AI national mission

1. Data Fellows |
National Program
on AI
February 2023
Induction Deck for Data Fellows

2. Agenda
A. Background
B. DMUs and Data Fellows
C. Data Fellows: Roles & Responsibilities
D. Reporting Structure
E. Deployment
F. Learning & Development

3. Background

4. Importance of Public Sector Data
Improved Governance - Unlocking data strengthens the evidence base for policy and program
design, monitoring and evaluation, enabling evidence-based decision-making and improving
governance
Enhanced Public Service Delivery – Analysis of public sector datasets optimizes welfare
delivery and increases administrative efficiency, enabling citizen-centric services and
targeted benefits to citizens
Catalyzing Research & Innovation– Improved availability of reliable, high-quality public-
sector data catalyses digital innovation for public good, creating new economic
opportunities
Greater Transparency & Accountability – Access to public sector datasets improves
transparency and accountability in government operations

5. Current Challenges in Government Data
Governance
Inconsistency in
Data Management
Processes
Non-compliance to
Meta-Data Standards –
Poor data
interoperability
Inconsistency in Data
Quality – Blank Files,
Missing Fields, Errors,
etc.
Infrequent
Updating of
Datasets & Latency
Lack of API Based
Data Sharing
Variations in File
Format of
Datasets
Limited
Sharing of
Datasets
Limited
curation of
datasets for AI

6. Major Government Initiatives around Data
SPDI Rules
2011
Notification of
NDSAP Policy
2012
2012
(First Version)
May 2022 Aug 2023
Launch of OGD
Portal
National Data
Governance Framework
Policy
DPDP Act
Founded on the
principle of
Accountability (via
the RTI Act) and
covers:
• Proactive Data
Sharing
• Data Classification
• Interoperability
• Data Licensing &
Pricing
Platform for uploading
datasets under Open
Access
Rules covering
privacy and
security of
sensitive data
(for enterprises)
Comprehensive
Data Protection
Act focusing on
data privacy &
security
(applicable to
all)
Draft policy
focusing on
improving data
quality, access,
and use and
providing
institutional
framework
(National Data
Management
Office) for Data
Governance
Dec 2022
National Program
on AI
Comprehensive
program to
catalyze AI
innovation.
National Data
Management
Office pillar to
focus on Data for
AI

7. National Data Management Office
The National Data Management Office is a critical part of the National Program on AI and National Data
Governance Policy to improve data management, quality, access, and use
Key Mandate
Standardize Government Data Management Practices
through rules/standards/guidelines
Guidelines for Identification, Classification, and Access to
Datasets
Meta-data, data quality standards, and Anonymization tools
and guidelines
India Datasets Program & Platform for Transforming Non-
Personal Data Ecosystem (Govt. & Private Entities)
Dedicated Government Data Management Capacity Building
& Augmentation
Structure of NDMO
NDMO PMU
Dedicated support to lead
governance, capacity and
platform synergies
Data Management
Units (DMU)
Headed by CDO
2 Analysts + 1 Scientist
Across 50 ministries/depts
Ministry 1 Ministry 2 Ministry n
Data
Scientist
Data
Analyst
. . .
India Data Officer
IndiaAI CEO

8. DMUs and Data Fellows

9. Data Management Units
Recognizing the need to augment dedicated data management capacity at a ministry/department level,
Data Management Units (DMUs) will be set up in every government ministry/department as data offices
Assist ministry/department in the management
of data over its lifecycle
Ensure adoption of metadata and data quality
standards
Assist ministry/department in undertaking
assessment of current state of data quality &
maturity
Create secure APIs for sharing data on Data
Platforms
Develop and ensure compliance against SOPs for
data collection, management, storage, and access
Streamline & Process Inter-Government Data
Sharing
Curate & Publish Datasets for AI Innovation
Enhance Data Analysis and Use within
Ministry/Department
Data Capacity Building & Awareness for government
officials
Advise on industry trends and best practices in
data access and sharing
Key Functions

10. Data Management Units
Structure
Basic DMU Structure
Chief Technology
Officer
Secretary
Data
Management
Cyber Security Applications
Chief Data
Officer
Data Scientist
Data Analyst 1
Data Analyst 2
Mature DMU Structure
While depending on requirements and resource availability, each DMU’s structure and size may vary, the minimum
structure for the DMU must include 1 CDO, 2 Data Analysts, 1 Data Scientist and 1 IT support person
Data Fellows

11. Data Fellows: Roles & Responsibilities

12. Key Functions of Data Fellows (1/5)
Functions Data Analyst Data Scientist
Streamlining
Data
Management
● Maintain and ensure quality and accuracy of datasets
● Ensure data collection on all parameters for monitoring
and policy making within the ministry/department
● Document all data points within the
ministry/department and maintain detailed records of
data management decisions
● Ensure no duplication of data collection efforts
● Ensure compliance against defined SOPs/Data
Management processes/Decision-making frameworks
● Enable cross-platform integration by defining metadata
standards and designing data flows for schemes within
the ministry/department
● Assist ministry/department in undertaking an
assessment of their current state of data quality
maturity
● Assist in enhancing data management practices over its
lifecycle (collection, processing, storage, access, and use)
● Streamline and standardize data collection practices and
data enterprise architecture
● Ensure 100% digitization of collected data
● Establish SOPs and protocols for data management
● Lead and mentor Data Analysts
● Design and implement data capturing and data quality
assurance mechanisms
● Institutionalize the creation and curation of datasets from
the available data

13. Key Functions of Data Fellows (2/5)
Functions Data Analyst Data Scientist
Enabling
Quality Data
Access
● Develop and maintain data inventory (inventory of all
data assets)
● Create secure APIs for streamlined data sharing
● Identify, curate, and contribute quality datasets to
data platforms and India Datasets Program
● Ensure processing of inter-government data sharing
requests and monitor related workflows
● Prepare a schedule of curated datasets to be
contributed and negative list of datasets to the India
Datasets Program on a by-annual basis
● Analyze the existing IT systems of department to
advise data scientist and CDO
● Ensure compliance against data anonymization
guidelines, data sharing decision making frameworks
● Frame data-access practices for the India Datasets
Platform and other data requests for the host
Ministry/Department
● Promote culture and practices pertaining to proactive
sharing of datasets
● Ensure culture of API based sharing of data
● Integrate siloed data systems across the
Ministry/Department
● Advise ministry/department on industry trends and
best practices in data access and sharing

14. Key Functions of Data Fellows (3/5)
Functions Data Analyst Data Scientist
Promoting
Data-Led
Governance
● Undertake and promote data analysis and creation of
data visualizations on collected data
● Provide hands-on training to government officials on
tools for data analysis and visualization
● Promote data analysis on collected data and drive a
culture of evidence-based policy making
● Build awareness around potential of data and its
use
● Enhance data management and analysis skills of
government officials
● Advise ministry/department on industry trends and
best practices in data management, analysis and
visualization
● Prepare monitoring frameworks and indicators to
ensure tracking of schemes, broader sectors, and
outcomes

15. Key Functions of Data Fellows (4/5)
Functions Data Analyst Data Scientist
Data Audits and
Quality
Assurance
● Ensure datasets are in line with the requirements as
specified by the NDMO
● Ensure adoption of metadata and data quality
standards as specified by the NDMO
● Ensure adoption of data storage, archival and deletion
SOPs in alignment with guidelines specified by the
NDMO
● Conduct spot data quality assessments, error checking,
and validation
● Perform statistical tests to determine the reliability and
soundness of insights generated
● Ensure compliance against data security and privacy
protocols as specified by MeitY, NDMO, or any other
government agency
● Ensure compliance against
Rules/Standards/Guidelines specified by the NDMO
● Ensure compliance with the timelines and processes
for the audits that are conducted by NDMO
● Ensure data integrity and quality by overseeing and
reviewing data cleaning and validations performed
by Data Analysts

16. Key Functions of Data Fellows (5/5)
Functions Data Analyst Data Scientist
Capacity
Building
● Provide insights and inputs on the DGQI action plan
developed by the host ministry/department
● Implement the defined training plan for officials on
data governance, analysis, access, and use
● Identify, on-board, and coordinate with training
partners
● Coordinate with vendors and execute trainings and
hands-on exposure on data analysis and management
tools, dashboarding tools
● Prepare a roadmap for the ministry/department
with specific milestones to enhance their data
preparedness
● Create an overall training strategy plan for the
ministry/department
● Develop and oversee M&E plans for all schemes
and projects

17. Reporting Structure

18. MeitY and IndiaAI: Key Structure
IndiaAI is an Independent Business Division under the Digital India Corporation (DIC) that will implement
the National Program on AI, including the National Data Management Office
ET Division
AS – Shri Akash Tripathi
GC – Smt. Kavita Bhatia
Divisions
Digital Governance
Division
Attached Offices
Statutory
Organisations
Section 8 Companies Autonomous Societies
Cyber Security
Cyber Laws
International Co-
operation
Data Governance
NIC
STQC
ICERT
UIDAI
NICSI
NIXI
DIC
BISAG-N
C-DAC
STPI
NIELIT
MeitY Key Structure*
* Key Structure – Does not include all divisions/attached offices/societies, etc.
NeGD IndiaAI MSH ISM
MyGov
IBD
NDMO

19. Reporting Structure
Illustrative DMU Structure
CEO IndiaAI
India Data Officer
Chief Technology
Officer
Secretary
Data
Management
Cyber Security Applications
Chief Data
Officer
Data Scientist
Data Analyst 1
Data Analyst 2
Data Fellows
Ministry
IndiaAI
The Data Scientists
will report to the
Ministry/Department
CDO as well as the
India Data
Officer/IndiaAI CEO

20. Deployment

21. Way Forward
Timelines / Approach Ministries for 1st Cohort
Hiring of Data Fellows
Orientation
Initial Training Week
Kick-Off Meeting with
Ministry/Department &
Deployment
Ministry of Rural Development
Ministry of Finance
Ministry of Health & Family
Welfare

22. Monitoring & Evaluation (1/2)
# Function KPI Description
Reporting
Frequency
1
Data Management, Audit, and
Assurance
No. of processes/SOPs defined and institutionalized for data management and access Bi-Annually
2 % of datasets compliant with metadata and data quality standards Quarterly
3 Data Completeness ratio Quarterly
4 Data Duplication rate Quarterly
5 Digitally collected/generated data as % of total data collected Quarterly
6 % of Data Tied to Legacy Systems Quarterly
7 Data validation coverage Quarterly
8 Data validation success rate Quarterly
9
No. of datasets tested for completeness, accuracy, and compliance with standards
issued by NDMO
Quarterly
10 No. of data systems and processes audited Quarterly
11 No. of statistical tests performed, insights and results thereof Quarterly
12 Change in DGQI rankings Quarterly

23. # Function KPI Description
Reporting
Frequency
12
Data Management, Audit, and
Assurance
No. of Inter-Government Data Sharing requests processed Quarterly
14 No. of datasets contributed to the India Datasets Platform Quarterly
15 No. of datasets contributed to the India Datasets Program Quarterly
16 No. of APIs written for real-time data sharing Quarterly
17 No. of downloads of datasets published by ministries/departments on IDP Quarterly
18 No. of downloads of datasets published by ministries/departments on OGD Quarterly
19 No. of data portals/dashboards/MIS not integrated with IDP Quarterly
20
Promoting Data-Led Governance
and Capacity Building
No. of Training Partners on-boarded Bi-Annually
21 No. of trainings conducted Quarterly
22 No. of data fellows, government officials that attended training Quarterly
23 No. of officers who successful completed training Quarterly
24 No. of M&E plans developed at a scheme/project level Quarterly
25 No. of internal dashboards/MIS/data monitoring tools live Quarterly
Monitoring & Evaluation (2/2)

24. Learning & Development

25. Key Competencies
Data Analytics
Data Visualization & Dashboarding
Communications and Market Engagement
Data Licenses
Promoting
Data Use
NDSAP DPDP Bill NDGP IT Act Sectoral Policies
Policies
Data Formats
Metadata Standards
Data Security and Privacy
Tools/Protocols
Data Quality & Assurance
Standards
API Development
Publishing Acceptance
Criteria
Cloud & Storage
Data Libraries & Tools
Preparing
Data
Data Structures &
Sources
Data
Cleaning/Curation
Entity Level
Roadmaps
Data Classification Data Prioritization
Governance Roles &
Responsibilities
Data Inventory &
Cataloguing
Data Identification
Access Mechanisms
Data Ingestion (Data
Platforms)
Governance
Strategy &
Processes
MeitY will be undertaking continuous learning and development efforts across the below competencies for
the Data Fellows

26. Suggested Readings
National Data Sharing &
Accessibility Policy
(NDSAP)
NDSAP
Implementation
Guidelines
Open Government
Data License
Draft National Data
Governance Policy
Digital Personal
Data Act
SPDI Rules (IT Act)
Draft Health Data
Management Policy*
DGQI
Methodology
*
* Only applicable for fellows deployed in MoHFW

27. Thank You