merging the patients' hospital data from 2016 with their outpatient billing data from 2 years before to 1 year after the ED visit (years 2014–2017), a harmonized dataset will be generated for data analyses. Due to the complex data protection challenges involved, first results will be available in 2021.Discussion: INDEED will provide knowledge on extracting and harmonizing large scale data from varying routine ED and hospital information systems in Germany. Merging these data with the corresponding outpatient care data of patients offers the opportunity to characterize the patient's treatment in outpatient care before and after ED use. With this knowledge, appropriate interventions may be developed to ensure adequate patient care and to avoid adverse events such as ED crowding.

Normalizing Multimedia Databases

2005 ◽  
pp. 408-412
Author(s):  
Shi Kuo Chang ◽  
Vincenzo Deufemia ◽  
Giuseppe Polese
Keyword(s):  
Multimedia Information ◽  
Information Management ◽  
Data Model ◽  
Query Language ◽  
Data Models ◽  
Multimedia Databases ◽  
Complex Data ◽  
Data Types ◽  
Indexing Techniques ◽  
Application Fields

Multimedia databases have been used in many application fields. As opposed to traditional alphanumeric databases, they need enhanced data models and DBMSs to enable the modeling and management of complex data types. After an initial anarchy, multimedia DBMSs (MMDBMS) have been classified based on standard issues, such as the supported data model, the indexing techniques to support content-based retrieval, the query language, the support for distributed multimedia information management, and the flexibility of their architecture (Narasimhalu, 1996).

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