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Towards a Data Economy: An enabling framework WHITE PAPER AUGUST 2021
Cover: Gettyimages/monsitj
Inside: Gettyimages/shulz; Gettyimages/Amiak; Gettyimages/koto_feja; Gettyimages/blackred;
Gettyimages/Urupong; Gettyimages/Cemile Bingol; Gettyimages/DKosig
Contents
3 A Note from the Data for Common Purpose Initiative
4 Foreword
5 Preface
6 Executive summary
8 1 The Data Economy: An imperative
9 1.1 Data economy
11 1.2 Barriers to realizing a data economy
11 1.3 Data exchanges to enable a data economy
13 1.4 Industry shifts powered by a data economy
14 2 Functional Architecture of a Data Exchange
15 2.1 Principles for data exchange
15 2.2 Capabilities and functionalities of DEx ecosystem layers
16 2.3 Reference model of a DEx
17 2.4 Distinctive characteristics of a DEx
19 3 Governance of a Data Exchange
20 3.1 Data governance
22 3.2 DEx stakeholders
23 3.3 3P approach to a governance framework for a data-exchange ecosystem
25 4 Incentivizing Data Sharing
26 4.1 Determining the value of data
27 4.2 Incentivizing the sharing of data
30 5 Enablers for a Data-Exchange Ecosystem
31 5.1 Availability of data
31 5.2 Usability of data
33 5.3 Building trust
34 5.4 Multistakeholder approach
35 6 Looking Ahead
37 Contributors
39 Endnotes
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Towards a Data Economy: An enabling framework 2
August 2021 Towards a Data Economy:
An enabling framework
A Note from the Data for
Common Purpose Initiative
Nadia Hewett
Satyanarayana Jeedigunta
Project Lead, Data for
Chief Adviser, Centre for the
Common Purpose Initiative,
Fourth Industrial Revolution
Data Policy and Blockchain,
India
World Economic Forum LLC
Data impacts everyone, regardless of industry, risks to all. Much needs to be considered in any
geography or type of entity. Accelerating the discussion on data exchanges and marketplaces
responsible exchange and use of data can including cultural beliefs, philosophies and industry
solve critical challenges and fuel innovation for nuance. For this reason, the focus in DCPI remains
society. Whether the purpose is to provide better on global approaches, to realize the potential of
outcomes in agriculture, health, mobility or other these interoperable systems, while respecting
sectors, organizations and governments can individualized and localized notions. This global
sponsor changes to enable data economies and initiative also serves as a space for further
leverage data. discussion on efforts to source greater trust and
transparency for economic benefit. The Centre
This publication, led by the Centre for the Fourth for the Fourth Industrial Revolution India, among
Industrial Revolution India, is part of the World others in the Network, is a major contributor to
Economic Forum Data for Common Purpose this initiative.
Initiative (DCPI). A global initiative, DCPI explores
data exchanges and marketplaces as means to An introduction to the potential of data exchanges,
exchange data assets for the common good and to Data-driven Economies: Foundations for Our
promote the transition to a data-driven economy. Common Future, was published in April 2021.
A global multistakeholder community of more This idea has gone from being a concept to active
than 50 global partners in 20 countries, inlcuding development, though it is in its early adolescence.
seven countries, DCPI focuses on exploring data The Centre for the Fourth Industrial Revolution
governance models that allow data from personal, India is sharing its vision in this white paper and a
commercial and/or government sources to be starting point for a potential data exchange. These
combined, while still respecting rights. white papers and frameworks are the first of many
deliverables of this multi-year initiative to explore
Presented here is a critical enabling framework to policy, technical and commercial enablers for a
allow stakeholders across the data ecosystem to flexible data governance framework for a data
take data exchanges from concept to reality. It lays exchange. Collectively and individually, they offer
the groundwork in India and elsewhere for those insights into and thorough examinations of, specific
poised to explore, develop and realize the benefits considerations for decision-makers.
of a data exchange to accelerate a transition to a
data-driven economy. In developing governance for data exchanges,
collaboration as well as a systematic and inclusive
Exploration of the topics in this paper resulted from approach are critical. With thanks to the Centre for
collaboration with the DCPI community and the the Fourth Industrial Revolution India for sharing
wider Centre for the Fourth Industrial Revolution their insights, now published for the first time, we
Global Network (C4IR Network). This is to ensure hope that those interested in building a robust data
a broad and global view providing the greatest ecosystem find the framework useful and look
opportunity to ensure the rights of stakeholders forward to incorporating feedback and continuing
and the equitable allocation of benefits and the dialogue on this important topic.
Towards a Data Economy: An enabling framework 3
Foreword
Amitabh Kant
Anna Roy
Chief Executive Officer,
Adviser, NITI Aayog
NITI Aayog
Rapid digitalization has not only helped The Data Empowerment and Protection
India achieve inclusive growth with improved Architecture (DEPA) released by NITI Aayog in
governance but also poised it globally as a data- collaboration with iSPIRT is truly futuristic, providing
rich country. As per a McKinsey report1, Digital data empowerment to the common citizen in the
India: Technology to transform a connected nation, most comprehensive and transparent manner. A
increased digitalization in sectors like agriculture, similar approach for developing data platforms
education, energy, financial services, healthcare, through unique public-private partnership that
logistics, retail, as well as government services moves data out of siloes would help in data-driven
and labour markets, could each create $10 billion decision-making for organizations and data-driven
to $150 billion of incremental economic value policy-making for the government.
by 2025. This impact would be a direct result of
increased digital applications that would help raise NITI Aayog has collaborated with the World
output, save costs and time, reduce fraud and Economic Forum to prepare this paper on data
improve the matching of demand and supply. exchange (DEx), technical and commercial enablers
for a flexible data governance framework. A data
As India moves from being data-rich to data- exchange allows data to be leveraged for broader
intelligent, it will use machine learning and sets of social outcomes and can play a pivotal role in
artificial intelligence to find solutions for a vast unlocking the potential of a data economy.
number of the challenges faced by our country.
Access to high-quality, reliable data along with This paper is a critical step towards a data-driven
appropriate mark-ups would be a primary driver economy and invites a dialogue on exploring
for developing artificial intelligence. Appropriate government-led data exchanges for citizen services.
handling of data, ensuring privacy and security
are of equal importance. The seminal work done For a data exchange to be effective, sector-specific
by the Justice Srikrishna Committee on data models and use cases need to be designed and
protection law lays the groundwork for a robust developed. NITI Aayog and the World Economic
and responsible data-usage framework. The seven Forum endeavour to release a second part of this
core principles of data protection and privacy – paper with a focus on the approach for developing
informed consent, technology agnosticism, data Logistics Data Exchange (LDEx), a framework for
controller accountability, data minimization, holistic data exchange of public- and private-sector data in
application, deterrent penalties and structured the logistics sector.
enforcement – will provide a strong privacy
protection regime in the country once enacted. We acknowledge the World Economic Forum team
and NITI Aayog collaborators for their initiative and
The National Strategy for Artificial Intelligence effort in preparing this white paper.
released by NITI Aayog in 2018 proposes the
development of a data marketplace to enable
easy access to quality data, provide a more level
playing field, equitable access to new data sources
and frameworks to incentivize data sharing in a
responsible manner.
Towards a Data Economy: An enabling framework 4
Preface
The intersection of technology and data
presents a huge opportunity to address various
social, environmental and economic issues
Sheila Waren
Deputy Head, Centre for the
Jeremy Jurgens Fourth Industrial Revolution;
Managing Director, World Head of Data, Blockchain and
Economic Forum Digital Assets; Member of the
Executive Committee, World
Economic Forum LLC
The rapid advancement of technologies is Any such framework will have to establish an
resulting in the collection, processing and analysis environment of trust in the governance of data
of huge volumes of data. This data can be ecosystems and embed security and privacy in
harnessed for the benefit of the society. However, its design. For a data exchange to be effective,
access, availability and enabling discovery of it would have to assure the quality of datasets
data remain key challenges. Data remains siloed, provided, conform to open, interoperable
fragmented across the public and private sectors, standards and support the data needs of
inhibiting the transition to a data-driven economy emerging technologies. While many issues
where the rights of all stakeholders are respected surrounding data and data sharing remain open,
in a trusted environment. this paper presents various approaches that
could be valuable in addressing such concerns.
The intersection of technology and data presents Given the nascent stage of the concept of data
a huge opportunity to address various social, economy, this paper recommends following the
environmental and economic issues. Efforts are principle – “Think big, Start small, Scale fast.”.
ongoing to leverage use of data for the well- We hope it generates thought and action in our
being of the society in various domains, such as journey towards a data economy.
agriculture, financial services, logistics, health and
mobility, among others
This white paper, a result of multistakeholder
consultation between the public and private
sectors in India and globally, sheds light on
data exchanges as a data-sharing mechanism
applicable to both the public and private sectors.
It harmonizes various perspectives – economic,
technical, on innovation and regulatory – to
accelerate the move to a data economy.
Towards a Data Economy: An enabling framework 5
Executive summary
Towards a Data Economy: An enabling framework 6
Data economy – the unrealized potential
In India, value from integrated data use is estimated mechanism for incentivizing data sharing. Data
at about $500 billion.2 To realize this potential exchange can play a pivotal role in the growth
and the benefits of data, certain building blocks of a data economy when facilitated for common
of a data economy need to be put in place in the purposes among various stakeholders and
form of functional technology systems, robust participants.
governance frameworks and a self-sustainable
Functional architecture of data exchange
This paper proposes a five-layer data-exchange set of technological and governance principles
ecosystem, comprising data, consent, data and facilitates exchange of data between data
provisioning, exchange and consumption layers. providers and consumers in a trusted, legally
The core layer - data exchange is based on a compliant environment.
Governance of data exchange
Building upon current governance frameworks, data rights management, prevention of anti-
a 3P-approach – Protect, Prevent, Promote – is competitive practices and misuse of data and
recommended to help define the governance that promotion of innovation and development of
can accelerate the evolution of a data economy standards and protocols. The 3P framework
in India. The core aims of such a framework are is adduced more as a necessity of the data
protection of personal data, privacy-by-design, ecosystem, than as an “imposition”.
Incentivizing data sharing
Data, being a unique asset, presents unique that may be deployed to encourage stakeholders
challenges in determining its value. This paper to exchange data for common purposes through a
explores various factors that impact the value of data-exchange ecosystem.
data and the various incentivization mechanisms
Enablers of data exchange
Due to the nascent stage of development of data Above all, the paper recommends adoption of
exchanges, five enablers are proposed, namely – a calibrated approach to establishing the data
availability of datasets in the ecosystem, usability exchanges that balances the needs of innovation
of the datasets, an environment of trust, effective and protection and follows the principle – “Think
governance and a multistakeholder approach big, Start small, Scale fast.”.
that will accelerate the growth of data exchanges
and help realize the untapped potential.
Towards a Data Economy: An enabling framework 7
1 The Data Economy:
An imperative
Towards a Data Economy: An enabling framework 8
India has an opportunity to create a trillion-dollar digital economy by 2025, benefiting all
sectors and people. For this, both data and technology will be key enablers. Steps we take
today will determine the trajectory of the data economy. This paper is a multi-stakeholder
effort that explores the concept of data exchanges to harness the potential of data.” .
Ajay Prakash Sawhney, Secretary, Ministry of Electronics and Information Technology, India
Data is a valuable resource. Just as traditional the evolution of a data economy, while rooted in
economies are based on the production and ethical and responsible frameworks:
consumption of goods and services, the data
economy will be based on generation and use, – A reference model that lays down the functional
re-use of data. Data has the power to solve capabilities of a DEx
some of the most pressing challenges facing
governments, societies, businesses and science. – Requirements of data governance that balance
The World Economic Forum’s Data-driven the need for innovation with regulation
Economies: Foundation for Our Common Future3,
developed in collaboration with a global community – Methods to incentivize data sharing to ensure it
and published in April 2021, presents multiple is a self-sustainable model
use cases that illustrate how accelerating the
responsible exchange and use of data can solve – Five enablers, imperative for DExs, to be
critical challenges and fuel innovation for society. enabled and promoted
Leveraging emerging technologies to derive value
from the relevant data in a responsible manner will This paper is intended for policy-makers, industry
form the bedrock of a data economy. leaders, start-ups and academic/research
institutions to kindle the idea of data exchanges
This white paper is a part of the World Economic that can make data easily available for common
Forum Data for Common Purposes Initiative purposes. The proposed frameworks presented
(DCPI), to which the Centre for the Fourth will help organizations and policy-makers steer
Industrial Revolution India is a major contributor. forward-looking, interoperable and innovative
It aims to facilitate understanding of how data approaches to allow use of data from personal,
exchanges (DExs) as a data-sharing mechanism commercial and/or government sources, while
can responsibly play a pivotal role in unlocking the respecting rights. It aims to accelerate the
potential of a data economy. responsible use of data, including recognizing
and apportioning rights, risks and rewards in an
The Centre for the Fourth Industrial Revolution equitable manner. While numerous examples
India, in collaboration with the Ministry of and illustrations cited in this paper are specific to
Agriculture, NITI Aayog, the Ministry of Electronics India, the various ideas, insights and suggestions
and Information Technology and the Government may be applied by other organizations and
of Telangana’s Centre for Responsible governments globally as well.
Deployment of Emerging Technologies, in August
2020, launched the Artificial Intelligence for Data sharing is subject to multiple views and
Agriculture Innovation initiative, examining how assumptions that stem from the relative infancy
emerging technology solutions can be scaled of the concept. Quite often the uncertainty arises
and adopted across agriculture systems.4 A core from the fact that even the terms “data exchange”
pillar of this initiative is the role of data exchanges/ and/or “data marketplace” mean different things
marketplaces in the agricultural sector. Through to different people. Much needs to be considered
a multistakeholder consultative process that in any discussion on “exchanging data”, “data
included government departments, academia, exchanges” and “data interoperability”, including
industry stakeholders, start-up communities and cultural beliefs, philosophies, industry-specific
experts in the domain of data and technology, needs and other nuances, which, it is important to
the concepts and frameworks explored in acknowledge, differ among people, organizations
this white paper on data economy have been and geographies. This paper acknowledges
shaped to enable and accelerate the growth of these nuances and the importance of respecting
a data economy in India. To this end, this paper, the individualized and localized notions of the
while still at early stages of the data economy concepts presented.
journey, delves into various themes relevant to
1.1 Data economy
A National Association of Software and Service of India to be in the order of $500 billion, which
Companies (NASSCOM) report5 assessed the constitutes about 10% of India’s aspirations to
value of integrated data use in the major sectors become a $5 trillion economy by 2025.
Towards a Data Economy: An enabling framework 9
FIGURE 1.1 Potential of a data economy by sector in India by 2025 (in $ billion)
Health
Public sector 30
Consumer goods
30 95 and Retail
Automotive
45
$500 billion 65 Agriculture
Transport and 55
logistics
55 65 Banking and
Energy
insurance
Source: NASSCOM, 55
Unlocking Value from Telecom, media
Data and AI: The India and IT
Opportunity, August 2020
Data economy assumes a special significance technologies like artificial intelligence (AI), machine
in the context of emerging technologies, also learning (ML), distributed ledger technologies (DLT)
referred to as Fourth Industrial Revolution (4IR) and precision medicine consume huge volumes of
technologies. This is because they produce and data to produce reliable and meaningful results.
consume big data – in terms of volume, velocity,
variety and veracity. IoT devices, sensors, drones Figure 1.2 illustrates how a data economy can be
and biotechnologies generate huge volumes envisaged as comprising several digital ecosystems,
of data at an unprecedented velocity, while which in turn consist of many data ecosystems.
FIGURE 1.2 Data economy, digital ecosystems and data ecosystems
- Governance models
Data economy - Regulatory frameworks
- Stakeholders
- Applications
Digital ecosystems - Infrastructure
- Services
- Data exchanges
Data ecosystems - Datasets
- Standards and protocols
Source: World Economic
Forum
Digital ecosystems - In India, digital ecosystems A National Digital Health Mission (NDHM) has been
are emerging based on the National Open Digital formulated by the Ministry of Health and Family
Ecosystems (NODEs) 6 and India Enterprise Welfare with the aim to create a national digital
Architecture (IndEA)7, both initiatives promoted health ecosystem8. Similar efforts are in the offing in
by the Ministry of Electronics and Information areas like agriculture (IDEA – India Digital Ecosystem
Technology, Government of India (GoI). of Agriculture9), finance (UPI - Unified Payments
Towards a Data Economy: An enabling framework 10Interface), education (NDEAR - National Digital the standards for the creation and interoperability
Education Architecture10) and smart cities (Smart of datasets, applications, services and payment
Cities Mission11). The evolution of digital ecosystems mechanisms, besides the protocols for interacting
is one of the key requisites for the systematic and with other digital ecosystems. Such data
organic growth of the data economy. ecosystems, which span across public and private
sectors and encompass end-to-end view of data
Data ecosystems - Data ecosystems are value chains, are expected to play a pivotal role in
sub-elements of more comprehensive digital the speedy evolution of a data economy in India.
ecosystems, comprising not only data, but also
1.2 Barriers to realizing a data economy
Volume, velocity, variety and veracity are the 3. Lack of interoperability of datasets –
attributes of data in the new age. However, the Where data from different sources is required
potential of a data economy remains locked due to to be shared/analysed/integrated, lack of
several existing challenges, not limited to: uniform standards and protocols is a barrier
in making sense out of data. For example, in
1. Unavailability of data – The potential of a healthcare, the fact that different health service
data economy can be realized only if the data providers may be recording health records
is available. Data is a ubiquitous resource. Its of a patient in different formats, makes data
availability and accessibility remain a challenge. portability arduous.
Aside from the government, much of the data
being generated today remains with the private 4. Regulatory uncertainty with respect to data
sector, siloed and unavailable for use for protection and privacy – Laws pertaining to
common purposes. data privacy are evolving. Issues relating to data
ownership and ease of compliance with data
2. Low quality of available data – Even protection laws hinders effective data sharing.
where datasets may be available, if they are
incomplete, mislabelled or in an unstructured As such, there is a need for data-sharing
format (such as portable document format mechanisms that can unlock the potential of data
(PDF)/paper records, etc.), significant effort for common purposes, bringing public and private
is required to clean, scrub or digitize data to stakeholders together to share their data, in a
derive potential or intended value. trusted environment in which rights are respected.
1.3 Data exchanges to enable a data economy
A data exchange (DEx) is one such mechanism of discovery and negotiation in bilateral deals
where seamless exchange of data for value may be too high and inefficient.
can operate. Within an exchange, businesses,
governments and citizens/residents will have the – Unlock the combinatorial power of data:
opportunity to access data for specified purposes. Timely and effortless access to the right datasets
While doing so, however, it is imperative to ensure would create the ability to provide value-added,
that the rights of all stakeholders and participants integrated and end-to-end services to the
are recognized and protected. Data should be beneficiaries, using the combinatorial power of
exchanged in a trusted, secure and efficient different datasets obtained from multiple sources.
manner and should not be misused.
– Data availability: Creating demand for good-
A DEx offers the following benefits in unlocking quality datasets from trusted sources will lead
data for common purposes: to an increase in equivalent supply from data
providers, thus creating a virtuous cycle of data
– Data discoverability: A DEx platform facilitates availability and use.
discoverability of data. On a single platform,
mechanisms to access datasets may be made – Data discipline: The rigorous quality
available by multiple data providers to be requirements imposed by the market dynamics
shared with multiple data users to identify and will inculcate data discipline among various
operationalize mutually beneficial data-sharing stakeholders in their effort to participate actively
deals. Without this kind of a platform, the cost and derive benefits in a DEx ecosystem.
Towards a Data Economy: An enabling framework 11– Transparency: Enhanced transparency would – Accelerates research: Research would be
be established in public and private sector accelerated in areas of public interest like
through analysis of data and deriving insights health, education, agriculture and environment.
into the functioning and performance of
various entities.
BOX 1 Shaping the future of agriculture and food: An agriculture data exchange
The case for an agriculture data exchange is based on its While bilateral commercial deals on data sharing already occur,
potential to create social and economic value for the various to obtain the true benefit of data in this ecosystem what is
stakeholders of an ecosystem including farmers, farmer required is the ability of multiple data holders to interact with
cooperatives, government, start-up ecosystems, agricultural multiple data users to identify and operationalize mutually
input and output industries, logistics, the banking and insurance profitable data-sharing deals. This requires a platform. Without
sector and consumers/society. Such value can materialize in one, the cost of discovery and negotiation in bilateral deals
multiple forms: economic, social and environmental. would be too high to allow the market to develop efficiently.
According to research conducted by NASSCOM, an Indian A recent project report13 released by the World Economic
non-profit organization, there is a $65 billion opportunity in Forum identified 30 use cases leveraging emerging
India alone to be realized through unlocking 15 critical datasets technologies through an extensive engagement with over 70
in agriculture.12 The critical datasets identified were: soil health, agri-tech organizations. These use cases can be delivered by
satellite imagery, real-time data on agricultural markets, crop start-ups and industry stakeholders using an agri-data stack as
yields, production and consumption data, weather data, a key enabler. The Ministry of Agriculture and Farmer Welfare,
irrigation maps, storage network details, warehouse details, Government of India, has also released a proposal IDEA (India
commodity profile data, digital land records registry, defect and Digital Ecosystem of Agriculture)14 for public consultation which
pest images, network import-export volume details, historical will unlock this huge opportunity by enabling an agri-data stack
purchase prices for crops. These datasets were analysed on for innovation.
parameters of availability, quality and data usability across
multiple technology innovation-led use cases.
Data providers Agriculture data exchange Data consumers
- Agri-tech startups
- Cloud service
Begin with 15 critical datasets that providers
can unlock $65 billion* in value in - Agri-input
agriculture sector in India companies
- Agri-processing
and market
ecosystem
- Open data - Banking
APIs APIs
- Commercial data and insurance
- Technology
industries
- Soil health - Production and
- System integrators
- Satellite imagery consumption
and data
- Real-time - Historic
transformation
mandi data purchase prices
- Research
- Crop yields - Weather data
institutions
Source: World Economic Forum
*NASSCOM, Unlocking Value from Data and AI: The India Opportunity, August 2020
For example, access to institutional credit for farmers remains technological, regulatory and commercial environment in an
a challenge. One of the reasons is unavailability of information integrated manner for making available the requisite data.
which can help a non-banking financial company (NBFC) to
manage its risk in providing appropriate financing. However, Availability of and accessibility to critical datasets can also benefit
NBFCs can procure datasets relating to soil health, historical in the following ways:
crop yield in a specific geographic area, historical and forecasted
1. In the preparation stage, accurate predictions about the
weather data, high-resolution satellite images and real-time data
weather and future commodity prices could allow better
of energy consumption and agriculture inputs (seeds, fertilizer,
coordination and planning among farmers.
pesticides) and combine with output measurement mechanisms
like electronic warehousing receipts (eWHR) to determine a 2. In the sowing and production stage, information on soil
risk matrix and provide credit on custom terms and conditions quality, weather, and other factors could enable the farmer to
through fintech companies/start-ups. Affordable and easy optimally apply various inputs into the production process.
availability of multiple datasets – both historic and near-real-time 3. Accurate information about current prices available for their
– is critical to determining risk management for NBFCs. Herein produce in various agriculture markets, can allow the farmer
lies the value of a data exchange, which creates the conducive to realize the best possible returns for their yield.1.4 Industry shifts powered by a data economy
Data disrupts the industry structure, enables as a care provider; competitors could become
new opportunities for existing and new players collaborators to solve a bigger problem).
and allows companies to transcend industry
boundaries. While there are innumerable – New industries: Digital products, data-driven
possibilities, few patterns that may be visible products and services (for example, patient
pertain to: health management using digital watches)
and growing data ecosystems will likely
– Existing industries: There may be opportunities attract new entrants that provide customized
for existing products/services to shift to smart services for collecting, owning, processing
products/solutions. Data may also be used and/or distributing data. This would enable
within the same industry to extend its position propagation of data across industries making
or transcend industry borders (for example, a it easier for existing and new players to disrupt
medical devices company may position itself their industries and innovate.
FIGURE 1.3 Cross-industry value proposition for a data economy
Data economy – benefits to industry
Existing industries Retail Manufacturing Healthcare Financial services
– Personal investment
– Personalized diagnosis
– Connected products / democratization
and health planning
– Instant product and services – Personalized wealth
Smarter products – Blockchain-based
package customization – Smart components and management
electronic health record
spares – Social banking and
EHR storage and access
investment
– Product traceability and
tracking
Extending positioning – Boundaryless retail – Micro health hub – Data powered micro and
– Connected contract
within industry network management network startup accelerator hub
factories and quick
service stations
– Connected store
– Digital manufacturing – Connected health
Transcend industry powered by 5G data – Connected medicare
from design to delivery and wealth estate
borders – hyper home , health and and insurance network
– Drop shipping management
media hub
New industries FoodTech/ AgriTech FinTech HealthTech LogisticsTech
– Personalized health
– Behaviour-drive
– Digital diet and meal assistant
insurance
planning – Digital nurse / – Digital mobility pass
Digital products – Micro subscription-
– Digital pet care nutritionist – Digital truck
based loan
– Digital pulse /diary farm – Digital disease &
– Digital growth bank
medicine simulator
– Digital BNPL (personal
– Preventive crop care and
lending on digital and
New data-driven cultivation – Personalized drug – Connected logistic
purchase behavior)
products and services – Produce F2M (farm to formulation network
– Digital currency products
market) network
and exchange
– Micro risk and
– Micro agri net to drive investment district (e.g.,
Transcend industry
local community market people who transact – Health plan & benefits – Logistics index exchange
borders
and finance with credit cards likely to
default on home loans)
Governance controls Privacy and regulation | data governance framework | application layer governance and data level governance
Role in the economy Operate the economy | participate in the economy | monetize data in the economy
Towards a Data Economy: An enabling framework 132 Functional
Architecture of a
Data Exchange
Towards a Data Economy: An enabling framework 142.1 Principles for data exchange
For a forward-looking data economy and data commercially viable DExs are a key requisite.
ecosystems to flourish, functionally efficient, Figure 2.1 illustrates the principles which should
technologically robust, legally compliant and be considered in the design of a DEx.
FIGURE 2.1 Technology and governance principles for DEx design
- Orthogonality of foundational - Trust among the stakeholders,
capabilities and core components, systems and transactions in a data
meaning they can evolve exchange
Governance Principles
independently
Technology Principles
- Equal and non-discriminatory
- Extensibility of technologies used, access to a data exchange to
enabling evolution without sacrificing ensure democratization of access
interoperability to data
- Open standards and open - Equitable distribution of risks and
application programming interface rewards among data exchange
(API)-based ecosystem as the stakeholders
basis of an exchange to enable ease
of data exchange - Transparency in data exchange
operations
- Interoperability to allow frictionless
flow of data - Privacy- and security-by-design
to ensure a protected and secure
- Federated architecture to ensure data exchange
autonomy and decentralized
operation of a DEx - Accountability and governance
mechanisms to provide appropriate
- Data agnosticism to maintain the redress to stakeholders
neutrality of a data exchange
Source: World Economic
Forum
2.2 Capabilities and functionalities of DEx ecosystem
layers
A DEx ecosystem is conceptualized to consist techno-legal solutions to validate the same
of five layers: Data, Consent, Data Provisioning,
Exchange and Consumption. The capabilities and – Provisioning layer enriches the
functionalities particular to each layer are listed data by various methods such as
in Figure 2.2. Each layer is envisaged such that it aggregation, annotation, metadata creation,
can evolve independently, as per the technology tagging, cataloguing and anonymization,
principles in Figure 2.1. where necessary
In Figure 2.2: – Exchange layer is presented in detail in
– Data layer refers to data held by data owners/ Section 2.3
providers
– Consumption layer refers to the point where
– Consent layer enables consent management, data is used by data consumers and economic
adherence to purpose of sharing as specified value from data is realized for common
by the data provider/owner and appropriate purpose.
Towards a Data Economy: An enabling framework 15FIGURE 2.2 A DEx ecosystem
Privacy, Security, Interoperability,
Regulation Functionalities of the layers
- End user management (research, innovation)
Consumption
- Payments, taxation interface
- Data rights management
5-layer model of data exchange ecosystem
- Registration of actors in data ecosystem
Exchange
- Data discovery, price discovery
- API & e-payment gateway
- Auditability, grievance management
- Extract, transform, load (ETL), aggregation,
Provisioning annotation, anonymization
- Metadata creation, tagging, cataloguing
- Data Commerce
- Purpose of sharing, consent management
Consent
- Visibility into data consumption
- Transaction history, compliance
- Creation, storage, maintenance
Data
- Quality, availability, security, privacy
- Identification, immutability
Source: World Economic
Forum
2.3 Reference model of a DEx
Central to a DEx ecosystem is the “exchange” 2. Dataset discovery and quality management:
layer. Figure 2.3 provides a DEx reference A DEx does not store data but facilitates
model. The layers are conceptualized using the peer to peer exchange of data between
technology and governance principles highlighted data providers and data consumers. Various
in this Section. The six functionalities represent datasets should be organized in a logical
capabilities in the areas of technology, regulation structure or taxonomy to help data consumers
and management. search the exchange easily and find what they
are looking for. Sample datasets may also
Major functionalities of a DEx provide live testing capabilities in a controlled
environment. Solutions may be built on top of
1. Identity management: A DEx enables open source as well as proprietary software.
identification, authentication and authorization
of the providers and consumers of data 3. DEx gateway: A DEx gateway facilitates secure
intending to transact on the platform. Trust in a exchange of datasets between data providers
platform is linked to the rigour with which these and consumers. This layer provides opportunities
three functions (identification, authentication for service providers in the space of integration
and authorization) are performed by a DEx. platform as a service and API management.
Towards a Data Economy: An enabling framework 16FIGURE 2.3 A DEx reference model
Data providers DEx governance structure Data consumers
Data exchange
User management
Identity | Registration | Exit | Messaging
Dataset discovery and quality management
Metadata | Catalogues | Provenance | Sample datasets
- Open data DEx gateway - Digital service
API gateway | Tokenization | Fulfilment monitoring providers
- Commercial data
APIs APIs - Startups
Transaction management
Price discovery | Smart contracts | Metering - Data provisioners*
- Public sector Invoicing | Settlements
- Researchers
- Private sector Trust management - Civil society
- Non-profit sector Data rights management | Audit trail | Intellectual
property rights | Consent management
Ratings | Reviews
Infrastructure and support services
DEx cloud | Security | Privacy
Analytics | Complaints | Administration
Source: World Economic
Forum
4. Transaction management: The transaction- (DLT) could be a viable option. A ratings
management system should be simple, with and reviews mechanism helps attract more
*Data provisioners least number of steps, intuitive and frictionless. consumers to use the exchange and identify
enrich data and make it
The processes should be secure and fool-proof the most popular and trustworthy datasets.
marketable in compliance
with data regulations. to prevent fraudulent transactions.
6. Infrastructure and support services: Various
They act as a bridge
5. Trust management: Among other features, infrastructure and support services including,
between data providers
immutable audit trail and authentication of but not limited to, an effective grievance
and data consumers.
data origin will add to the trust in the platform. redressal system would enhance user
Deployment of distributed ledger technologies confidence and increase transparency.
2.4 Distinctive characteristics of a DEx
There are multiple frameworks, technologies are designed for use cases where the nature and
and tools for exchanging data, each driven format of data and the purpose and process for
by a different aim and focus. DEx is one such its sharing are deterministic. In respect of a DEx,
mechanism with a focus on unlocking data to on the other hand, 1. the architecture needs to be
create economic value in a rights-respecting and optimized for a wide range of use cases where
trusted environment. The distinctive characteristics the data is yet to be discovered, 2. the manner of
of a DEx are described below: its use is dependent on the nature of innovation,
and 3. the terms of data exchange need to be
1. DEx is more than data-sharing: A DEx platform agreed upon between multiple parties.
offers a wide range of services that precede
and succeed the actual data-sharing. While 2. Minimum viable product (MVP) of a DEx:
frameworks, technologies and tools used for It may be impractical to design and develop
data sharing can be leveraged by a DEx, several the entire range of features and services of a
services specific to a DEx may have to be DEx upfront. A DEx should evolve with time. It
provided for in a DEx platform itself. For instance, is therefore appropriate that the core features
while leading API gateways provide functionalities of the platform are built as an MVP. These
relating to user management, API management, features should be such as to enable exchange
authentication, authorization and metrics, they of data relating to a specific sector and for
may not sufficiently address issues relating purposes of innovation in identified segments
to data exploration and discovery or consent of the related value chains, in compliance with
management. Likewise, some of the frameworks applicable regulations.
Towards a Data Economy: An enabling framework 173. Interoperability of DEx with external this in mind, the technology architecture of a
platforms: A DEx is conceptualized as a DEx needs to be designed in a modular and
multi-layer system with the capabilities of interoperable manner, using open standards
each layer well-defined. The functionalities and open-source products and components.
of some of the layers have already been This will allow external platforms to plug into
built by commercial platforms in different a DEx platform with relatively less effort and
scenarios like e-commerce and open data carry the footprint of their existing users to a
initiatives. Such platforms can deliver part of DEx environment.
the functionality envisaged by a DEx. With
TA B L E 2 A sampling of data exchange technologies and/or platforms includes:
Data exchanges (non-exhaustive)
1. Dawex15 – a data exchange and data marketplace technology company
2. DATA for GOOD Foundation16 – enables consensual sharing of GDPR regulated data
3. Indian Urban Data Exchange17 – open-source software platform for data exchange in smart cities
4. Elastos18 – a platform that enables data ownership, decentralized data exchanges and data
monetization by offering an array of open-source developer services
5. Databroker19 – a blockchain-supported exchange for data
6. One Creation20 – a platform providing a decentralized digital rights exchange fabric (DDREF) with
tools to control, enforce and monetize data digital rights
Towards a Data Economy: An enabling framework 183 Governance of a
Data Exchange
Towards a Data Economy: An enabling framework 19Both the public and private sectors hold large security, protection of commercially sensitive/
amounts of data, which remain siloed and confidential/legally protected data, trust and
inaccessible to be used for common purposes. compliance requirements in cross-border data
Even where such datasets are made available flows. While these issues and risks are common
(open data, etc.), data governance models do to organizations and governments around the
not allow data from personal, commercial and/or globe, development of an appropriate governance
government sources to be combined. If effectively framework remains specific to each industry and
leveraged, both public- and private-sector data jurisdiction. A balanced approach that recognizes
have the potential to solve complex challenges, the trade-off between opportunity and challenges
while still respecting rights. needs to be adopted by the various stakeholders.
This section surveys the governance landscape
Data sharing comes with its own set of challenges, and identifies the requirements that can facilitate
however. These include issues relating to privacy, the evolution of data economy in India.
3.1 Data governance
Data governance frameworks, including but and regulations (current and proposed), bearing
not limited to policies, regulations, formal and upon the exchange of data in India are listed in
informal standards and rules, are rooted in and Table 3.1. Exchange of data in other jurisdictions
arise out of privacy concerns and the need will have their specific data regulations to consider
to protect personal information of individuals and comply with. The need and extent of
from unauthorized access or use. In India, data regulation of data exchanges remains debatable,
ecosystems are regulated by a set of regulations, with various views across the spectrum.
general and specific to data protection. The laws
TA B L E 3 . 1 The existing (and proposed) data governance frameworks in India
Regulation Description
Information The IT Act of India was enacted as an enabler of e-commerce. It provides legal recognition of
Technology (IT) Act electronic records, authentication of electronic records by public key infrastructure (PKI)-based digital
2000 and IT signatures, delivery of electronic services and notably, execution of contracts electronically. Electronic
(Reasonable contract can be considered a distant forerunner of smart contract, which is essential for the evolution
security practices of a data economy. The Rules notified in 2011 under the IT Act provide for protection of sensitive
and procedures and personal information.
sensitive personal
data or information)
Rules, 2011
National Data NDSAP is applicable to all non-sensitive shareable data available in digital/analog form but generated
Sharing and using public funds by various ministries/ departments/ agencies/organizations of the Government of
Accessibility Policy India. It called upon the government to proactively share open data and was followed by the launch of
(NDSAP), 2012 the open data government portal (data.gov.in)
Law on copyright In India, the Copyright Act 1957 provides copyright protection to “original literary works”21, among
and trade secrets other classes of works. “Literary works”22 include compilations of data and the Indian courts have
viewed “originality” as requiring a “minimum level of creativity”.23 As such, data in raw form may not be
copyrighted. However, if some level of skill and creativity has been exercised in compilation of a datasets/
database to make it usable, it may be protected under Indian law.
There is no statutory protection afforded to trade secrets in India. However, trade secrets are recognized
and protected by way of judicial rulings and contractual arrangements. Secret information has a
commercial value and steps taken to keep it secret usually fall within the ambit of a trade secret.
Contracts with confidentiality obligations can be entered into between parties to protect disclosure of
data (including trade secrets).
Towards a Data Economy: An enabling framework 20Regulation Description
The Competition Data is a substantial intangible asset used for value creation, comparable to copyright, patents,
Act, 2002 intellectual capital, or goodwill. This is leading to a situation where a few large platforms have become
the new gatekeepers to the internet. In this context, it is essential that a regulatory framework for
DExs should not only support innovation, but also provide effective safeguards from potential harm to
competition and consumer welfare.
The Competition Act 2002 provides some safeguards to mitigate risks associated with data-driven
economies. Amendments may be required, however, to strengthen the existing provisions to deal with
likely infringement of competition laws specifically in the context of data economy, to curb restrictive and
unfair practices such as abuse of dominant position, online vertical restraints, anti-competitive licensing
agreements, commercial arrangements, mergers and acquisitions.24
The Personal Data At the time of writing this paper, the PDP Bill is under consideration in the Indian Parliament. It seeks to
Protection Bill (PDP lay down a comprehensive framework for personal data protection. The Bill provides for 1. obligations
Bill), 2019 of data fiduciaries that determine the purpose and means of processing personal data; 2. rights of data
principals (natural persons to whom the personal data relates); 3. establishment of a Data Protection
Authority in India; and 4. penalties and compensation for contravention of certain provisions of the law.
The Bill balances the needs of data economy with the responsibility of data protection with respect to
personal data.
Report of Committee The report of the Expert Committee constituted by the Government of India has proposed a framework
of Experts on for use of non-personal data (NPD), which includes the salient features below:
Non-Personal
Data Governance 1. Recommends establishing a legal basis for asserting the rights of India and its citizens over
Framework 25 non-personal data
2. Outlines a framework for generating economic benefits from non-personal data for India and its
people
3. Provides an illustrative architecture of NPD exchange
4. Defines and identifies certain categories of data as High-Value Datasets (HVDs), to be used for public
good
5. Provides recommendations on data sharing in the context of public good purposes
Data Empowerment The National Institution for Transforming India (NITI) Aayog, the national body responsible for planning
and Protection national development designed the DEPA framework to catalyse activities in the data economy. DEPA
Architecture introduces the concept of a consent manager which would enable individuals to control their data and to
(DEPA)26 consent to share it with third party institutions.
In the financial sector, DEPA has been formalized through the Account Aggregator27 framework, for which
directions were notified by the Reserve Bank of India. Under this framework, a new class of non-banking
financial companies are being licensed to allow data owners to share their financial data, which may be
siloed in banks with third party applications.
DEPA is a powerful instrument that builds on the time-tested architecture/principles of Unified Payments
Interface (UPI) in India. It provides guidance in the design of some of the core components of a DEx.
Towards a Data Economy: An enabling framework 213.2 DEx stakeholders
There are several stakeholders in a DEx commercial models evolve. They are likely to be
ecosystem. Table 3.2 lists the roles of various explored and tested, set within parameters for
stakeholders. These might be further reimagined responsible, fair and ethical use of data.
and redefined as technology, regulation and
TA B L E 3 . 2 Table 3.2 – DEx stakeholders
Stakeholder Role
Government 1. Amend and/or enact legislation, regulations, policies to facilitate development of DExs
2. Promote use of data for common purposes to create value by the public and private sectors
3. Establish new regulatory authorities or extend authority of existing regulatory authorities for redress of grievances
and effective enforcement of laws relating to data ecosystems
Regulators 1. Protect interests of DEx participants and stakeholders
2. Promote development and adoption of technology standards, specifications and best practices in DExs
3. Establish infrastructure like regulatory sandboxes to accelerate and promote innovation
DEx platform 1. Connect data providers and consumers in a trusted environment in compliance with applicable regulations
2. Register, identify and authtenticate DEx users
3. Specify the rules of engagement for DEx users
4. Enable discovery of datasets
5. Establish secure systems that ensure security, privacy and consent management
Data provisioners28 1. Enhance value of raw data by adding value to it, providing a range of data-processing services to ensure that the
data is usable, interoperable and transformed into a format required by the data provider/consumer
2. Establish a trust mechanism between data providers and consumers with respect to data quality
3. Provide consent management and contract management services, if needed
Data providers 1. Data providers are public- or private-sector entities (government, business, non-profit organizations or individuals)
that create, provide, update, secure and maintain data (both personal and non-personal)
2. Exercise effective control over their data and provide consent in accordance with applicable regulations, which is
critical for building a trusted environment
3. Proactively assert their rights where needed, especially in areas relating to personal data protection and equitable
distribution of value, aiming for the long-term stability and sustainability of data ecosystems
Business enterprises 1. In addition to being data providers, businesses should adopt best practices in data governance to ensure
availability and management of real-time, high-quality secure datasets
2. Fund research in applied data science and application of emerging technologies within the enterprise and beyond
3. Leverage the network effects fairly and equitably using the combinatorial power of multiple datasets and diverse
technologies by working with other data ecosystem stakeholders
Innovators 1. Innovators include the start-up community and the small and medium-sized enterprises (SMEs) segment
exploring opportunities to solve real-life challenges using data and conventional/emerging technologies
2. Discover new ways of leveraging data for scalable solutions
3. Participate actively in the sandbox(es) created by various authorities to experiment with new ideas by accessing
data in a controlled environment
Researchers 1. Develop standards and protocols to enable DExs, particularly irreversible methods of anonymization, federated
databases, owner-centric data management, lightweight consent management frameworks, privacy-preserving
technologies and intellectual property rights (IPR) preserving technologies
2. Develop data-governance frameworks adapted to a DEx
3. Conduct applied research on innovative use of datasets
Civil society 1. Explore vulnerabilities in a DEx ecosystem, specifically in domains of data security and privacy
2. Observe the operations of a DEx and identify any restrictive practices
3. Advocate policy with the objective of enhancing protection of stakeholder interests equitably and inclusively
Towards a Data Economy: An enabling framework 22Building on the work undertaken by the Centre for explore the roles and responsibilities of DEx service
the Fourth Industrial Revolution India and presented providers. Deliverables aim to provide jurisdiction-
in this paper, the Data for Common Purpose and industry-agnostic tools, while ensuring
Initiative (DCPI) will facilitate further collaboration adaptability as per local context and requirement29.
between public- and private-sector partners to
3.3 3P approach to a governance framework for a
data-exchange ecosystem
Data has unique characteristics, the most existing (and proposed) governance frameworks
noteworthy being its volume, velocity, variety and in India (Table 3.1) and the various stakeholders
veracity, in addition to its non-rivalrous nature and (Table 3.2), any framework should aim to balance
above all the immense scope for innovation that enabling innovation with governance requirements
access to data provides. The combination of the to accelerate the evolution of data economy in India.
above characteristics makes it difficult to design a The following principles are proposed to guide the
governance framework, whether government-led formulation of such a framework in a 3P approach,
or self-regulatory. Taking into consideration the namely, Protect-Prevent-Promote (Figure 3.2)
FIGURE 3.1 3P framework
PROTECT PREVENT PROMOTE
- Personal data - Unauthorized use - Dynamic,
and misuse of data competitive, trusted
- Embed data rights
DEx ecosystem
management - Anti-competitive
practices - Development of
- Effective grievance
standards and
redress mechanism - Harm to
protocols
stakeholders
- Open innovation
Protect 3. Effective grievance redress mechanism
– The interests of all stakeholders of data
1. Personal and non-personal data should be protected through appropriate
– Personally Identifiable Information (PII) of grievance-redress mechanisms.
natural persons should be protected across
the data value chain by all stakeholders Prevent
involved in the ecosystem. The principle
of privacy-by-design should be observed 1. Unauthorized use and misuse of data
in the design and implementation of all – The purpose of data sharing may be
digital and data ecosystems, specifically identified and agreed upon to prevent
those dealing with personal data. These possible misuse of data. Broad categories
include but are not limited to notice, choice, of data processing purposes may be
consent, purpose limitation, collection defined through appropriate standards and
limitation, disclosure limitation, right of guidelines applicable in general for all DExs
the data owner to access and correction, or specifically to each domain or sector of
security, accountability and transparency. the economy. One such example is the set
of standards developed by the International
2. Embed data rights management Organization for Standardization (ISO),
– Differential authorization of data use may be 14265-1130, on “classification of purposes”
adopted to allow the data owners/providers of using health data. The framework should
to specify for which purpose(s) their data be designed so as not to discourage
can be used, for what duration and whether innovation and preferably in the form of
the data should be monetized. To realize self-regulation in respect of processing of
this requirement, a data-rights management non-personal data.
framework may be developed, akin to
digital rights management in the media and
entertainment sector.
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