Stuff I've seen: a system for personal information retrieval and re-use
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The user-subjective approach to personal information management systems
Journal of the American Society for Information Science and Technology
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Personal information management with SEMEX
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
IEEE Intelligent Systems
Data integration: the teenage years
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Making mashups with marmite: towards end-user programming for the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Relations, cards, and search templates: user-guided web data integration and layout
Proceedings of the 20th annual ACM symposium on User interface software and technology
Intel Mash Maker: join the web
ACM SIGMOD Record
Information scraps: How and why information eludes our personal information management tools
ACM Transactions on Information Systems (TOIS)
Potluck: Data mash-up tool for casual users
Web Semantics: Science, Services and Agents on the World Wide Web
End-user programming of mashups with vegemite
Proceedings of the 14th international conference on Intelligent user interfaces
PARIS: probabilistic alignment of relations, instances, and schema
Proceedings of the VLDB Endowment
Matching ontologies in open networked systems: techniques and applications
Journal on Data Semantics V
| Hi-index | 0.01 |
The information processing capabilities of humans enable them to opportunistically draw and integrate knowledge from nearly any information source. However, the integration of digital, structured data from diverse sources remains difficult, due to problems of heterogeneity that arise when data modelled separately are brought together. In this paper, we present an investigation of the feasibility of extending Personal Information Management (PIM) tools to support lightweight, user-driven mixing of previously un-integrated data, with the objective of allowing users to take advantage of the emerging ecosystems of structured data currently becoming available. In this study, we conducted an exploratory, sequential, mixed-method investigation, starting with two pre-studies of the data integration needs and challenges, respectively, of Web-based data sources. Observations from these pre-studies led to DataPalette, an interface that introduced simple co-reference and group multi-path-selection mechanisms for working with terminologically and structurally heterogeneous data. Our lab study showed that participants readily understood the new interaction mechanisms which were introduced. Participants made more carefully justified decisions, even while weighing a greater number of factors, moreover expending less effort, during subjective-choice tasks when using DataPalette, than with a control set-up.