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  • Part 1: Teach to write an extractor (35 mins)
    • Start with the bd-template extractor, which is the word count extractor.
    • Ask participant to modify the extractor, which would use 'grep' to find a specific pattern within the file.
    • Ask to change the name of the extractor from ncsa.wordcount to ncsa.grep.
    • Include yes/no in the metadata if the pattern is found or not found.
    • Briefly describe Json-ld support. Provide intuition behind the idea json-ld with a simple example. No need to go into details of RDF. 
    • TODO
      •  Smruti PadhyMarcus SlavenasJong Lee  Provide Step-by-step instructions/screenshots of updating the extractor and the output as seen at the Clowder GUI.  Also provide link to json-ld for further readings. Provide minimum software requirements for the development such as Clowder, Rabbimq, MongoDB, pyclowder, python libraries, etc.
      •  Inna Zharnitsky Write an extractor that does grep along with the wordcount for demonstration purpose and include json-ld 
      •  Sandeep Puthanveetil Satheesan Write an extractor that accepts csv file with say 3 columns (probably with values from weather or bacterial growth model (see Problem 2.2 below)) , calculate the average of a specific column
        •  Provide step-by-step screenshots for writing such an extractor.

  • Part 2: Teach to write a converter (35 mins)
    • Start with the bd-template for converter- imagemagick
    • Ask the participant to modify the converter input/output formats in the comment section. And see the result using the polyglot web UI for post and get
    • Another example - FFmpeg converter for audio and video
    • TODO

  • Part 3: Teach to upload a converter or an extractor to the locally installed Tools Catalog. (20mins)
    •  Inna Zharnitsky Step-by-step procedure to upload an extractor or a converter, an input file and an output file without a docker file.

  • Part 4 (Optional - For advanced user): Dockerize the tool

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