Paper Info
Title
An Architecture Supporting the Collection and Monitoring of Data Openly Contributed over the World Wide Web
Abstract
Open data collection over the World Wide Web-in which any web user can contribute to large databases of "informal" data -presents several challenges that require novel approaches in human interface design, algorithmic machine learning and collaborative infrastructure. Foremost among these challenges is the need to ensure data integrity and quality, by automatically or semi-automatically identifying unreliable or hostile contributors and rejecting their contributed data. Other, traditional requirements include security, scalability, and the need to support collaboration between separate but related data collection projects. Further, for the open software/data model, the system must permit users to freely browse, navigate and download the contributed data. This paper presents a collaborative architecture for a set of such data collection projects that addresses these challenges and requirements. Key components of this architecture have been implemented and tested as part of the Open Mind Initiative.
Year
DOI
Venue
2001
10.1109/ENABL.2001.953448
WETICE
Keywords
Field
DocType
anoma- lous data detection,web infrastructure,learning with queries,data openly,open mind initiative,data model,data quality monitoring,world wide web-in,open software development,data integrity,collaborative architecture,open software,data collection project,open data collection,related data collection project,collaborative infrastructure,user interface design,internet,groupware,data security,relational data,collaboration,machine learning,data collection,human interface,algorithm design and analysis,data quality,world wide web,user interfaces,computer architecture,databases,scalability,software development,learning artificial intelligence
Data architecture,Data collection,Open data,World Wide Web,Collaborative software,Computer science,Data integrity,User interface,Data model,The Internet,Distributed computing
Conference
ISBN
Citations 
PageRank 
0-7695-1269-0
1
0.44
References 
Authors
4
1
Name
Order
Citations
PageRank
David G. Stork1627106.17