An Extensible Conceptual Model for Tabular Scientific Datasets

摘要

There is a proliferation of datasets generated by various scientists of different scientific disciplines. Therefore, there is a growing need to construct and develop platforms that enable scientists to capture, exchange, process, and interpret data for immediate use, as well as to store and manage data to support future reuse. Modeling and organizing data within such platforms are key challenges. To this end, in this paper, we introduce the dataset model of the BExIS 2 platform and how data can be organized inside the model. In particular, we describe the anatomy of a general purpose tabular dataset, which consists of data tuples to represent the table rows and data cells that are compound objects holding the obtained values and their auxiliary information. The structure of datasets is defined and applied separately in order to factor out shared concepts such as unit of measurement, methodology, data type, valid and missing values, processing functions and so on. The datasets are extensible in multiple ways and can be annotated on various levels utilizing taxonomies, ontologies, and custom metadata structures.