The Fred Hutch Ontology Browser is a tool intended to facilitate interoperability between data management tools in use by Fred Hutch investigators. Currently version controlled, curated data dictionaries are managed via GitHub and presented for interactive viewing on the various tabs included on this site. If fields/variables/annotations of interest to you are not included in the relevant data dictionary, proposals for new data elements ideally would be sourced from an established ontology provider as this will be valuable for future interoperability between systems. Our initial suggestions for finding new data elements are to reference the NCI Thesaurus and the overall NCI Common Data Elements Browser.
Caisis is a clinical data management tool into which data from medical records, etc are abstracted or fed from various sources to create another resource for the research community. Abstraction for each disease group follows a data dictionary outlining fields of high interest for that program which have been approved by a multi-disciplinary team of disease experts and researchers. The tables included are lists of the fields currently in use by one or more of the various diseases for which data abstraction has been, or is currently, abstracted. Descriptions of those field definitions are displayed. In the “All” tab any field in use by any disease is included while on each disease tab only those fields in use by that particular disease are displayed.
This tool has a download feature which is best applied to the “All” tab and as fields are selected in the table on the left (or deselected), they will appear (or disappear) in the table on the right. Once all of the currently in use fields of interest are selected, clicking the “Download Ontology” button will download a csv file containing all of the selected fields and their descriptions. This file can then be added to if there are fields that are of interest but not already in the Caisis dictionary and then sent to STTR/HDC to indicate the desired fields for a data abstraction process.
The Translational Genomics Repository data dictionary is oriented toward the particular metadata associated with the generation of large scale molecular data sets from human biospecimens and incorporates information about consent, data privacy, experimental covariates and genomic dataset specific metadata. The annotations listed are a subset of the entire dictionary used to coordinate molecular genomic data work which are those specifically that are shared across all studies, and applied to processed data sets deposited to the TGDCC data commons projects. As desired, study-specific covariates will be shared via this tool. If you are interested in collaborating with the TGDCC, please contact us and let us know (see the Contact Us section below).
STTR is currently performing a review of existing and newly developed biospecimen tracking and metadata collection tools. The current overview of fields and descriptions of fields of interest for a Fred Hutch wide Biospecimen Management tool are displayed in this tab.
If you have any questions or issues regarding this tool, please email: Amy Paguirigan, (
apaguiri at fredhutch.org). This app is supported by the Translational Genomics Repository.