[
https://issues.apache.org/jira/browse/AIRAVATA-3593?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17526949#comment-17526949
]
Suresh Marru commented on AIRAVATA-3593:
----------------------------------------
Suggested tasks to demonstrate required skills:
* Deploy a local MongoDB
* Store JSON-LD examples from [https://github.com/MolSSI/QCSchema] and
[https://github.com/stuchalk/scidata] into the database
* Do not directly expose the database to the UI but create an API to query
data. For reference, you can look into [https://github.com/SciGaP/seagrid-data]
* Develop a Django App with VueJS front end to query the data and display the
data and deploy it to a stand-alone instance of Airavata Django Portal
* Refer to Airavata Data Lake and EmCenter UI for reference -
[https://github.com/SciGaP/emcenter-gateway]
* Integrate with Custos Security [https://airavata.apache.org/custos/]
> SMILES data Models
> ------------------
>
> Key: AIRAVATA-3593
> URL: https://issues.apache.org/jira/browse/AIRAVATA-3593
> Project: Airavata
> Issue Type: Epic
> Reporter: Suresh Marru
> Priority: Major
> Labels: gsoc2022, mentor
> Attachments: Proposal Draft-1.pdf, Proposal architecture draft-1.png
>
>
> Extend Airavata Data Catalog to record metadata extracted from experimental
> and computational data in support of the small-molecule ionic isolation
> lattices SMILES data.
> Suggested flow:
> VueJS user interfaces -> Django App -> API Server -> Data Orchestrator ->
> Data Lake
> Refer to [https://github.com/apache/airavata-data-lake]
> The data models should be developed in JSON-LD [https://json-ld.org/]
--
This message was sent by Atlassian Jira
(v8.20.7#820007)
