CRI: Collaborative Research: Improving Experimental Computer Science with a Searchable Web Portal for Data Sets

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

This collaborative project, developing and populating a Web-based Dataset Portal, provides a powerful front-end for online searching, querying, and browsing research datasets coupled to an intelligent back-end system that dynamically provides cross-references among datasets, research papers, techniques, authors, grants, and journals/conferences. The datasets are linked to Rexa, a research paper digital library at U Mass. The work redesigns the UCI dataset archive with structured meta information that allow queries on the web creating a formalized repository of research datasets with uniform queryable metadata. The system is built on the UCI Machine Learning and KDD Data Repositories. In research areas such as machine learning, data mining, applied statistics, language modeling, information retrieval, computer vision, and speech recognition, methodologies are often evaluated on publicly available datasets. Although these Datasets often serve as a common touchstone for communication, identifying and locating specific data spread haphazardly across various Web sites presents some difficulty. This work creates a community resource to address this problem. Broader Impact: The project directly impacts empirical research, teaching, and most collaborative research activities. Browsing data that suggest new models and applications should inspire researchers and students. Real world data sets not only broaden research but are also bound to encourage teachers to incorporate these in the curriculum. Sharing data should bring about more collaboration from multiple areas.