Acuity Transform_Overview

ACUITY-transform (or SDTM tool) is an application that converts raw source .csv or .sas7bdat files to .csv files that can be imported to the ACUITY system with AdminUI application.

Details and Prerequisites

1. ACUITY-transform is a command line tool and does not have any graphic UI.
2. ACUITY-transform uses MongoDB as an intermediate data storage, so a running MongoDB instance is required to use it
3. To use ACUITY-transform you need its built .jar file and a configuration file (application-<your-profile-name>.yml, e. g. appliction-myprofile.yml) that you'll configure as you need (or you may just create a new one accordingly with the instruction below)
4. ACUITY-transform is a Java application, so you'll need an installed Java and configured JAVA_HOME environment variable
5. To convert data files with ACUITY-transform, you need to know the study name (e.g. STUDY001) and version name (e.g. SDTM_1_1_STUDY001) for which you need to perform the conversion. If you don't know them, you may find them in the name of files directory/archive (but it's just a hint, not a stable rule!)
6. To work with files stored in Microsoft Azure file storage you'll need storage account data (but you may also just work with local files in your file system)

How to use it

1. If you don't have running instance of MongoDB, run it:

• Download MongoDB distributive from the official site and unpack it in some directory on your machine (tested with MongoDB 4.2.6 Community version)
• In the unpacked directory subdir bin, run mongod executable file in a command line tool (dbpath may be any available directory you prefer to place temporary database directory into; port may be any available port, or you may just omit this parameter - then default 27017 port will be used):

mongod --dbpath=\path\to\db\files --port=51327

2. Place ACUITY-transform .jar file and configuration file in the same directory
3. Edit the configuration file (or create a new one) as described below:

mongo:
  host: localhost  # address of your MongoDB instance; for locally running one, it's localhost
  port: 27017      # MongoDB port you'll specified in p. 1; by default, it's 27017 
  db: test         # database name; choose any non-existing one

# file locations; they may be either local file system directories or Azure storage directories
# (in the second case they should look like `azure-file://some/path`)
SRC_BASE: \path\to\source\files     # directory where your data files are placed
OUT_BASE: \path\to\resulting\files  # directory where you want to have conversion result

studies:
  list:                             # below just one dataset metadata is added, but more can be if you need it
    - study: STUDY001                 # study for which you want to perform the conversion
      version: SDTM_1_1_STUDY001      # study version
      source: ${SRC_BASE}
      destination: ${OUT_BASE}
      domain: dm                    # for now, it changes nothing, so just don't touch it

# the following section is needed only if you plan to work with files in Azure storage; otherwise just omit it
azure:
  storage:
    protocol: https
    account: storage-account        # place your Azure storage account here
    key: storage-key                # place your Azure storage key here

4. Place your raw files in the directory you configured as SRC_BASE in p. 3
5. Finally, run the conversion process; let's name your profile myprofile, then configuration file should be named application-myprofile.yml. If you are going to run local files conversion, run the following command:

java -Dspring.profiles.active=myprofile -jar acuity-transform.jar

And if it's about files in Azure storage, run this:

java -Dspring.profiles.active=azure-storage,myprofile -jar acuity-transform.jar