Open Data

Data are (yes, it's plural) everywhere, but what is available as 'open data' is also vast.
"Open data is data that anyone can access, use or share. Simple as that. When big companies or governments release non-personal data, it enables small businesses,
citizens and medical researchers to develop resources which make crucial improvements to their communities." (The Open Data Institute, https://theodi.org/what-is-open-data)

Where can you find open data?
Well, local authorities, Governing Bodies and Government funded research projects provide a wealth of open data ready for reuse by others. Examples include:

The European Data Portal, https://www.europeandataportal.eu/en, has the
strategic objective of improving accessibility and increasing the value of Open Data.
UK Government data can be searched at https://data.gov.uk/.
Subject specific data is widely available, for example a range of data is provided by the Office of National Statistics (ONS), https://www.ons.gov.uk/, which provides a range of economic, demographic, educational data, geographic data and more.
Official Labour Market Statistics can be found at https://www.nomisweb.co.uk/default.asp.
Open access to Scotland's official statistics https://statistics.gov.scot/home.
Scottish Forestry Open Data https://open-data-scottishforestry.hub.arcgis.com.
Open Data Wales https://www.opendata.wales.
Open Data for Northern Ireland https://www.opendatani.gov.uk.
An analysis of data for qualifications can be found at the Register of Regulated Qualifications, https://register.ofqual.gov.uk/, with a full data set being downloadable.
An example of a local authority is that of Nottingham City Council and the trees which they maintain https://www.opendatanottingham.org.uk/dataset.aspx?id=209.
Sports facilities data, in England, can be searched at the Sport England Active Places web site, https://www.activeplacespower.com/opendata. A downloadable folder with a range of data sets (as csv 'comma separated values') files can be downloaded for analytical purposes.

If you use open data from a single source, then you will usually attribute the data to that organisation. If, however, you use information from several information providers and multiple attributions are not practical in your product or application, you will typically use a statement such as "Contains public sector information licensed under the Open Government Licence v3.0".

For the grounds care industry, a good starting place is to investigate the data available from Sport England for sports pitches and that of the ONS (available as .csv or .xsl files, as well as other formats) in relation to population sizes.

Information might be sought on how the different regions of England compare in sports provision, for example in relation to grass pitches, such as football or tennis courts. The sports data is available as numerous csv files, so this data needs to be converted into something which could be readily interrogated. Creating a MySQL database from selected data, cleanse unnecessary data fields and rename fields to get the data ready. Another approach which is worth investigating is importing relevant, cleansed csv files into Python, which is really useful if longitude and latitude data is to be taken advantage of, so as to create maps of sports locations.

One issue with the supplied tennis court data from the Sport England dataset, for example, was that the playing surface type was not directly linked to the courts at a facility, so these needed to have a separate table created to enable a link to be made. With open data there will be a need to adapt it and recode elements to best suit your need as it will rarely be exactly what you are after but combining data from more than one source can help to provide useful insight into an issue being investigated.

Tennis courts
The total number of courts, in England, at the beginning of 2022 were found to be as follows:

Court surface type Number of courts
Grass 1,419
Acrylic 660
Acrylic-Clay 362
Artificial Grass 2,631
Clay 401
Concrete 3,822
Macadam 10,759
Polymeric 39
Shale 85
Textile 81
Other 1139
Total 21,398

Combining regional tennis court data with ONS population figures indicated that there were about 15 courts per 100,000 of population in the North-East, to 36 courts per 100,000 of population in the South-East; a ratio of 2.4:1 in favour of the South-East. Is this equitable? Is there a good reason why there is this difference? Analysing such data does start to promote a debate as it is a value judgement as to what is appropriate or not.

Grass football pitches
For the grass pitches the analysis might try and identify total pitches and estimated areas and relate this to the range of provision required and likely maintenance inputs needed to achieve this provision.

An initial analysis indicated that the number of football pitches available ranged from 79 - 102 per 100,000 (ratio of 1.29:1) of population throughout England, except for London, which was 45 pitches per 100,000 of population, although considering the built-up nature of that region this is not really a surprise.

Football pitch type Number of pitches
Adult Pitch 24,656

Junior (9v9; U11/U12) 2,664

Junior Pitches (11x11: U13/14) 7,573*

Junior Pitches (11x11: U15/U16) 7,574*

Mini (5-a-side; U7/U8) 2,277

Mini (7v7: U9/U10) 9,557

Total 54,301

*This was actually a combined figure of 15,147 but has been split 50/50 for the different types of junior pitch size.

Using other information about 'typical' pitch maintenance inputs and the type of standard of pitch can also help to give an indication of the likely workforce needed to support this type of provision. For the adult football pitches totalling 24,656 this might have the following analysis:

Standard Pitches desired at this level Equivalent number of pitches Maintenance inputs per pitch (Hours) Total inputs for all pitches at this level (Hours)
Basic 10% 2,466 200 493,200
Satisfactory 25% 6,164 350 2,157,400
Good 30% 7,397 500 3,698,500
Very Good 25% 6,164 900 5,547,600
Excellent 10% 2,465 1,200 2,958,000
Totals 100% 24,656 n/a 12,697,300

To arrive at an estimated full-time equivalent for staffing, then 1,300 hours of productive time can be considered typical for a worker, which therefore equates to needing 9,767 workers to maintain football pitches to the desired provision spread.

This could also lead to another question that would then need to be answered, which is 'Does the number of artificial pitches, especially the newer 3G infilled pitches, help to compensate for the reduced number of grass pitches available for football?

The following data, providing the number of individual surfaces and an estimate of the total area is given for the main artificial sports surfaces:

Surface Number of individual surfaces / pitches Total area (m²)
3G infill (mostly rubber crumb) 4,554 12,220,666
2G sand-filled 2,048 6,972,664
2G sand-dressed 793 3,616,132

You may also wish to provide an estimate of total mass of rubber crumb infill used as the performance layer within a 3G pitch (nearly all are rubber crumb infill, an extremely minute percentage are other infill). If a typical infill quantity is 15kg per m², and if a typical full sized 3g pitch surface area is 7,000m², to include safety surrounds, then each pitch might have 105 tonnes of rubber crumb infill present. Or to put it another way if there were 12,220,666m² of 3G carpet at the stated rate of infill for rubber crumb this would equate to 183,310 tonnes of material which is classed as a micro-plastic.

Clearly a lot more analysis is needed (and especially verifying accuracy of figures), breaking the data in market segments ¯ age groups, gender, quality of the grass pitches and how many games they can sustain without deteriorating below a certain standard, but again data analysis opens the way for an informed discussion and debate to take place. The above examples just scratch at the surface of how open data might be used to improve understanding and for better decision making within the grounds care industry.