scholarly journals Improving User Interaction on Ontology-based Peer Data Management Systems

2014 ◽  
Vol 7 (2) ◽  
pp. 67-85
Author(s):  
Andreza Leite de Alencar ◽  
Ana Carolina Salgado
Keyword(s):  
Data Management ◽  
User Interaction ◽  
Data Management System ◽  
Management Systems ◽  
Query Interface ◽  
Query Formulation ◽  
User Query ◽  
Visual Query ◽  
Query Generation ◽  
Peer Data Management

The issue of user interaction for query formulation and execution has been investigated for distributed and dynamic environments, such as Peer Data Management System (PDMS). Many of these PDMS are semantic based and composed by data peers which export schemas that are represented by ontologies. In the literature we can find some proposed PDMS interfaces, but none of them addresses, in a general way, the needs of a PDMS for user interaction. In this work we propose a visual user query interface for ontology-based PDMS. It provides a simple and straightforward interaction with this type of system. It aims not only providing a natural visual query interface but also supporting a precise and direct manipulation of the data schemas for query generation.

scholarly journals Ontology-Based Clustering in a Peer Data Management System

2012 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Carlos Eduardo Santos Pires ◽  
Rocir Marcos Leite Santiago ◽  
Ana Carolina Salgado ◽  
Zoubida Kedad ◽  
Mokrane Bouzeghoub
Keyword(s):  
Data Management ◽  
Data Management System ◽  
Management Systems ◽  
Challenging Problem ◽  
Data Management Systems ◽  
Stage Of Development ◽  
Data Source ◽  
Peer Data Management ◽  
P2p Applications ◽  
Current Stage

Peer Data Management Systems (PDMSs) are advanced P2P applications in which each peer represents an autonomous data source making available an exported schema to be shared with other peers. Query answering in PDMSs can be improved if peers are efficiently disposed in the overlay network according to the similarity of their content. The set of peers can be partitioned into clusters, so as the semantic similarity among the peers participating into the same cluster is maximal. The creation and maintenance of clusters is a challenging problem in the current stage of development of PDMSs. This work proposes an incremental peer clustering process. The authors present a PDMS architecture designed to facilitate the connection of new peers according to their exported schema described by an ontology. The authors propose a clustering process and the underlying algorithm. The authors present and discuss some experimental results on peer clustering using the approach.

Clinical Trial Data Management Software: A Review of the Technical Features

2019 ◽  
Vol 14 (3) ◽  
pp. 160-172 ◽  
Author(s):  
Aynaz Nourani ◽  
Haleh Ayatollahi ◽  
Masoud Solaymani Dodaran
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Data Management ◽  
Clinical Data ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Data Management System ◽  
Management Systems ◽  
Data Management Systems ◽  
Technical Features

Background:Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems.Methods:Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study.Results:Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development.Conclusion:It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.

A Review of Clinical Data Management Systems Used in Clinical Trials

2019 ◽  
Vol 14 (1) ◽  
pp. 10-23 ◽  
Author(s):  
Aynaz Nourani ◽  
Haleh Ayatollahi ◽  
Masoud Solaymani Dodaran
Keyword(s):  
Clinical Trials ◽  
Data Management ◽  
Clinical Data ◽  
Data Management System ◽  
Management Systems ◽  
Management Process ◽  
Data Management Systems ◽  
Ovid Medline ◽  
Research Findings ◽  
Accuracy Of Results

Background:A clinical data management system is a software supporting the data management process in clinical trials. In this system, the effective support of clinical data management dimensions leads to the increased accuracy of results and prevention of diversion in clinical trials. The aim of this review article was to investigate the dimensions of data management in clinical data management systems.Methods:This study was conducted in 2017. The used databases included Web of Science, Scopus, Science Direct, ProQuest, Ovid Medline and PubMed. The search was conducted over a period of 10 years from 2007 to 2017. The initial number of studies was 101 reaching 19 in the final stage. The final studies were described and compared in terms of the year, country and dimensions of the clinical data management process in clinical trials.Results:The research findings indicated that none of the systems completely supported the data management dimensions in clinical trials. Although these systems were developed for supporting the clinical data management process, they were similar to electronic data capture systems in many cases. The most significant dimensions of data management in such systems were data collection or entry, report, validation, and security maintenance.Conclusion:Seemingly, not sufficient attention has been paid to automate all dimensions of the clinical data management process in clinical trials. However, these systems could take positive steps towards changing the manual processes of clinical data management to electronic processes.

SCHEMA MEDIATION IN PEER DATA MANAGEMENT SYSTEMS

2011 ◽  
Vol 20 (03) ◽  
pp. 261-305
Author(s):  
JIE ZHAO ◽  
RACHEL POTTINGER ◽  
CODY BROWN ◽  
SHRIRAM RAJAGOPALAN
Keyword(s):  
Data Management ◽  
Stable State ◽  
Management Systems ◽  
Light Weight ◽  
Access To Information ◽  
Sources Of Information ◽  
Data Management Systems ◽  
Share Data ◽  
Peer Data Management ◽  
Current Systems

Peer Data Management Systems (PDMSs) allow the efficient sharing of data between peers with overlapping sources of information. These sources share data through mappings between peers. In current systems, queries are asked over each peer's local schema and then translated using the mappings between peers. While this allows the data to be accessed uniformly, users lack access to information that is not in their own schemas. In this paper, we propose a light-weight, automatic method to create a mediated schema in a PDMS. Our work benefits PDMSs by allowing access to more data and without unduly stressing the peer's resources or requiring additional resources such as ontologies. We present our system — MePSys, which creates a mediated schema in PDMSs automatically using the existing mappings provided to translate queries. We further discuss how to update the mediated schema in a stable state, i.e. after the system setup period.

A research agenda for query processing in large-scale peer data management systems

2008 ◽  
Vol 33 (7-8) ◽  
pp. 597-610 ◽  
Author(s):  
Katja Hose ◽  
Armin Roth ◽  
André Zeitz ◽  
Kai-Uwe Sattler ◽  
Felix Naumann
Keyword(s):  
Data Management ◽  
Query Processing ◽  
Research Agenda ◽  
Large Scale ◽  
Management Systems ◽  
Data Management Systems ◽  
Peer Data Management

scholarly journals The Piazza Peer Data Management System

2004 ◽  
Vol 16 (07) ◽  
pp. 787-798 ◽  
Author(s):  
A.Y. Halevy ◽  
Z.G. Ives ◽  
J. Madhavan ◽  
P. Mork ◽  
D. Suciu ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
Data Management System ◽  
Peer Data Management
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