(1) What is Spatial Data? Why is it important?

“Spatial data” refers to any data with reference to a specific geographical location. In fact, “spatial data” has long been integrated into our lives. We can use the map applications in our mobile phones, for example, combined with Global Positioning System (GPS) to locate nearby restaurants, parking lots or bus stops by their addresses, streets or building names and more.

Geographical location is the bridge between information. It can associate relevant information of facilities that are above, on and under ground level to support the development of various smart city applications. According to overseas academic research, more than 80% of all data is location-related information.

Common Spatial Data Infrastructure (CSDI) aims to provide government departments as well as public and private organisations with an information infrastructure to promote the sharing of spatial data and support the development of various smart city applications. It is envisaged that the establishment of CSDI standards to facilitate linkage and integration of spatial data from various government departments and that of the whole territory, and the provision of a common platform for integration and exchange of geospatial information will be conducive to the provision of reliable spatial data services for the efficient use of resources, development of a smart city and sustainable development.

Throughout the years, various government departments as well as public and private organisations have made use of the Geographic Information System (GIS) to facilitate the management of individual geographic related spatial data and/or the development of different map service platforms. The spatial data thus generated, therefore, comes from different government in-house data systems and are without common standards. The development of the Common Spatial Data Infrastructure (CSDI) aims to provide a platform to link and integrate geospatial data across various government departments to facilitate easy sharing and use of high-quality spatial data by government departments, public and private organisations, academics as well as the general public.

There are two main categories of spatial data, namely Framework Spatial Data Theme (FSDT) and Common Sharable Spatial Data (CSSD). FSDT provides a standard geographic framework for geocoding or referencing other data sets. For example, street address, which is commonly maintained by multiple organisations, once standardised and geo-coded to location, can be further visualised and analysed geospatially in ways that would have never been possible otherwise.

CSSD are usually those datasets, such as planning data, census data etc., provided and maintained by unique data owner. These types of common sharable data, once geo-coded to location, are usually demanded by multiple agencies and/or members of the public for use in their spatial analysis or applications.

(1) Federal Geographic Data Committee (United States)

Aims: Promoting the coordinated use, sharing and dissemination of geospatial data nationwide across government, academic community and private sector

Benefits: Enabling the open up of spatial data facilitating city management and innovative application/ data analytics

(2) Singapore Land Authority (SLA) and the Government Technology Agency of Singapore (GovTech) (Singapore)

Aim: Making authoritative spatial data available

Benefits: Support decision-making, public security and cost-effective businesses

(3) Geospatial Commission (United kingdom)

Aims: Maximizing the value of all UK government spatial data, and to create jobs and growth in a modern economy; using spatial data more productively

Benefits: Unlocking up to £11 billion of extra value for the economy yearly; stimulating innovation in the economy and driving the development of growing digital economy

(1) Boosting digital economy

In this era of autonomous applications, the capability of 3D digital map can be extended to support a wide range of applications (e.g. self-driving car and drones) and foster the creation of a digital twin by leveraging the Internet of Things, building information modeling (BIM) technology and big data analytics.

(2) Enhancing data-driven decision-making in the Government

By collecting the Dengue Fever Ovitrap Index from 3 000 locations across the territory and presenting the index figures via an interactive map interface with trend data, the Food and Environmental Hygiene Department (FEHD) can readily identify the more affected areas and accordingly deploy manpower to tackle priority sites.

(3) Spurring innovations and improving quality of life for the wider community

A retail chain store is considering to open a new shop. Socio-economic data such as age, income and housing type of residents, as well as information on traffic pattern, foot traffic and the number of residences in the area can be helpful when choosing a location.