1. Interoperability and standards for statistical data exchange
Sub-regional workshop on data and metadata sharing and exchange for English-speaking African countries
19-21 September 2018
Kigali, Rwanda
Daniel Eshetie
United Nations Statistics Division

2. modernizing statistical data exchange and dissemination

3. Challenge of modernizing statistical data exchange and dissemination
Statistical organizations strive to modernize their entire business processes, from data collection to dissemination
They face distinct resource constraints and operate in many different types institutional environments
There is need to build new systems on what already exists, often relying on legacy systems that need to be maintained

4. Cape Town Global Action Plan for Sustainable Development Data
Provides a framework for planning and implementing statistical capacity building
Calls the global statistical community to take decisive actions to transform how data and statistics are produced and disseminated
In particular, underlines the need for improved data interoperability to address the information demands of the 2030 Agenda

5. Cape Town Global Action Plan for Sustainable Development Data
Strategic Area 2: Innovation and modernization of national statistical systems
Objective 2.1: Modernize governance and institutional frameworks to allow national statistical systems to meet the demands and opportunities of constantly evolving data ecosystems
enhanced data sharing across the NSS
improve transparency of, and public access to, official statistics

6. Cape Town Global Action Plan for Sustainable Development Data
Strategic Area 2: Innovation and modernization of national statistical systems
Objective 2.2: Modernize statistical standards, particularly those aimed to facilitate data integration and automation of data exchange across different stages of the statistical production process
Define and implement standardized structures for the exchange and integration of data and metadata…
Promote interoperability

7. Cape Town Global Action Plan for Sustainable Development Data
Strategic Area 2: Innovation and modernization of national statistical systems
Objective 2.2: Facilitate the application of new technologies and new data sources into mainstream statistical activities
Identify specifications for interoperable, open source technologies
Promote the development of integrated database systems

8. Interoperability

9. Data interoperability challenge
Organizations often develop and maintain fragmented data production and dissemination systems to meet the needs of different internal and external constituencies
disparate protocols for data exchange
proprietary technological platforms
diverse data models, classifications, file formats…
This makes it very difficult to integrate the wealth of data that is available across organizational boundaries

10. Interoperability Ability to:
Search many data collections in a single query
Exchange data across computer systems using standard data formats and communication protocols
Automatically and unambiguously interpret the meaning of the information exchanged
Integrate multiple data assets into coherent information products

11. Key enablers of data interoperability
Technology standards
Allow system components developed and maintained by multiple parties to be seamlessly integrated and to work together
Enable multi-lateral exchange and use, in contrast to bi-lateral exchange where an agreement needs to be reached between each pair of parties, or the data consumer needs to adapt to the practices and standards of each data provider
• Technology standards
• Common (high-level) data and metadata models
formalize the description of data and metadata objects in a consistent way across disparate systems
• Common vocabularies and classifications
ensure there is no ambiguity regarding the information content of data services provided by different sources
• Geographic information systems
Enab;le multiple data items to be linked by location and analysed using the description of geographically-related features,
• Application Programming Interfaces (APIs)
An API is a reusable interface to which different client applications can easily connect. APIs provide essential capabilities for extending and integrating various data and software components by allowing users to link data and processes from multiple sources. APIs also facilitate the discovery of new uses for existing data assets and make them easily available to external third-party developers; thus fuelling new innovations.
• Data governance
To allow citizens, governments, international organisations, civil society organisations, businesses and other stakeholders to build their own applications on top of interoperable data services, it is necessary to develop and open and service-oriented data architecture that facilitates public access to a wide range of data assets from custodian organisations at different jurisdictional levels. Moreover, data management technologies and practices are rapidly evolving and require an increasingly collaborative approach. In this context, a data governance framework based on effective multi-level organisational arrangements to facilitate coordination, negotiation and collaboration across different territorial levels and stakeholder networks is urgently needed. The primary challenge when it comes to governance is reconciling collective and individual needs and interests to achieve common goals through collective decision-making. Coordination provides the critical link between the ‘steering’ process of governance and the ‘rowing’ activities of individual actors that move the community in the necessary direction.

12. Key enablers of data interoperability
Common (high-level) data and metadata models
Help formalize the description of data and metadata objects in a consistent way across disparate systems
Common vocabularies and classifications
Ensure there is no ambiguity regarding the information content of data services provided by different sources
• Technology standards
• Common (high-level) data and metadata models
• Common vocabularies and classifications
• Geographic information systems
Enab;le multiple data items to be linked by location and analysed using the description of geographically-related features,
• Application Programming Interfaces (APIs)
An API is a reusable interface to which different client applications can easily connect. APIs provide essential capabilities for extending and integrating various data and software components by allowing users to link data and processes from multiple sources. APIs also facilitate the discovery of new uses for existing data assets and make them easily available to external third-party developers; thus fuelling new innovations.
• Data governance
To allow citizens, governments, international organisations, civil society organisations, businesses and other stakeholders to build their own applications on top of interoperable data services, it is necessary to develop and open and service-oriented data architecture that facilitates public access to a wide range of data assets from custodian organisations at different jurisdictional levels. Moreover, data management technologies and practices are rapidly evolving and require an increasingly collaborative approach. In this context, a data governance framework based on effective multi-level organisational arrangements to facilitate coordination, negotiation and collaboration across different territorial levels and stakeholder networks is urgently needed. The primary challenge when it comes to governance is reconciling collective and individual needs and interests to achieve common goals through collective decision-making. Coordination provides the critical link between the ‘steering’ process of governance and the ‘rowing’ activities of individual actors that move the community in the necessary direction.

13. Key enablers of data interoperability
Geographic information systems (GIS)
Enable multiple data items to be linked by location and analysed using the description of geographically-related features
Application Programming Interfaces (APIs)
Help extend and integrate various data and software components by allowing users to link data and processes from multiple sources.
Facilitate the discovery of new uses for existing data assets and make them easily available to external third-party developers

14. Collaborative on data interoperability

15. Collaborative on SDG Data Interoperability
On 17 January 2017, at the first UN World Data Forum in Cape Town, South Africa, the Global Partnership for Sustainable Development Data (GPSDD) and the United Nations Statistics Division (UNSD) convened a meeting on the theme of Advancing SDG Data Interoperability
A multi-stakeholder meeting on data interoperability for the SDGs, on 5 March 2017 in New York, established a new Collaborative on SDG Data Interoperability

16. Collaborative on SDG Data Interoperability
Objectives
Connect: create a virtual space for stakeholders across constituencies to come together
Experiment: foster an environment in which new solutions to interoperability challenges are experimented with and prototypes jointly developed
Learn: build and catalogue a body of knowledge, lessons and stories on the success, replicability and scalability of data interoperability solutions
Advocate: raise awareness among stakeholders about how data interoperability can help meet and monitor the SDGs

17. Collaborative on SDG Data Interoperability
Deliverables (to be presented at the second UNWDF in Dubai)
Technical Interoperability Guide Hands-on recommendations to improve data interoperability within and across organizational boundaries
Policy Brief Document to highlight the benefits that interoperable solutions can impart for decision-makers, contributing to efforts making the case for investments in data for development