Describe Cassandra data model with examples and simplicity. This tutorial includes column, super column, column family, super column family, keyspace, validator & comparator.
At the core of the platform lies a common data model to enable interoperability between the different components. In order to interact with the platform, a component should know how to interact with at least a subset of the CDM. The model describes all the commonly used data that is dealt with in the platform, and therefore covers at least taxonomic names and concepts; literature references; authors; (type) specimen; structured descriptive data; and species related content of any kind like economic use or conservation status. Nearly all this data has already been described by existing or upcoming TDWG standards. Unfortunately, there are still major gaps in compatibility, so a new integrated data model has to be developed in order to quickly yield results.
A pre-relational databases datamodel. "Preceeded" by the relational model since the flexibility of this makes it hard to work with. Now re-invented in RDF :)
{. Schouten, {. Bueno, W. Duivesteijn, and M. Pechenizkiy. Data Mining and Knowledge Discovery, 36 (1):
379--413(January 2022)Funding Information: This research is supported by EDIC project funded by NWO. We thank the EDIC consortium and the ZGT hospital for allowing us to analyse the data from the DIALECT-2 study. We especially thank Niala Den Braber (PhD candidate at Universiteit Twente and researcher internal medicine at ZGT hospital) and prof. dr. Goos Laverman (internist-nephrologist at ZGT hospital) for giving us clinical valuation of our findings. In addition, we thank our colleagues dr. Robert Peharz for giving us useful insights on Markov chains and DBNs and dr. Maryam Tavakol for guiding us towards the MovieLens dataset..
R. Tennakoon, A. Bab-Hadiashar, D. Suter, and Z. Cao. 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA), page 1-8. (November 2013)
F. Lemmerich, M. Becker, P. Singer, D. Helic, A. Hotho, and M. Strohmaier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 965–974. New York, NY, USA, Association for Computing Machinery, (2016)