Upload geographical time-series data as a CSV file. The csv file must have the following columns:

Column 1: has header 'timestamp' and contains timestamps as strings, matching those available on the timestamp slider,
Example: 2016-10-12

Column 2: has header 'geom' and contains geographical locations (currently points only),
Example: POINT (-2.254 53.397)

Columns remaining: header(s) will be used as measurement name(s) and values should be numeric (non numeric will be converted to null)

Note that the uploaded file's data is stored locally on the browser, and only used for visualisation on the map, within this browser session.
Download data
UoM Turing EPSRC

This web application is part of the project "Understanding the relationship between human health and the environment" funded by the Alan Turing Institute

Would you like to run your own copy of this web application and/or improve the code? You can find the source code at: github.com/UoMResearchIT/geo_sensor_gaps Pull requests welcome!

Site measurement data uses imputed data originally sourced from MEDMI and AURN. We have cleaned this data and imputed missing values. Click on the 'Download data' button for further details and to access this processed data.

The 'pre-loaded' data (under 'Select estimation method') contains regional estimates data derived from the above pre-processed site measurement data. Click on the 'Download data' button for links to obtain further details and to access these files.

The https://pypi.org/project/region-estimators python package was used to generate the 'pre-loaded' regional estimations file.

A Django web application to display sensor data on a map, allowing comparison with regional estimates and that can generate time-series graphs for each sensor location.

All data is loaded into the web app's database by the (admin) user at runtime, from 4 CSV files comprising 2 data files and 2 metadata files. See the github documentation section on how to load data for more detailed instructions.

Regional estimates can also be calculated at run-time. The estimation methods (click on 'Select estimation method' and see all options except 'pre-loaded') are those available in the python library: https://pypi.org/project/region-estimators ('concentric-regions' and 'distance-simple' at time of writing)

Users can also upload their own data locally (within a browser session), again via a CSV file upload, so that their own data can be compared alongside the actuals/estimates data pre-loaded.

Getting started:

Click on a site to see site info and also the option to view site and estimated data across all timestamps.

Click on a region to see region info. If no sites exist for this timestamp, either:
(i) use slider to find another timestamp
(ii) use 'Select measurement' option to change measurements.

Detailed instructions:

See our github documentation User instructions for more detailed instructions.