A Framework for Semi-automatic Data Integration

2009 ◽  
pp. 46-60
Author(s):  
Paolo Ceravolo ◽  
Zhan Cui ◽  
Ernesto Damiani ◽  
Alex Gusmini ◽  
Marcello Leida
Keyword(s):  
Data Integration ◽  
Automatic Data

Distributed mashups: a collaborative approach to data integration

2015 ◽  
Vol 11 (3) ◽  
pp. 370-396 ◽  
Author(s):  
Tuan-Dat Trinh ◽  
Peter Wetz ◽  
Ba-Lam Do ◽  
Elmar Kiesling ◽  
A Min Tjoa
Keyword(s):  
Data Integration ◽  
Data Processing ◽  
User Study ◽  
Heterogeneous Data ◽  
Visual Programming ◽  
Data Sources ◽  
Time Data ◽  
Semantic Web Technologies ◽  
Automatic Data ◽  
Content Type

Purpose – This paper aims to present a collaborative mashup platform for dynamic integration of heterogeneous data sources. The platform encourages sharing and connects data publishers, integrators, developers and end users. Design/methodology/approach – This approach is based on a visual programming paradigm and follows three fundamental principles: openness, connectedness and reusability. The platform is based on semantic Web technologies and the concept of linked widgets, i.e. semantic modules that allow users to access, integrate and visualize data in a creative and collaborative manner. Findings – The platform can effectively tackle data integration challenges by allowing users to explore relevant data sources for different contexts, tackling the data heterogeneity problem and facilitating automatic data integration, easing data integration via simple operations and fostering reusability of data processing tasks. Research limitations/implications – This research has focused exclusively on conceptual and technical aspects so far; a comprehensive user study, extensive performance and scalability testing is left for future work. Originality/value – A key contribution of this paper is the concept of distributed mashups. These ad hoc data integration applications allow users to perform data processing tasks in a collaborative and distributed manner simultaneously on multiple devices. This approach requires no server infrastructure to upload data, but rather allows each user to keep control over their data and expose only relevant subsets. Distributed mashups can run persistently in the background and are hence ideal for real-time data monitoring or data streaming use cases. Furthermore, we introduce automatic mashup composition as an innovative approach based on an explicit semantic widget model.

Data Integration of CAD, CAE with CAM for Composite Structures

2010 ◽  
Vol 139-141 ◽  
pp. 1294-1298
Author(s):  
Li Hua Zhang
Keyword(s):  
Data Integration ◽  
Fiber Orientation ◽  
Composite Structures ◽  
Manufacturing Systems ◽  
Data Transfer ◽  
Final State ◽  
Element Mesh ◽  
Orientation Data ◽  
Automatic Data ◽  
Automatic Mapping

Digital composite structures definition is the basis for the data integration of CAD, CAE and CAM for composite structures. The key of digital composite structures definition is the modeling of material structures. In this paper the procedure of material structures modeling and contents of laminate lay-up definition data have been summarized briefly. Today composite structures can not be analyzed with true fiber orientations. True fiber orientations of discrete triangle elements have been used to approximate the final state of ply fibers and a XML file has been used to describe laminate lay-up definition data. Furthermore, automatic mapping of fiber orientation data to the finite element mesh based on user specified tolerances has been used to obtain the automatic data transfer from CAD software to CAE software. Finally, the data integration of the CAD software with two manufacturing systems has been presented.

scholarly journals An Integrative Clinical Database and Diagnostics Platform for Biomarker Identification and Analysis in Ion Mobility Spectra of Human Exhaled Air

2013 ◽  
Vol 10 (2) ◽  
pp. 35-47 ◽  
Author(s):  
Till Schneider ◽  
Anne-Christin Hauschild ◽  
Jörg Ingo Baumbach ◽  
Jan Baumbach
Keyword(s):  
Data Integration ◽  
High Throughput ◽  
Ion Mobility ◽  
Data Retrieval ◽  
Clear Understanding ◽  
Human Breath ◽  
Automatic Data ◽  
Biomarker Identification ◽  
Exhaled Air ◽  
Automated Data Integration

Summary Over the last decade the evaluation of odors and vapors in human breath has gained more and more attention, particularly in the diagnostics of pulmonary diseases. Ion mobility spectrometry coupled with multi-capillary columns (MCC/IMS), is a well known technology for detecting volatile organic compounds (VOCs) in air. It is a comparatively inexpensive, non-invasive, high-throughput method, which is able to handle the moisture that comes with human exhaled air, and allows for characterizing of VOCs in very low concentrations. To identify discriminating compounds as biomarkers, it is necessary to have a clear understanding of the detailed composition of human breath. Therefore, in addition to the clinical studies, there is a need for a flexible and comprehensive centralized data repository, which is capable of gathering all kinds of related information. Moreover, there is a demand for automated data integration and semi-automated data analysis, in particular with regard to the rapid data accumulation, emerging from the high-throughput nature of the MCC/IMS technology. Here, we present a comprehensive database application and analysis platform, which combines metabolic maps with heterogeneous biomedical data in a well-structured manner. The design of the database is based on a hybrid of the entity-attribute- value (EAV) model and the EAV-CR, which incorporates the concepts of classes and relationships. Additionally it offers an intuitive user interface that provides easy and quick access to the platform’s functionality: automated data integration and integrity validation, versioning and roll-back strategy, data retrieval as well as semi-automatic data mining and machine learning capabilities. The platform will support MCC/IMS-based biomarker identification and validation. The software, schemata, data sets and further information is publicly available at http://imsdb.mpi-inf.mpg.de.

LinksB2N: Automatic Data Integration for the Semantic Web

2009 ◽  
pp. 1121-1138 ◽  
Author(s):  
Manuel Salvadores ◽  
Gianluca Correndo ◽  
Bene Rodriguez-Castro ◽  
Nicholas Gibbins ◽  
John Darlington ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Integration ◽  
Automatic Data

scholarly journals Post-operative deep brain stimulation assessment: Automatic data integration and report generation

2018 ◽  
Vol 11 (4) ◽  
pp. 863-866 ◽  
Author(s):  
Andreas Husch ◽  
Mikkel V. Petersen ◽  
Peter Gemmar ◽  
Jorge Goncalves ◽  
Niels Sunde ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Data Integration ◽  
Brain Stimulation ◽  
Report Generation ◽  
Automatic Data ◽  
Deep Brain
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