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The problem is that repositories are often not flexible enough to store data that do not conform to known standards. Genomics, for example, benefits from community genomics standards groups that develop standard programmatic interfaces for managing, describing, and annotating genomic data (attribution: https://gdc.cancer.gov/about-data/data-standards)and open industry standards. Many other fields of study are without such standards, yet generate significant amounts of data.
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The DCC's goal is to use the CSSI DCC Portal to store emerging data types in addition to those that comply with ISA-TAB. Facilitating this is the DCC's design approach, which followed the principles of FAIR: FAIR principles--Findable, Accessible, Interoperable, and Reusable, --and applied both metadata standards such as ISA-TAB and the best practices of the cancer research community.
The CSSI DCC Portal has is powerful and serves the following purposes:
- Provides a common location and web access to data from disparate data types including gene expression results from Next Generation Sequencing, microarray experiments, histopathological images, metabolomics data and proteomics data, allowing for easy access by multiple collaborators and researchers located at different geographic locations. Is flexible enough to handle new and unspecified data types.
- Stores the data in one common location so that you can make biological insights that would otherwise be missed by having data in multiple locations.
- Applies the information gained from one study to multiple studies and projects.
- Allows you to search the metadata from each study to identify datasets of interest.
- Develops data storage and data mining modules that can be applied across studies, avoiding duplication of effort and saving costs.
- Develops and/or adopts common vocabularies, data standards, and ontologies for data representation, storage, and comparison.
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See Neo4j - Rapidly Prototyping a Semantic Graph for more information about technologies used in CSSI DCC.
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