1. Presentation on SubmissionTrackingTool: by Anjan Sharma

2. What is Submission Tracking ?

3. Curation Process ? Curation Database Ftp Repository MAGE-ML MAGE-ML Repository MAGE Validator/Loader Submission Message back to Submitter. ValidationLog Otherlog

4. 1. Submitter submits some files: File1.xm File2.xml File3.xml 2. Validator validates and error found. Inform the submitter about the fault. 4. Same set of files arrives from the same submitter with modifications 5. After spending few more hours curator found that there is a problem in the file3.xml and he cannot curate farther unless the curator gets the correct version of file3.xml. 6. Curation of that set of file will stop till the new file arrives. 7. Curator is busy with other files. 8. File3.xml arrives. ----- What to do now? What was the status of this submission? ---- 3. Curation is going on (Spent few hours) Here there is a more practical scenario.

5. Solution of the problem - Version Control System. - A system that can keep the status submission. - A system that can notify the submitter and curator with what is going on during the curation process. - A system that can take care of the storage space issue as the MAGE-ML files are big in size. - A system which enables query the MAGE-ML file during the during preload.

6. Some of the preload checks What are the packages present in the Submission? Does it contain all MIAME required fields? -Surface type -Reporters with associated bio-sequence -Check for presence of Reporter Groups in the Array -Check for Feature, Reporter or Composite Sequence for the Design Element. -Check for Bio-sequences that describes the Reporter -Check for Experiment factors variable and associated bioassays. -Check for data file for each hybridisation Provide report on these.

7. - Report on Ontology and its context. - Check for Ontology. W here and how ?

8. Management of the MAGE-ML files that comes to us through the MAGE-ML pipeline that needs Manual Curation. It is needed for pre-load check and integrity of the MAGE-ML. What is Submission Tracking?

9. Ftp Repository Ready to Load MAGE_ML BACK UP Ftp Backup Curation DB XML Editor Submission Submission Tracker CVS Repository In Out How does it work?

10. Invoked the application: - Who is invoking the tracker and for what purpose he is invoking? - Which is the submission that he is going to work. - Fresh submission or re-submission ? - Who is the submitter and when it was submitted? -Validate and Check the MAGE-ML and generate different log files. -Generate Check report and Ontology report. -What are the modifications made before last check-in of the submission? Store them. - Cleans up the curation repository and perform space management. - Notify the curator and the submitter about curation.

11. Bit of Technical stuff: -Build on the Object Model. -Build on façade Design Pattern with the help of some additional packages. Use Case:

12. - It is a command line java application. - Class can be used to provide a web interface. Tool is now present at: /net/nfs6/vol4/ma-db/AE-CUR/Curation_Cvs /

13. Option Description -fetch : Fetch the ftp submission in to the CVS. Moves the submission to the ftp backup location. “Given name” is the name given to the enclosed directory of the MAGE-ML files. Can be used to fetch multiple uncompress submissions. Option “–fetch -temp ” can be used to fetch from other location rather than the ftp submission location. -status: Displays curator’s status whose name is supplied as an argument. Status information includes the name of submission the curator is currently working and the modification made with respect to the previous Check- in/Original submission. -check Looks for new Ontology in the Submission and generate a report. [ Partially implemented ! ]

14. Limitation: 1.Platform specific script to use only on Unix. 2. No revert functionality it the current version. 3. No graphical user interface Things to be done: 1. Add revert functionality. 2. Good graphical user interface 3. Add more preload checks 4. Add Ontology manager. 5. Add more functionality as we come to know about them.

15. Create a database of Ontology. (Practically a Table in the existing database) - Periodic update. (With the help of Ontology developer tool) - Synchronized with external Ontology database. - During MAGE-ML check/validation it will create Ontology report validating against the Ontology database, which are non-duplicate and context base. - Send this report to another application like oilEd where you can edit them. Update the Ontology database when ready.

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