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Last updated on 2023-09-15

This page is intended to describe describes the workflow required to build, edit, and update the data model for MODEL-AD.

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Data Modeling at Sage requires using two in-house tools: Schematic and the Data Curator App (DCA). SCHEMATIC is an acronym for Schema Engine for Manifest Ingress and Curation. The Python based tool is a schema-based, metadata ingress ecosystem, intended to streamline of biomedical dataset annotation, metadata validation and submission to a data repository for various data contributors.

Documentation

Guide: How to use Schematic for Data Model Development/wiki/spaces/SCHEM/pages/2967568387

Code in Github

https://github.com/Sage-Bionetworks/schematic

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https://sagebionetworks.jira.com/wiki/spaces/SCHEM/pages/2473623559/The+Data+Model+Schema#A.-Schema-properties-and-relationships

Create Data Model

https://sagebionetworks.jira.com/wiki/spaces/SCHEM/pages/2967568387/Guide+How+to+use+Schematic+for+Data+Model+Development#Create-a-Data-Model

The data model is defined in a table, then stored (i.e. serialized) in a JSON-LD schema which specifies attributes as suggested by Schema.org.

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Convert Data Model from CSV to JSON-LD

https://sagebionetworks.jira.com/wiki/spaces/SCHEM/pages/2967568387/Guide+How+to+use+Schematic+for+Data+Model+Development#Convert-Data-Model

schematic schema convert model.csv

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• https://cambridgesemantics.com/blog/semantic-university/learn-rdf/rdf-nuts-bolts-2/

• https://json-ld.org/

• https://medium.com/wallscope/understanding-linked-data-formats-rdf-xml-vs-turtle-vs-n-triples-eb931dbe9827

Guide to Developing Data Models in JSON-LD

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https://sagebionetworks.jira.com/wiki/spaces/SCHEM/pages/2458648589/Setting+up+a+DCC+Asset+Store#How-do-I-Structure-My-DCC-Synapse-Project-to-Work-with-the-Data-Curator-App%3F

ADTR Projects

Projects

Folder Structure

https://dca-docs.scrollhelp.site/DCA/Working-version/Project-Agnostic/organize-your-data-upload#OrganizeyourDataUpload-FlattenedDataLayoutExample

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├── biospecimen_experiment_1
    ├── manifest1.csv
├── biospecimen_experiment_2
    ├── manifestA.csv
├── single_cell_RNAseq_batch_1
    ├── manifestX.csv
    ├── fileA.txt
    ├── fileB.txt
    ├── fileC.txt
    └── fileD.txt
└── single_cell_RNAseq_batch_2
    ├── manifestY.csv
    └── file1.txt

Study Content

/wiki/spaces/AKP/pages/1057882353

• Study Description in wiki

• Methods description in each data folder

/wiki/spaces/EPD1/pages/2900819969

AMP-AD

• Second Test
  AD Portal DCA Test Project

• Fileview AD Portal DCA Test Project - Table

• https://github.com/adknowledgeportal/test-data-model

https://github.com/adknowledgeportal/test-data-model/blob/main/model-ad/model-ad.data.model.jsonld

https://github.com/adknowledgeportal/data-models/blob/main/README.md#editing-data-models

AD data model → modular

repo:

branch: test-split-csvs

folders:

modules/

..biosopecimen/

..mouse/

Term = Attribute in the data model where Parent = DataProperty

test-split0csvs branch

MODEL-AD

ELITE

• ELITE Portal - backend

Annotate study folder with contentType = 'dataset'

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