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The Integrated Query System currently in development will access a variety of data types, shown below, that reside in independent systems.
Genomic Data
Will go in the Google genomics cloud
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| Data accepted by the Integrated Query System | Data Source |
|---|---|
| Genomic | Google Genomics Cloud |
| Clinical | Downloaded from TCGA and stored in a customized database at Emory University |
| Preclinical |
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| Customized database at Emory University |
| Radiology Images |
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| (Human and Animal) | TCIA |
| Radiology Image Annotation and Markup | AIM Data Service (AIME) |
| Pathology Images (Human and Animal) | caMicroscope |
| Pathology Image Annotation and Markup | uAIM Data Service (uAIME) |
Given the technical challenges inherent in such a system, technical solutions are animal images are in TCIA.Given the technical challenges inherent in such a system, technical solutions are being developed. This API is being designed to support federation of multiple information repositories using the concept of data mashups. A data mashup in this case is a software interface, much like a dashboard, that allows a person to visualize and analyze data from different sources. The Integrated Query System, with its support for whole slides and data mashups, will act as a foundation for a broader set of novel community research projects.
Annotation and Markup for Radiology Images
Comes out of the AIME Data Service
Pathology Data
Are in caMicroscope
Annotation and Markup for Pathology Images
Currently being developed but will be in the microAIM data service.
Google Genomics
- https://cloud.google.com/genomics/
Radiology Image Annotation and Markup
- AIM Data Service (AIME)
Pathology Image Annotation and Markup
- uAIM Data Service (uAIME)
Preclinical data
- customized database at Emory
Clinical Data
- TCGA
- Customized database at Emory
Radiology Image (human and animal)
- TCIA
Pathology Images (human and animal)
- caMicroscope
DICOM Working Group 30
While the challenges of integrating small animal/co-clinical data with data on humans are steep, given the lack of common data standards, the potential rewards are great. These rewards depend on a common data standard for human and small animal data and support by equipment manufacturers for the standard.
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