scholarly journals UNIVERSITY IS ARCHITECTURE FOR THE RESEARCH EVALUATION SUPPORT

2017 ◽  
Vol 2 ◽  
pp. 112 ◽  
Author(s):  
Laila Niedrite ◽  
Darja Solodovnikova
Keyword(s):  
Information System ◽  
Data Integration ◽  
Data Quality ◽  
Research Evaluation ◽  
Common View ◽  
Research Activities ◽  
Data Integration System ◽  
Computation Formula ◽  
Integration Problems ◽  
Different Sources

The measuring of research results can be used in different ways e.g. for assignment of research grants and afterwards for evaluation of project’s results. It can be used also for recruiting or promoting research institutions’ staff. Because of a wide usage of such measurement, the selection of appropriate measures is important. At the same time there does not exist a common view which metrics should be used in this field, moreover many existing metrics that are widely used are often misleading due to different reasons, e.g. computed from incomplete or faulty data, the metric’s computation formula may be invalid or the computation results can be interpreted wrongly. To produce a good framework for research evaluation, the mentioned problems must be solved in the best possible way by integrating data from different sources to get comprehensive view of academic institutions’ research activities and to solve data quality problems. We will present a data integration system that integrates university information system with library information system and with data that are gathered through API from Scopus and Web of Science databases. Data integration problems and data quality problems that we have faced are described and possible solutions are presented. Metrics that are defined and computed over these integrated data and their analysis possibilities are also discussed.

scholarly journals Architecture Enabling Adaptation of Data Integration Processes for a Research Information System

2018 ◽  
Vol 43 (2) ◽  
pp. 129-149
Author(s):  
Darja Solodovnikova ◽  
Laila Niedrite ◽  
Aivars Niedritis
Keyword(s):  
Information System ◽  
Data Integration ◽  
Research Evaluation ◽  
Bibliometric Indicator ◽  
Scientific Activity ◽  
Research Information ◽  
Quality Aspects ◽  
Integration Architecture ◽  
Research Information System ◽  
Data Integration System

Abstract Today, many efforts have been made to implement information systems for supporting research evaluation activities. To produce a good framework for research evaluation, the selection of appropriate measures is important. Quality aspects of the systems’ implementation should also not be overlooked. Incomplete or faulty data should not be used and metric computation formulas should be discussed and valid. Correctly integrated data from different information sources provide a complete picture of the scientific activity of an institution. Knowledge from the data integration field can be adapted in research information management. In this paper, we propose a research information system for bibliometric indicator analysis that is incorporated into the adaptive integration architecture based on ideas from the data warehousing framework for change support. A data model of the integrated dataset is also presented. This paper also provides a change management solution as a part of the data integration framework to keep the data integration process up to date. This framework is applied for the implementation of a publication data integration system for excellence-based research analysis at the University of Latvia.

scholarly journals Optimization of data integration using schema matching of linguistic-based and constraint-based in the university database

2021 ◽  
Vol 11 (3) ◽  
pp. 119-129
Author(s):  
Rifqi Hammad ◽  
◽  
Azriel Christian Nurcahyo ◽  
Ahmad Zuli Amrullah ◽  
Pahrul Irfan ◽  
...  
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Integration ◽  
Data Entry ◽  
Optimization Process ◽  
Schema Matching ◽  
Matching Method ◽  
Integration Problems ◽  
The University

University requires the integration of data from one system with other systems as needed. This is because there are still many processes to input the same data but with different information systems. The application of data integration generally has several obstacles, one of which is due to the diversity of databases used by each information system. Schema matching is one method that can be used to overcome data integration problems caused by database diversity. The schema matching method used in this research is linguistic and constraint. The results of the matching scheme are used as material for optimizing data integration at the database level. The optimization process shows a change in the number of tables and attributes in the database that is a decrease in the number of tables by 13 tables and 492 attributes. The changes were caused by some tables and attributes were omitted and normalized. This research shows that after optimization, data integration becomes better because the data was connected and used by other systems has increased by 46.67% from the previous amount. This causes the same data entry on different systems can be reduced and also data inconsistencies caused by duplication of data on different systems can be minimized.

scholarly journals Optimization of data integration using schema matching of linguistic-based and constraint-based in the university database

2021 ◽  
Vol 11 (3) ◽  
pp. 119-129
Author(s):  
Rifqi Hammad ◽  
◽  
Azriel Christian Nurcahyo ◽  
Ahmad Zuli Amrullah ◽  
Pahrul Irfan ◽  
...  
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Integration ◽  
Data Entry ◽  
Optimization Process ◽  
Schema Matching ◽  
Matching Method ◽  
Integration Problems ◽  
The University

University requires the integration of data from one system with other systems as needed. This is because there are still many processes to input the same data but with different information systems. The application of data integration generally has several obstacles, one of which is due to the diversity of databases used by each information system. Schema matching is one method that can be used to overcome data integration problems caused by database diversity. The schema matching method used in this research is linguistic and constraint. The results of the matching scheme are used as material for optimizing data integration at the database level. The optimization process shows a change in the number of tables and attributes in the database that is a decrease in the number of tables by 13 tables and 492 attributes. The changes were caused by some tables and attributes were omitted and normalized. This research shows that after optimization, data integration becomes better because the data was connected and used by other systems has increased by 46.67% from the previous amount. This causes the same data entry on different systems can be reduced and also data inconsistencies caused by duplication of data on different systems can be minimized.

scholarly journals Graph-based sequence annotation using a data integration approach

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Robert Pesch ◽  
Artem Lysenko ◽  
Matthew Hindle ◽  
Keywan Hassani-Pak ◽  
Ralf Thiele ◽  
...  
Keyword(s):  
Data Integration ◽  
Gene Function ◽  
High Throughput Sequencing ◽  
Prediction Method ◽  
Function Prediction ◽  
Function Annotation ◽  
Automated Annotation ◽  
Data Integration System ◽  
Reference Databases ◽  
Function Assignment

SummaryThe automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara- Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation.The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

scholarly journals DBE2 – Management of experimental data for the VANTED system

2011 ◽  
Vol 8 (2) ◽  
pp. 85-94
Author(s):  
Hendrik Mehlhorn ◽  
Falk Schreiber
Keyword(s):  
Experimental Data ◽  
Information System ◽  
Data Integration ◽  
Data Management ◽  
Data Storage ◽  
Controlled Vocabulary ◽  
Biological Experiment ◽  
Experiment Data ◽  
Measurement Units ◽  
Persistent Data

Summary DBE2 is an information system for the management of biological experiment data from different data domains in a unified and simple way. It provides persistent data storage, worldwide accessibility of the data and the opportunity to load, save, modify, and annotate the data. It is seamlessly integrated in the VANTED system as an add-on, thereby extending the VANTED platform towards data management. DBE2 also utilizes controlled vocabulary from the Ontology Lookup Service to allow the management of terms such as substance names, species names, and measurement units, aiming at an eased data integration.

Sign in / Sign up

Export Citation Format

Share Document