Geospatial data and official statistics integration 

Definition and sources of statistics and geospatial data 

In general, integration of geospatial data and statistics   is a vital procedure to allow comparisons at local, sub-national, national, regional, and global levels for decision-making processes within and between countries and thematic domains. Its practical implementation contributes to supporting social, economic and environmental policy decisions by the various stakeholders. At the national level, it enables the flow data sharing among the National Statistics System’s (NSS) institutions, taking advantage of interoperability of geospatial and statistical information. Its contribution to national policies impacts by unlocking of new insights and data relationships that would not have been possible by analysing socio-economic, environmental, or geospatial data in isolation; increasing at the same time information on smaller geographical areas to leave no one behind in the decision making processes.

Nevertheless, geospatial data   and statistics   do not share the same nature. Statistics respond to conceptual frameworks and are quantitative data, mostly ratio data that have been organized through mathematical operations [1]. Instead, geospatial data constitutes a set of organized and related pieces of information that usually have geocoding or coordinates to represent relationships of objects in the space. Complete sets of geospatial data [2] include location features (like cardinal scales of the earth), attribute information (like characteristics of an observed spatial object), and the temporal dimension during which the features of the object and location co-exist.

Geospatial data and statistics integration is the technical practice of consolidating data from the above described disparate sources into a consolidated dataset in order to providing users with consistent access and delivery of data across a wider spectrum of matters [3].Only in the last decade the practice of incorporating digitalized data using geo information systems(GIS) has been generalized and acquired especial relevance at National Statistical Offices (NSOs) and NSS all around the world. Given the growing enabling impact of information technologies for official organizations, GIS are increasingly being integrated to all decision-making process. Advances in data interoperability protocols and standards have greatly supported this endeavor also. Other substantial drivers of this change include the sophistication in data management processing techniques, the generalized digitalization of data in general, the massive use of Global Positioning Systems (GPS) in handheld devices and also the decreasing costs of satellite images.

The 2030 Agenda for Sustainable Development specifically recommends NSOs to pursue the integration of diverse data sources and support the measuring and monitoring of the targets and global indicator framework for the Sustainable Development Goals (SDGs) while they prepare, implement and disseminate the results of the 2020 Round of Population and Housing Censuses. Figure   maps all possible indicators that could be generated integrating statistics with geospatial data according to each goal of the SDGs.

This special topic also relates to the data challenges involved in the data revolution   endeavour and fuels the need to consider data ecosystems beyond the functioning national statistical system in order to narrowing gaps in statistical development. In most cases of least developed and low income countries (LMICs), the production of geo enabled statistics will require technical and organisational efforts toward modernizing the national statistical system.

Besides, some national statistical systems from fragile states, small island developing states, LMICs would greatly benefit from the modernisation that geospatially enabled statistics can provide to their decision making processes. This will certainly further spur their ability to proactively respond to and align with the new, emerging, and rapidly evolving statistical environment spawned by the sustainable development agenda in the long run.

Why is the National Strategy for the Development of Statistics (NSDS) a key entry point for improving Geospatial data and official statistics integration? Why focusing on Geospatial data and official statistics integration during the NSDS design?

Geospatially enabled statistics entails the implementation of a fully-fledged geo infrastructure mediated through a process-oriented sequence of steps until its final deployment. However, in order to assure its sustainability in the organizational realm, it needs to lean against a broader framework to improve and maintain its functionality. The overarching lifecycle approach that the NSDS represents warrants the continuous improvement and updating in the integration of geospatial and statistics within a wider spectrum of actors and sources.

One of the connotations of the NSDS is to aid the process for statistics development, mainstreaming statistics into national policy and planning process. This quest demands time and effort. The production of geo-enabled statistical information needs not only responding to the needs of geo-oriented users (such as those committed to the territorial and environmental decision-taking) but also mainstreaming all other geo-data related sectors and players , like logistical companies or transportation industries. Including these actors into the resulting geospatial data ecosystem will input, and at the same time require, the unique insights that the integration of statistics and geo-information can deliver.

National policies that may be affected by geo enable statistics include, but are not restricted to; i) all SDGs that require the territorial dimension [4], ii) decisions related to natural disasters' management, iii) endemic, epidemic and pandemic analysis, iv) poverty mapping and v) the use of mapping for education planning and in health care delivery [5], among many other areas of policy-making.

Main entry points in the NSDS lifecycle 

As geospatial data and statistics can be integrated in a step-by-step guidance [6], the preliminary stage, design and deployment stages and related steps of the NSDS can be mapped accordingly, specifying each of the activities embodied in the tasks needed to geo enable statistics. 

An important insight to keep in mind when mapping is that although a step-by-step guidance for integrating statistics and geospatial data follows a chronological and process-oriented rationale in parallel to the NSDS life cycle, it doesn’t assume expressly the monitoring and assessment angle. This is because in general one-time implementations do not necessarily imply a lifecycle process, without the valuable stocktaking of lessons arising from the implementation of the sequence of activities. A harmonic complementation of a step-by-step guidance with a lifecycle strategy acquires especial relevance when it is needed to input knowledge and planning of tasks from geo-enabled statistics practitioners to NSDS planners and implementers. The life-cycle rationale will aid the continuous updating of geospatial and statistics integration processes consolidating with the regular repetition of the cycle the excellence in the practice of geo-enabled statistics.

The following subsections map the common tasks that the step-by-step guidelines and the NSDS lifecycle share when considering the integration of geospatial data and statistics. Steps marked in blue refer to the Guide on geospatial data integration in official statistics. 

  • Preliminary stage: This stage involves gathering and establishing an enabling environment toward a common vision all the actors that could use and produce geospatial data leaded by the visions and actions of the NSO.
    • Engaging stakeholders |Step 5.1 of the guidance
      • This task of the guidance is related to Step 1.1, Step 1.2 and Step 1.3 of the NSDS guideline. At this point, the guidance aims to provide to the preliminary stage of the NSDS with the identification, summoning and mapping of all geospatial data-related actors. These should be supplied with the kit of policies, roadmap and advocacy materials in order to organize their contribution to bring the point of view from geo-enabled statistics. 
    • Preparing |Step 5.1 of the guidance
      • This task of the guidance is especially related to Step 2.1 and marginally to Steps 2.2 to 2.3 of the NSDS. Its role is to integrate selected geospatial actors in the team building exercises and workshops. Actors will provide and stress attention on awareness of this specific data challenge. This will help to develop a preliminary vision and a general consensus on data integration ambitions.
  • Design stage
    • Assessing| Step 5.2 | Step 5.3 | Step 5.4 of the guidance
      • These tasks of the guidance are related to Step 3.1 and to Steps 3.2 to 3.3 of the NSDS. It will input with a comprehensive assessment of the capacity of productive factors from the NSS regarding geospatial sources, generating an inventory of available and needed geospatial human expertise, technologies and geospatial data available for the NSDS. Finally, related to Step 3.4 of the NSDS, the geospatially –related actors will produce an expert report on the outcomes.
    • Envisioning| Step 5.5 | Step 5.6 | Step 5.8 of the guidance
      • These tasks can provide substantive contents to Steps 4.1, 4.2, and 4.3 of the NSDS. The guidance tasks will aid in establishing and integrating mission, vision and goals for the geo-infrastructure to be consolidated for the future geo-enabled statistics. The formulation should be done in such a way that it will lead to the definition of a manageable set of objective indicators for the goals, including dissemination ambitions, discriminating between the medium and long run.
    • Elaborating | Step 5.2 | Step 5.3 | Step 5.4| Step 5.5 | Step 5.6 | Step 5.8 of the guidance
      • These tasks include inputs to identify costs, possible funding sources and risks for Steps 5.1 to 5.3 of the NSDS. Regarding Steps 5.4 and 5.5 of the NSDS the guidance doesn’t provide steps as inputs, although monitoring should be derived from initial steps of the sub stage for the elaboration of the action plan.
  • Deployment stage
    • Implementing & monitoring| Step 5.6 | Step 5.7 | Step 5.8 of the guidance
      • These tasks include inputs to disseminate, mobilise and implement the plans for Steps 6.1 to 6.3 of the NSDS. They can provide detail of how to implement all previously planned activities, especially those that harmonise, disseminate and enable the interoperability of integrated geospatial data and statistics. Implementers of the NSDS should consider that this may probably be the first implementation round of the geo-infrastructure and ambitions of dissemination should be particularly adjusted.
      • As per Steps 6.4 to 6.7 of the NSDS, monitoring activities should be derived from the previous steps and based on medium run indicators, focusing in gaps of goals and adjusting as needed. 
    • Evaluating 
      • There are no tasks from the step-by-step guidance that will provide inputs for evaluation. Evaluation results should be based on long run indicators, focusing in gaps of broader goals and adjusting as needed for next NSDS exercise.