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Download the SWIFT toolkit distribution {{eagle-i-datatools-etl-distswift-\[version\].zip}}, unzip it into a dedicated directory, and navigate to it. For example

mkdir ~/eagle-i
unzip -d ~/eagle-i eagle-i-etldatatools-distswift-12.7MS20MS3.01.zip
cd eagle-i/eagle-i-etl-dist-1.7M2swift-2.0MS3.01

Input generation instructions

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1. Place your input files (i.e. the completed templates) in a directory of your choice, e.g. dataDirectory. All files contained in this directory will be processed by the ETLer.
2. To run an ETL, execute the following command (note that all records will be uploaded in the requested workflow state):

   No Format
   ./ETLer.sh -d dataDirectory [-p DRAFT|CURATION|PUBLISH] -c username:password -r repositoryURL

   Info

   If you are practicing the ETL process, you may wish to upload your data to the common eagle-i training node. In this case, if your directory is named dataDirectory, the script would be executed as follows (default workflow state is DRAFT): No Format ./ETLer.sh -d dataDirectory -c L4:Level4 -r https://training.eagle-i.net Note that the data that is uploaded to the training node CAN be viewed and modified by others even in a draft state (even if you subsequently lock the records). Note also that the information in the training node is not persistent as the node is refreshed periodically.

3. To verify the data upload, log on to the SWEET application and select the lab to which the ETLd resources belong.

De-ETL instructions

Resources that are uploaded to an eagle-i repository via ETL are tagged with the name of the file from which they were extracted. It is therefore relatively simple to de-ETL an entire file. To do so, execute the following command:

 ./deETLer -f filename -c username:password -r repositoryURL

Appendix A. Input file odds and ends

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