Abstract
We present a novel RDBMS-based framework for interactively querying and exploring large-scale bio-science research data. We focus on the interactive exploration model and its evaluation support using Bloom filter indexing techniques for Boolean containment expressions. In particular, our framework helps explore structured research data augmented with schema-less contextual information. Our experiments show significant improvements over traditional indexing techniques, enabling scientists to move from batch-oriented to interactive exploration of research data.
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Notes
- 1.
omics - an informal reference to a field of study in biology ending in -omics, such as Genomics, Proteomics, Metabolomics etc.
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Doniparthi, G., Mühlhaus, T., Deßloch, S. (2020). A Bloom Filter-Based Framework for Interactive Exploration of Large Scale Research Data. In: Darmont, J., Novikov, B., Wrembel, R. (eds) New Trends in Databases and Information Systems. ADBIS 2020. Communications in Computer and Information Science, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-030-54623-6_15
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DOI: https://doi.org/10.1007/978-3-030-54623-6_15
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