Using Irish Open Data

By Angela C

April 30, 2021 in open data APIs

Reading time: 2 minutes.

Looking at uses of open data such as that available through the Irish open data portal at https://data.gov.ie which can be mined and processed.

I have been using the CKAN API’s for retrieving the lists of datasets available on the Irish open data portal at https://data.gov.ie. There are over 10,000 datasets which are available in a variety of formats such as CSV, JSON, GeoJSON, JSON-STAT etc

So far I have been working with the APIs for retrieving the lists of datasets (known as packages on the CKAN API), the lists of publishers (organizations), the list of tags etc. Then based on these lists that I have pulled into some Jupyter notebooks, programmatically retrieve the actual dataset resources.

The main types of datasets I have looked at so far are

  • the weather datasets from Met Eireann available in CSV format and JSON formats through an API.

  • bike sharing datasets from Dublin Bikes, Coca-Cola Zero bikes, Moby bikeshare. These datasets are available in CSV, GEOJSON formats as well as an API.

  • various economic, social and statistical data from the Central Statistics Office (CSO) in JSON-STAT and PX formats.

  • GEOJSON datasets by publishers such as county councils, libraries, beaches, heritage sites etc.

  • Many other datasets have geographical locations included and therefore can be used with Python packages such as GeoPandas and then visualised on maps using various libraries such as folium and plotly.

While there are over 122 publishers list, many of these are government departments or county councils. Many of the datasets listed for the government departments are available through the CSO.

The CSO has a dissemination database system, PxStat that is replacing it’s old StatBank. While you can navigate here and select and filter data, the main datasets can be retrieved like all other datasets listed on https://data.gov.ie using the CKAN API actions.

The datasets available through the CSO can be analysed to gain insights into socio-economic trends. This could help identify and extrapolate demographic and market trends.

I am currently working on learning how to create interactive data visualisations using Dash on some of these datasets.