The MEDLINE Dashboard is a dynamic dashboard allowing for the easy manipulation and visualisation of the different aspects of MEDLINE data, including the MeSH Heading descriptors. It aims to provide public health professionals and data analysts with intuitive and accurate tools to explore their own KPIs, making them independent of often busy ICT departments. The backend is based on the Elasticsearch technology that allows for powerful queries using the Lucene language sintax. The frontend is based on the Kibana add-on that allows the user to build and share their own dashboards of visualisation modules.
Prerequisites:
- Python 3
- Does not work on python 2.X
- Elasticsearch vers. 6
- Kibana vers. 6
Load the data onto the local Elasticsearch instance:
On Linux/Mac:
chmod +x influenzanet_load.sh
./es_load.sh
On Windows:
es_load.bat
For detailed installation of Elasticsearch and Kibana check the following instructions:
QMidas technology is developed by Quintelligence and AILab at Jozef Stefan Institute, considering the needs and requirements of the MIDAS Project use-cases across Europe.
Parts of the library were developed under MIDAS Project, funded under the call SC1-PM-18-2016 with the Grant Agreement nr. 727721.