What is FASTREAD_ECL?

FASTREAD_ECL is a tool to support primary study selection in systematic literature review implemented on HPCC for massive scale-up.

Latest Versions:

• On Github repo: https://github.com/ai-se/FASTREAD_ECL.

Setting up FASTREAD

1. Setting up HPCC:

   • Install HPCC virtual machine
   • Install HPCC Client Tools    - add C:\Program Files (x86)\HPCCSystems\xx.xx\clienttools\bin (the installation path to ecl.exe) to your environment path.

2. Setting up Python:

   • We use anaconda by continuum.io (see Why?)
   • We won't need the entire distribution. Download a Python 2.7 version & install a minimal version of anaconda.
   • Make sure you select add to PATH during install.

3. Getting dependencies:

   • get flask package from anaconda: run conda install flask in your terminal/shell.
   • get ecl-ml from github
   • install libsvm development package on your HPCC nodes: ECLAGENT, THOR, THORMASTER, ECLCCSERVER.
   • for the virtual box case, just run sudo apt-get install libsvm-dev on your vitual machine
   • for the case of multiple nodes, every node should be installed with libsvm development package
   • put ecl-ml in the same directory alongside FASTREAD_ECL:

Use FASTREAD_ECL

1. Running HPCC in virtual box:

   • follow the instruction here

2. Get data ready:

   • Prepare a csv file like this:
   • the 'label' column stores the TRUE label of each entry, if not applicable, leave it as blank or 'unknown'.
   • Remove the header (first row) of your data file.
   • There are some example data files in FASTREAD_ECL > UI > workspace > data
   • Open ECL_Watch: http://ecl_watch_ip::8010  + Upload your data file onto HPCC landing zone (files > Landing Zones > Upload):
   • Spray it:
   • Select uploaded file
   • Click Spray: Delimited
   • Change the Target Scope to fastread::
   • Hit Spray at bottom right

3. Running script:

   • Navigate to FASTREAD_ECL > UI > src and run index.py.
   • If all is well, you'll be greeted by this:

4. The Interface:

   • Fire up your browser and go to http://localhost:5000/hello/. You'll see a page like below:

5. Load the data:

   • Click Scan button to see what data files are on your HPCC system. Then select the data to work on from the selection tab.
   • Wait up to minutes for the first time. Once the data is successfully loaded, you will see the following:

6. Begin reviewing studies:

   • choose from Relevant, Irrelevant, or Undetermined for each study and hit Submit.
   • hit Next when you want a to review more.
   • statistics are displayed as Documents Coded: x/y (z), where x is the number of relevant studies retrieved, y is the number of studies reviewed, and z is the total number of candidate studies.
   • when x is greater than or equal to 1, an SVM model will be trained after hitting Next.
   • keep reviewing studies until you think most relevant ones have been retrieved.

7. Export csv:

   • Click Export button will generate a csv file with your coding in FASTREAD_ECL > UI > workspace > coded.

8. Restart:

   • Click Restart button will give you a fresh start and loose all your previous effort on the current data.

Version Logs

May 23, 2017. v1.0.0 The very first, basic version is released.