We have developed the R package for Harmony and open sourced it. To get started, you need R installed on your system.
Click here to try an example in Google Colab.
Here’s a Jupyter Notebook with an example using Harmony in R
We are currently submitting the R library to CRAN.
In the meantime, you can install the development version of harmonydata from GitHub (documentation in the README file):
You also need devtools
which will already be there if you are using R Studio. If not, you can install devtools
with the following command in the R console:
install.packages("devtools") # If you don't have devtools installed already.
Next, to install Harmony, run:
library(devtools)
devtools::install_github("harmonydata/harmony_r")
Let’s import Harmony and harmonise an instrument.
If you want to read in a raw (unstructured) PDF or Excel file, you can do this via a POST request to the REST API. This will convert the file into an Instrument object in JSON.It returns the instrument as a list.
library(harmonydata)
instrument = load_instruments_from_file(path = "examples/GAD-7.pdf")
names(instrument[[1]])
#> [1] "file_id" "instrument_id" "instrument_name" "file_name"
#> [5] "file_type" "file_section" "study" "sweep"
#> [9] "metadata" "language" "questions"
You can also input a url containing the questionnaire.
instrument_2 = load_instruments_from_file("https://medfam.umontreal.ca/wp-content/uploads/sites/16/GAD-7-fran%C3%A7ais.pdf")
names(instrument_2[[1]])
#> [1] "file_id" "instrument_id" "instrument_name" "file_name"
#> [5] "file_type" "file_section" "study" "sweep"
#> [9] "metadata" "language" "questions"
You can get a list containing the results of the match.Here we can see a list of similarity score for each question comapred to all the other questions in th other questionaire.
instruments = append(instrument, instrument_2)
match = match_instruments(instruments)
names(match)
#> [1] "questions" "matches" "query_similarity"
Help us design the next phase of Harmony and win up to £300 in vouchers! Search and Results UX/UI Challenge Harmony is a platform for researchers to help them discover and compare complex meta-data across different academic studies. The project is a collaboration between University College London (UCL), The University of Ulster, and Fast Data Science and has been funded by the Economic and Social Research Council (ESRC) and by Wellcome as part of the Wellcome Data Prize in Mental Health.
It’s all over! The Matching Challenge is now officially closed. Thank you to everyone who took part. The wait is over! We have now closed the Matching Challenge which was hosted on DOXA AI. Over the course of the competition we saw a total of 26 participants with 14 finalists making it onto the scoreboard. The final days were tense with many participants improving on their scores, submitting different methods and swapping places at the top of the scoreboard.