Recommendation 9

Recommendation 9: Adopt an integrated location-based approach in the collection and analysis of statistics on different topics and at different levels of government

Why:

  • Much statistical data has a geospatial component
  • The techniques and mechanisms used nationally and in different policy areas for location-based data collection and analysis are not sufficiently well integrated to support pan European or cross-domain analysis and comparisons
  • The cost of collection and integration of location-based statistical data hinders the timeliness and extent of analysis that can be undertaken, inhibiting the potential value of the policy evidence base
  • Geospatial information combined with statistics underpins evidence-based policy making and political decisions at all levels in government
  • Periodic monitoring of geographically-related indicators over time is a typical requirement for many EU Directives, e.g. the Marine Strategy Framework Directive, being addressed by the EULF Marine Pilot
  • With a common geospatial framework policy makers in public administrations will be able to combine different methods of location-based data collection to inform their policy decisions, including census data, transaction data, social media information etc.

How:

  • Member States create and maintain an accurate and up-to-date knowledge base of where their citizens and businesses are located. This will make the collection of census and other statistical data as straightforward as possible
  • Member States have a common geospatial reference framework for statistics to enable timely, accurate and efficient production of location-based statistics. This should be based on geocoded registers of administrative units, addresses, buildings and dwellings and use consistent and persistent identifiers to reference relevant information. The geospatial reference framework for statistics should be based on INSPIRE to enable the widest possible collation of harmonised data
  • Member States have mechanisms to enable frequent (‘dynamic’) collection of statistical information taking account of this ‘location’ knowledge
  • Opportunities are taken to streamline and improve statistical data collection, taking into account new sources of information, such as social media, web analytics etc.
  • The spatio-temporal dimension of statistics is captured in a format that enables it to be used readily in a GIS for geostatistical analysis, with consistent geo reference data and other consistent coding to enable it to be analysed at different geographic / administrative levels
  • The geospatial reference framework for statistics forms the basis for the collection of census data, including supporting dynamic census data collection
  • To support the production of statistics and census information, it is important to understand the origin, production process and other aspects of the quality of geospatial data. INSPIRE metadata should be used as the basis for this documentation
  • Public authorities apply analytical techniques (customer analytics) to help improve public services. For example, Transport for London uses ‘big data’ analysis of vehicles, vehicle location, traffic information and payment cards to reveal patterns or trends and enable action to be taken

Challenges:

  • Too much data and not enough information – there is so much data that can be collected and analysed, with risk of hiding or missing the message
  • Drawing conclusions based on location may be too simplistic to determine appropriate interventions
  • Establishing a common basis for analysis and comparison in multiple geographies and domains is very challenging

Best Practices:

Further reading:

Nature of documentation: Technical report

Categorisation

Type of document
Document
Licence
European Union Public License, Version 1.1 or later (EUPL) 
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