Across the world, citizens are continuously demanding for 2 things. The implementation of good governance and transparency systems to ensure sustainable development. Data is primarily recognized as the ‘heart ‘of digital government initiatives across the globe. In most of the e-government initiatives, secure storage, organization, and maintenance of data across the government is challenging and complex.
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As per the IDC & Seagate Data Age 2025 report, its estimated the global data sphere will grow from 33 zettabytes in 2018 to 175 zettabytes in 2025. Furthermore, IoT devices alone are expected to create over 90 zettabytes in 2025. As the world is rapidly moving forward with data-centric e-government initiatives, Sri Lanka is no exception. We have to get ready to manage big data sets with evolving technological trends such as 5G networks, highly data-centric applications with AI, machine learning, augmented & virtual reality, robotic process automation, blockchain, edge computing in order to move forward in par with world trends.
With the introduction of the Intelligent Data Governance Service Architecture, there are 2 key objectives. The first is to support & emphasize the importance of understanding Sri Lanka’s Data Ecosystem. The second is to implement a National Data Strategy for Sri Lanka to build a sustainable data economy to upstream the economic and social benefits of all Sri Lankans. In this article, the author endeavours to briefly discuss the primary factors and components that could be used to implement an intelligent data governance service architecture for sustainable economic development in Sri Lanka.
Why Data Governance
The ICTA’s 2024 vision for ‘A digitally transformed Sri Lanka,’ offers a blueprint for the way forward. The ICTA’s vision proposes technology clusters will generate a huge amount of zettabytes of data. This data could be derived from government sectors institutes and other private sectors during the next few years. The data thus obtained may be generated from several sources.
These sources can range from online portals, IoT based systems, government eservices, interacting with online chatbots, personal data, business data, various sensor-based Apps with the many smart Sri Lanka initiatives underway. These encompass many sphere including health, education, law & order, tourism, transportation, ports & shipping, logistics, finance from government and private sectors organizations. Particularly, government data collected from key public enterprises will play a pivotal role in improving e-governance, empowering citizens, creating economic opportunities, and solving societal issues.
But this can only be possible if the data ecosystem, demand for data, and a strategy for managing data are properly addressed by the relevant authorities. Globally, surveys have revealed the number of countries with Open Government Data (OGD) portals have increased from 46 countries in 2014 (24%) to 153 in 2020 (80%). There are enormous benefits with the release of Government data for the development of people-centric applications for the public.
“If the Government could execute a proper plan to collect, manage, store, use, share, the zettabytes of data that will be generated during the next few years with the smart Sri Lanka initiatives, they could do wonders and could be a good source of income generation avenue to boost the economy in Sri Lanka.”
Challenges in managing zettabytes of data
Are we really ready to accept, properly manage, and capitalize the huge data sets that will be generated in future? What is the strategy and proposed data governance architecture to deal with huge data sets? In Sri Lanka, with the proposed digital transforming initiatives, such as, from smart cities, smart health, smart tourism, smart education, smart government, smart agriculture etc., an enormous amount of digital datasets will be generated from all sorts of government and private sector entities.
The following are some of the challenges government may face in managing all this data:
- Who owns the data?
- Government strategy assigning data stewards and their roles?
- What is the strategy for sharing data among public and private partners?
- Who can access the data?
- How would we eliminate the data redundancies among many government and private institutes?
- Where and how would we store data?
- How to assure privacy and confidentiality of data?
- What is the mechanism or policies defined that government organizations, industries, researchers, citizens or any others could extract data ( adhering to data protection & confidentially rules) for various business operations, analytics etc and at a justifiable cost?
Understanding data governance
Data governance aligns people, processes and technology to manage and protect data assets. The sharing, privacy, availability, integrity, data quality, and accountability of data could be assured by implementing data governance. It would further enable the government to effectively capitalize on the data, which could be collected from various sources as mentioned above for economic development of the country. Data governance assigns data owners and data stewards to supervise and manage the manipulation of huge data sets.
Intelligent Data Governance Service Architecture (IDGSA)
The intelligence data governance service architecture offers a fully integrated intelligent data platform. It allows governments to manage & capitalize on robust data governance capabilities. All the while, ensure high data quality, privacy, data cataloging, intelligent scaling of data, leveraging the power of AI and machine learning for management of data stewardship capabilities, scalability and agility.
In order to efficiently handle the challenge of managing zettabytes of data, Sri Lanka needs a more intelligent robust model. One with long-term planning to be implemented without any delays. The proposed IDGSA model, which is a layered architecture, described below will outline how to manage & capitalize on data assets, and its impact on the economic development of Sri Lanka.
Layer 1: Data Source Layer
This layer extracts data from various sources, it may be belonging to various Government departments, public data and private organizations or any other sources. Data sources may be extracted from IoT devices, sensors, databases, chatbots, AI applications, GIS/GPS data, SMS data, satellite data, social media, data from wearable’s, CCTV, QR-codes etc. All of this data will be in different formats.
Layer 2: AI based Data Harmonization Layer
This layer defines the policies, standards, strategies, frameworks, and AI based automated processes defining how these zettabytes of data is stored in an effective manner.Data coming from various sources in different formats from several Government, private institutes and public need to be understood. Then rules must be enforced with automated processes on how this data can be used and shared among parties for a number of reasons. These can range from business purposes, developing citizen-centric e-services, policy making, and in general improve the living standards of all citizens.
Hence, in this layer, it is required to clearly define the roles, polices and AI based processes to manage data stewardships and ownership of data. These should encompass the means of collecting and sharing of data among various sectors in Sri Lanka. Additionally, defining the means of eliminating redundancies, processes for managing data security, data retention, classification of data, accountability, authentication, privacy of data, data normalization.
All of which, require a standardized set of rules, policies, and the use of AI & machine learning for automating processes utilize to eliminate data inefficiencies to manage dynamic relationship of data among various data clusters, data synchronization, collaboration data links between various sectors of government & private institutes.
The adoption of AI and machine learning embedded automated processes in this layer will leverage the power of intelligent systems to efficiently manage the data stewards’ effort and time defining data integrity, interoperability and sharing of data among many data clusters. Further, Layer 2, it assures that data structures are properly aligned with the Government’s national data strategy.
Layer 3: AI based Data Service Layer
With the previous layer, data is now stored in a proper manner with the support of AI and machine learning capabilities. In Layer 03, it is required to investigate how these valuable data assets could be processed and shared for well being of humans and society in general. Hence, Layer 3, that is, AI based Data Service Layer provides the much-needed intelligence tools. Offering the means to process and manipulate big data sets for public institutes, private parties, general public, researchers and others for use of any busines purposes.
In Layer 3, the means are offered for private software development companies, government entities, entrepreneurs, researchers, and others to develop and deploy state of the art intelligent tools and other automated tools. Enabling us to process big data sets to produce on-demand requests of various users, where the potential users may be government or private parties.
The required policy framework for deploying AI tools for processing data, data security, confidentiality, accessibility and availability of data has to be clearly defined in the government’s national data strategy. A strategy for pricing the use of AI & other automated tools deployed for intelligent processing of big data by various authorized parties in Layer-3 also can be setup to encourage the software development community in the country.
Layer 4: User App Layer
This Layer is denoted as the ‘Plug & Play’ Layer in the proposed IDGS architecture. Users can use their mobile, web and other interfaces to access the data from a diverse range of sectors agriculture, health, ports & shipping, education, finance etc. The data from both the government and private sector can be linked through this layer (L4). Afterwards, services can be requested of the various tools in L3 for obtaining required information from the proposed IDGS architecture. Alternatively, they can be used to extract raw data from the data stores.
In this context, governments can decide a subscription-based pricing model for accessing and processing various types of data in line with the national data strategy. This would ensure confidentiality, privacy, availability and authenticity of various valuable data available under government custody. Towards this, the relevant authorities must setup and manage the data storage and communication channels required for implementing the IDGS architecture.
Harnessing the power of big data for a better future
The implementation of IDGS architecture helps to promote improved data management strategies across the country. It also encourages the deployment and adoption of AI based set of tools, processes, policies, standards in managing data across almost all the sectors in a country.
For example, farmers starting on a new project can request a multidimensional data related to crops, demands, IoT based sensor data on similar projects, etc. They can also request the services of AI tools for analyzing the future demand, analytics, prediction, trends, risks, financial modeling etc. All of these would be accessible by paying a reasonable service fee for the use of data and tools proposed in the IDGS architecture.
Governments can also seriously make some effort to strategies on how to motorize on the big data assets available with the introduction of proposed IDGS architecture. In doing so, benefiting all relevant parties. Further, the proposed IDGS architecture encourages all citizens to actively participate, contribute in building and use of the valuable data asset centered around in many sectors. In doing so, deepening the citizens engagement and encouraging active participation with the government for improved services for all citizens and or the betterment and prosperity of our country.
