“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.
To prepare for the roll out of the CSDI portal, all departments have been asked to submit on a yearly basis annual spatial data plans to set out the datasets they plan to release in the coming three years. The first set of annual spatial data plans was published on government websites at the end of 2021.
All government departments can access and contribute to the CSDI portal, which is now available for government internal trial use and targeted to be made available for public use free of charge by the end of 2022. It is expected that at the time the CSDI portal is available for public use, over 500 spatial datasets from over 50 departments as listed in their respective annual spatial data plans, covering different aspects such as planning, lands, buildings, works, population, transport, etc., will be publicly accessible through the portal.
(1) Geo-tagging of non-spatial data
Geo-tagging of non-spatial data usually involves the adding of geographical identification such as latitude, longitude and grid coordinates, or administrative boundaries and addresses.
(2) Data Specification
Spatial data on CSDI must meet the established data specifications with detailed description of the data, including the data definition, content and structure, quality, workflow, maintenance, delivery and exchange.
Spatial data released on CSDI will contain metadata, describing the source and definition of the dataset, update time and contact information, etc.
(4) Open and machine readable format
Open and machine readable format refers to data formats that can be read and processed automatically by free and open-source softwares without human intervention to facilitate programming and spurring community innovation. Spatial data released on CSDI will be in GeoJSON, GML, KML and CSV formats which are commonly used by the industry.
(5) Application Programming Interface (API)
An API is a tool that enables a software application to share its functionalities and data with other software applications. It can greatly facilitate application development by allowing application developers to integrate specific functionalities and data to their applications without having to “reinvent the wheel” and spending time to create functionalities and data that already exist.
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) Map Application Programming Interface (API)
The Map API is an API for the CSDI portal to share map data with the public and private sectors to support their applications requiring map display. It enables the community to build innovative applications enriched with locational and other features such as virtual city navigation;
(2) Geo-tagging Tool
It is an enabling tool to convert non-spatial data (e.g. demographic data or ground features) into a form of spatial data for display on a map. For example, a user can use the tool to convert the demographic data of different districts, which is textual and non-spatial in nature, into spatial data which can then be shown on a digital map rendering the map with the spatialised demographic data more informative;
(3) Address Data Infrastructure (ADI) (GeoAddress)
It is an enabling tool to standardise location identifiers across departments facilitating interoperability of address information across departments. The standardisation can help B/Ds improve public services, such as postal delivery, assessment of rateable value, planning of emergency services and management of complaint cases (e.g. calling by 1823); and
(4) District-based Spatial Information Dashboard
It is a web-based application that uses charts, gauges, maps, and other visual elements to display spatial datasets in an easily readable form and provide
public and private sectors with consistent, up-to-date and consolidated district-based spatial information. In short, a dashboard assimilates different online information and provides data analytics. For example, a dashboard can be used to display a summary of the number, size, core facilities and management responsibility of public open spaces in a district. Overseas experience shows that dashboards can be used for city management as well as an understanding of public opinions and trends.
(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.