The Journal of Machine Learning Research
Active Management of Scientific Data
IEEE Internet Computing
iMecho: an associative memory based desktop search system
Proceedings of the 18th ACM conference on Information and knowledge management
Software traceability with topic modeling
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Predicate-based indexing for desktop search
The VLDB Journal — The International Journal on Very Large Data Bases
Bridging workflow and data provenance using strong links
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
PODD - Towards an Extensible, Domain-Agnostic Scientific Data Management System
ESCIENCE '10 Proceedings of the 2010 IEEE Sixth International Conference on e-Science
Scalable and Distributed Processing of Scientific XML Data
GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
TopicNets: Visual Analysis of Large Text Corpora with Topic Modeling
ACM Transactions on Intelligent Systems and Technology (TIST)
A Provenance Approach to Trace Scientific Experiments on a Grid Infrastructure
ESCIENCE '11 Proceedings of the 2011 IEEE Seventh International Conference on eScience
Provenance collection support in the kepler scientific workflow system
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
GLASS: Genomic Literature Area Sequence Search
BIBMW '11 Proceedings of the 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops
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Scientific experiments typically produce a plethora of files in the form of intermediate data or experimental results. As the project grows in scale, there is an increased need for tools and techniques that link together relevant experimental artifacts, especially if the files are heterogeneous and distributed across multiple locations. Current provenance and search techniques, however, fall short in efficiently retrieving experiment-related files, presumably because they are not tailored towards the common use cases of researchers. In this position paper, we propose Experiment Explorer, a lightweight and efficient approach that takes advantage of metadata to retrieve and visualize relevant experiment-related files.