Different aspects of the implementation of GSGF Europe are studied and presented. The provided material aims to help and assist users to produce geospatial statistics in a consistent, systematic and harmonised way. The material presents the GSGF Europe reference architecture, strategy, governance and other non-technical aspects and point-based foundation for statistics. It also studies geospatial statistics according to data collection method, links of the GSGF to other frameworks in Europe, as well as confidentiality and quality aspects.



Reference Architecture

Effective collaboration starts by ensuring that the statistical and geospatial communities can share the same view of their operating environment and that they discuss the same concepts on common ground. Only then can solutions be built on the same common conceptual and theoretical base. In addition, a reference architecture approach will help to translate the vision into implementation strategies and priorities in a consistent and systematic way and clearly show how the various components and organisational roles fit together. To support this, the first steps have been taken in describing the GSGF Europe Reference Architecture.

The GSGF Europe Reference Architecture aims to act as a template for statistical organisations in the development of their own geospatially enabled enterprise architectures. It provides a common framework incorporating geospatial frameworks, standards and processes in a consistent manner, in order to produce geospatially enabled data and statistical services. The first version of the Reference Architecture describes the actors, roles, processes, services and concepts.

Documents to download:

Guidance and Analytical Tools for the Implementation of the GSGF Europe Reference Architecture

As a continuation of the GSGF Europe Reference Architecture, supporting material for its actual implementation has been designed. Two kinds of supporting material are proposed. First, schematic representations of the way data are transformed within geospatial statistical processes are provided, with different trajectories illustrating different business and technical contexts. Second, the first trial of analytical grids for a selection of sub-processes is done to help assess the maturity level, from an architectural point of view, at each stage of the statistical geospatial process.

This material aims to guide stakeholders in evaluating their own context in comparison with the GSGF Europe specification, identifying the components that are already available, and those to be built. The supporting material aims at highlighting specific and non-shareable technical implementations of statistical processes, in order to replace them with shared and generic solutions, in accordance with international standards. Stakeholders are invited to use these tools as a help to build transversal knowledge of the processes currently at work, and to establish an achievable target, allowing progress to be made in accordance with the principles of the GSGF.

Documents to download:

Non-technical aspects

When implementing a framework, such as the GSGF,  there are several organisational, legal and other non-technical aspects to consider in addition to the technical sides. Strengthening of institutions and governance, as well as improved communication with stakeholders are decisive. Long-term financial sustainability, capacity and capability development, as well as innovation are all vital for geospatial information management, integration of geospatial information in statistics production and to ensure interoperability of data and statistics within the frames of a national spatial data infrastructure (NSDI).

This document focuses on the non-technical aspects, which can also be categorised as governance, innovation and policy matters. The document aims to highlight the foundations for good ‘integration-environments’ for stakeholders across sectors at both administrative and operational levels.

The document to download:

GSGF Europe: Strategy, Governance and Other Non-technical Aspects

Point-based foundation for statistics

The GSGF Europe assumes that a point-based geocoding infrastructure is far more flexible in terms of production and maintenance than a conventional area-based infrastructure with fixed output areas, such as enumeration areas or other small area geographies. A point-based geocoding infrastructure is also better equipped to integrate data in order to exploit better the spatial dimension of statistics (e.g. spatial analysis).

This paper outlines the fundamentals of a point-based foundation for statistics. A point-based foundation for statistics is a technical and methodological framework to enable assignment of a precise geographical reference to a statistical observation. The paper also discusses the constraints and challenges related to the establishment of a point-based foundation. Furthermore, the paper discusses approaches for implementing a point-based geocoding infrastructure.

The document to download:

GSGF Europe: A point-based foundation for statistics

Confidentiality in Geospatial Statistics

The statistical community has a well-established body of knowledge and practice on statistical confidentiality and data protection issues. On the one hand, it ensures confidentiality of data used in the statistical production process to promote users’ and institutional trust and, on the other hand, it seeks to protect the privacy of the individuals from the sensitive data that contain personal information. Geospatial data raise new challenges in terms of personal data protection, so that the disclosure risk is a great matter of concern when you deal with geocoded data.

It is relevant to develop harmonised and consistent confidentiality methods and techniques to protect private information that is geospatially enabled and that can handle both statistical and geospatial data within the statistical production process. Recommendations to avoid privacy risks and data disclosure in the production and dissemination of geospatial statistics are presented in this document.

The document to download:

GSGF Europe: Managing Confidentiality in Geospatial Statistics

Big Data

Big Data may complement existing data sources and potentially be integrated within the existing statistical production process and reference architecture. In some cases, Big Data may be used to replace customary data sources in order to reduce the response burden, increase data flow and their geographical detail and provide auxiliary variables. Since Big Data are not owned or produced by NSIs, it is challenging to integrate this type of data within the statistical production process and also to ensure stable and timelier access to the sources since data deliveries depend on external private providers.

The document on Big Data aims to describe the key characteristics of this emerging data source that are important to consider as a collection method for statistical purposes. Both technical and institutional topics are discussed and two different use cases are considered and analysed when it comes to geospatial statistics through the prism of the GSGF Europe: i) Big Data as reference data on geography; and ii) Big Data as location data of a phenomenon.

The document to download:

GSGF Europe: Geospatial statistics according to data collection method BIG DATA

Survey Data

Most statistical production processes rely on survey data to collect, process, analyse and disseminate information. Thus, they constitute a customary data acquisition method for most statistical authorities. However, there is increasing awareness that conventional surveys, including censuses and questionnaires, do not meet the user demands on data availability, usefulness, timeliness, spatial resolution and territorial flexibility. There is a need to respond to the growing need to add the spatial dimension to customary data sources, processes and derived outputs in order to geo-enable the statistical production and produce geospatial statistics.

The document on survey data aims to promote long-term processes and objectives through short-term actions in data collection management by geo-enabling statistical production and bringing the geospatial perspective into statistical pipelines which may depend on survey data as input data. Contents on spatial sampling and geo-solutions to survey data management are presented and specific recommendations within the GSGF Europe are proposed.

The document to download:

GSGF Europe: Geospatial statistics according to data collection method SURVEY DATA


QAFgeo – Geospatial Enhancements of the ESS Quality Assurance Framework

While within the common quality frameworks for the ESS (Code of Practice – CoP – and the Quality Assurance Framework – QAF) various types of data (e.g., survey data, administrative data, privately held data) are addressed in general terms, geospatial data are neither properly nor specifically mentioned, underestimating their value and integrative role on producing official statistics.  Thus, to increase the visibility, awareness and understanding of geospatial data and to strengthen the importance of geospatial aspects within the ESS some changes to the QAF regarding geospatial aspects are proposed in order to appropriately address and formalise geospatial data within this framework.

The documents to download:



Recommendations for Geospatial Quality Reporting

The integration of statistical and geospatial data must consider all phases within the statistical production process contributing to all dimensions of quality of inputs and outputs. Assessing the quality of the geospatial and statistical data and related integration processes and activities used across the GSGF is fundamental to its implementation. This document aims to establish guidelines for the suitable and standard assessment and reporting of quality aspects related to geospatial data and their integration within the traditional production of official statistics. Recommendations are proposed on what could be included in a quality report and which indicators are suitable for this purpose. The documents to download: GEOSTAT 4: Recommendations for Geospatial Quality Reporting GEOSTAT-4_Annex_SIMSgeo-Recommendations-for-Geospatial-Quality-Reporting


Quality Checklist for Geospatial Processing Related to a Specific Statistical Product

A quality management approach that includes geospatial data and geospatially related activities should be integrated into the statistical production process in order to ensure quality assurance in a comparable and sustainable manner over time.

The provided quality checklist for geospatial processing related to a specific statistical product is a generic checklist for a systematic quality assessment of geospatial aspects and processing related to a specific statistical product. The checklist is generic in the sense that it applies to every statistical product which intends to produce statistical-geospatial outputs, including geospatial statistics.

The document to download:

GEOSTAT 4: GEOCHECK: A Quality Checklist for Geospatial Processing Related to a Specific Statistical Product

Frameworks Environment

The Global Statistical Geospatial Framework, the GSGF is a high-level framework. It is generic and permits application of the framework principles to the local circumstances of individual countries. The GSGF acts as a bridge between statistical and geospatial professional domains, between NSIs and NGIAs, and between statistical and geospatial standards, methods, workflows and tools. Several other frameworks are applied for the purposes of statistical and geospatial domains in Europe, and the GSGF also links to these.

In this document, nine other frameworks applied in Europe are reviewed and linked to the GSGF. The aim is that geospatial information and the related standards and aspects will be a natural part of the ESS statistical production. This is done by identifying links and roles between the selected frameworks and the GSGF.

Documents to download:

GSGF Europe: GSGF and Frameworks Environment

GSGF and Frameworks Environment: the CSDA, GSGF, GSBPM matrix