Digitalisation / Harmonisation of Data Standards
Case Studies
Policy Areas


Smart cities generate significant amounts of data every minute, and the frequency and complexity of this information naturally creates a challenge with respect to how policymakers can best share and integrate their work. Different stakeholders will often have varied protocols and technologies for how they collect and manage information, which makes the coordination of data between departments especially challenging.

Establishing harmonised standards, particularly within government, can help tackle such issues of uncoordinated data management. Standardising data means that each department collects information in a logical and consistent way that is recognisable to and compatible with all potential users. Such actions help to ensure the quality and consistency of information collected, and also help to maximise the potential value of data as a policy tool.

By ensuring harmonised standards, governments facilitate the seamless exchange and communication of information, both from public to private sector, as well as between governmental agencies at different levels, national to local or between municipalities. In turn, this creates multiple benefits, such as lowering the requirements for manipulating and converting data to a usable format, limiting the potential risks of different agencies duplicating data efforts (if government departments are fragmented with insufficient communication), and simplifying overall data exchange to have broader usability and faster adoption between departments.

Policymakers should therefore pay close attention to the interoperability of data as such issues are a critical feature of how data should be collected, shared and used to shape overall policy choices. One example is to ensure that all data is adequately digitised, preferably in a numeric form, such that they can be easily used and analysed. Many municipalities across the developing world operate key municipal data such as cadastral systems in paper-based form, creating a huge challenge for sharing, analysis, searching records, and a whole host of other important issues, until such records are digitised.

City governments and departments play an essential role in ensuring the interoperability of all types of data collected, both pre-existing and new. By storing data in machine-readable formats and adhering to open standards, city agencies can successfully promote interoperability and openness.

Take Taipei, for example.[i] In the early 2010s the city government was struggling to manage its parking system, as private spaces were not consistently recorded as public parking areas. To address the issue, the Ministry of Transportation and Communications issued a statute in 2015 for an Advanced Traveller Information System (ATIS), which harmonised both public and private parking information systems. The new Taipei Parking Information System has been functioning smoothly ever since, demonstrating how a set of common communication protocols for data formatting and integration can help to improve asset management and policy decision-making.

The harmonisation of data standards usually occurs early in the data lifecycle, often after a city strategy is defined, and before new data collection phases. Specific activities are usually coordinated by a government steering committee and should follow national or global standards. For instance, if a city aims to solve the problem of traffic congestion, the first step is to define action items, such as finding out how bad congestion is on the city’s busiest road sections and planning potential interventions accordingly. The city can then identify where to deploy sensors most effectively, either through a feasibility assessment or in-house research based on pre-existing data, and see what information needs to be collected for further analysis. Data interoperability and standards are critical, as they define the data’s format, rules and specifications – such as information on car type, size, speed and transmission frequency. Having clear data standards in place can also address legal concerns as to what kind of information can be collected, shared and used. These institutional frameworks should be followed at each phase of the data lifecycle.

Resource implications and key requirements


Data governance and management play an important complementary role to ensure the interoperability of the technologies in question. Here, data management refers specifically to data oversight, ensuring accountability over the data lifecycle. A low-cost and essential first step is for the city government to conduct a data and digital solutions inventory to identify what and how many existing data are already in municipal government systems and departments, how they are held, in what formats and under what standards for sharing. Conducting a data inventory can thus save governments significant resources and time by avoiding duplication of data-collection effort by different government departments.


Metadata are “data that provide information about other data”,[iii] or data that allow certain data to be found and used more easily in particular instances.[iv] Metadata play a key role in data knowledge management; they allow software and machines to save, exchange and process data by defining the common format of the data.[v] To be effective, metadata must be structured and consistent over various sources, adhering to a single (or at least similar) standard from the national level down. Inconsistency of metadata hampers interagency and technical-system interoperability and limits effective data dissemination to end-users. Common national standards help to reduce the challenges due to the inconsistency of format for data dissemination and data integration between different cities or government agencies.

A monitoring system with a simple automated process that identifies errors and strategies for lowering errors during data estimation or possessing procedures also supports good data governance.

Legal and institutional frameworks

Legal and institutional frameworks play a key role in setting boundaries on what data and information can or cannot be gathered, how they can be shared with the general public or across government departments, and the appropriate formats for data reporting and analysis. For instance, intelligent traffic systems generate copious amounts of sensitive data, so personal privacy and data protection is always a concern. Consequently, several municipalities across Europe have had to comply with the European Union (EU)-wide General Data Protection Regulation (GDPR) to ensure the legitimate collection, processing and use of data, in line with international privacy and security frameworks.

Potential private-sector participation

The private sector can support governments in the design and implementation of standardised digital communications infrastructure in a number of ways. Notably, providers of technology solutions can supply governments with essential services such as office software for managing, analysing and reporting on data. Companies such as SAS and UiPath are leading examples in this space, with the latter pioneering the use of artificial intelligence to automate and streamline office-related tasks such as data collection and cleaning for interoperability.

Governments should also consider what information the general public and private sector might need access to, if they were to design accessible and open access data platforms. In this way, it is critical to have open dialogue with the private sector to focus efforts on seamlessly exchanging the information that can provide most value.

Obstacles to implementation and possible solutions

Interoperability of information is a constant challenge in government as new requirements for data collection and updates in technology are consistently arising. It is important in this way that governments maintain regular communication and oversight of approaches between different departments, and seek to regularly harmonise standards for data collection and sharing. This can be particularly challenging when governments have insufficient funding to update their systems, or legacy formats of data collection (such as paper-based cadastral records) that are too large to standardise quickly and effectively. As well as procuring funds for new data, governments must consistently dedicate funding and time towards ensuring such legacy systems of data are brought into line with latest standards.

Another challenge arises where there are differing approaches between private operators. For instance in Tapei, when Taipei and New Taipei City merged their bus operating systems, the different algorithms each operator used for collecting and disseminating bus information led to widespread inaccuracies and difficulties when the two systems integrated. Eventually, the two cities had to engage in joint bidding to reinvent and reintegrate the system with a common algorithm and standard. [vi]

Lastly, the pioneer city that implements smart city initiatives ahead of central government is sometimes punished rather than rewarded, as its standards for data collection may be inconsistent with those later developed by the national government. Again, Taipei is an important example of this; the city initiated an Open Data and Open Government[vii] initiative around a year before the national government did, creating different formats and metadata for the system, which ultimately could not coordinate with national systems. With only a limited budget, Taipei City had to bring its Open Data back in line with the national standard, leading to costly and long-term reforms which continue to this day.


[i] Chen,Rong-Ming (4th September 2020) Interview by Y. F. Lin. “Interview with the Deputy Commissioner, Department of Transportation, Taipei City Government.”

[ii] United Nation (2019) “Introduction to data interoperability across the data value chain”. Available at:

[iii] Merriam Webster (n.d) “Definition of metadata”. Available at:  (Accessed: May 2021)

[iv] TechTarget (n.d) “Metadata”. Available at:,particular%20instances%20of%20data%20easier (Accessed: May 2021)

[v] United Nation (2019) “Introduction to data interoperability across the data value chain”. Available at:

[vi] Chen,Rong-Ming (4th September 2020) Interview by Y. F. Lin. “Interview with the Deputy Commissioner, Department of Transportation, Taipei City Government.”

[vii] Hue-Min, Chen (25th August 2020) Interview by Y. F. Lin.) “Interview with the Chief Secretary of Department of Information Technology, Taipei City.”