LifeWatch user-analysis

A KGAP implementation for the LifeWatch user analysis.

Steps to start up this K-GAP project

1. retrieve the source code from github

2. to build the services simply run

.$ cp dotenv-example .env             # make sure you have an .env file
.$ cd docker && docker-compose build  # use docker to build the services 

3. to start up the services simply run

.$ cd docker && docker compose up     # use docker to run the services 

4. open the jupyter notebook

• http://localhost:8889/

• .$ xdg-open $(docker/jupyter_url.sh)  # this gets the url for the service and opens a browser to it

5. open the graphdb browser ui

• http://localhost:7201/

• .$ xdg-open http://localhost:7200     # opens the web ui in a browser

Updates

With each yearly update of the lwua, following folders need to be updated:

• ./data/_LWUA_DataSystems_RawInput/
  This folder contains the raw input files.
  Please follow spreadsheet structure of csv files present.

• ./data/reference_data/
  This folder contains 2 files that need to be updated when new affiliations occur in the input data:
  AffiliationInfo.csv
  --> Manually curated list of standardized reference affiliations, with information added about the country, QH, group, ...
  AffiliationMappingFile.csv
  --> Mapping between standardized affiliation names and other possible writings of affiliation names

Folder structure

./notebooks/
--> contains the Jupyter notebooks with statistics for the LWUA. (see notebooks for description of content itself)

./data/
--> contains the data used in the LWUA.

./templates/
--> contains the templates used to semantically uplift input data into RDF.

./src/py/
--> contains the pythons scripts used to standardize affliations information

./config/
--> contains the sembench.yaml files that lists the tasks that need to be executed when running this kgap project.