Data ecosystems: turning data into public value
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The document discusses open data and data ecosystems, emphasizing the importance of data quality, reuse, and the creation of services that provide public value. It outlines stakeholders' engagement strategies, governance structures, and technical enablers necessary for building sustainable data ecosystems. Additionally, it highlights various projects and findings related to open data's impact, particularly in Luxembourg and Europe.
Data ecosystems: turning data into public value
- 1. Slim Turki, Dr. Open data & Data Ecosystems slim.turki@list.lu October 6th, 2021 AIH Live Exchange #Session 7
- 2. Open Data release and re-use ▪ Data and Metadata quality ▪ Turning Open Data into services and public value ▪ Barriers, incentives, enablers Data ecosystems orchestration ▪ Ecosystem thinking and modelling: identify and trigger the uptake of data ecosystems ▪ Organizational and technical Governance ▪ Sustainability: Value creation and distribution, business models, impact assessment ▪ Data flows: Increasing data-reuse beyond the original purpose, new modes of data creation and exchange BE-GOOD (Building an Ecosystem to Generate Opportunities in Open Data, Interreg NWE, 2016-2022) Support cities, regions and national authorities for data release, re-users engagement, PPPs, innovative procurement, impact assessment. ASTEROID (Data ecosystems for geospatial data, EC - Joint Research Centre, 2019-2020) Identify and analyse successful data ecosystems and address recommendations in support of the implementation of data-driven innovation in line with the European strategy for data. Impact of open data in Luxembourg (2017 - 2019) Studies for the Government of Luxembourg. Share-PSI 2.0 (ICT-PSP, 2013-2016) Best practices for Public Sector Information release in Europe. Open Data for a Smarter Society ODYSSEY 2
- 3. Introduction 3 Official statistical data recognized as high-value datasets for society and economy, to enrich research, inform decision making or develop new products and services. Data production and release come at a high cost Not enough to generate public value Inadequacy between offer and demand Value creation from open data remains difficult to assess Structure 1. Introduction to data ecosystems 2. Stakeholders mapping and engagement (Data ecosystem starter kit) 3. Recommendations for the establishment of sustainable data ecosystem
- 4. Provider: Provides open data Enabler: Facilitates the supply or use of open data Enricher: Uses open data to enhance existing products or services Developer: Uses open data primarily for the development of applications Aggregator: Uses Open Data to gather meaningful insights 4
- 5. “The value of data lies in its use and re-use” Ecosystem Thinking Beyond data provision paradigm Strategic move Integrate other stakeholders’ perspectives Starts with creating community around data Disclaimer: No one-size-fits-all Localized strategies and action plans Learning by doing Data Ecosystem (or ‘data-driven digital ecosystem’) is where a number of actors interact with each other and their environment for a specific purpose, generating value from the network by producing, exchanging and consuming data in a collectively governed and operated way. 5
- 6. NSO 6 Public Sector • Government departments • Local Authorities • Policy makers • Emergency services Private Sector • Business and commerce • Incubators and accelerators Journalists & Media • Data journalism Civil Society / NGOs • Open Data communities • Historically, a driving force in advancing open data agendas Research, academia and students • Data users and suppliers • Open Data research Multilateral organisations • E.g. Development banks. Citizens / General public
- 7. Prioritize stakeholders, users and re-users 7 Keep Satisfied Inform + Consult Engage Closely Inform + Consult + Collaborate Low High High Stakeholder Interest Stakeholder Influence Minimal Effort Inform Show Consideration Inform + Consult
- 8. Stakeholder Engagement Continuum 8 Monitor • Pay attention to the actions of stakeholders • Through media scans, internet searches, and conversations with other parties that may have knowledge of their actions or positions • Logs analysis, within the limits of privacy protection rules • Interactions on social media Message • Create and target messages toward specific stakeholders. • An invitation to respond is typically not implied. • Newsletters • Posts on social media • Press releases • Publicity campaign • Dedicated sections on the portal for specific stakeholders' groups (e.g., SMEs) Advocate • Participate in activities intended to enlist support for a specific effort or position where there is an imbalance or implication of power/influence affecting the relationship. • With internal / external sponsors: Policy makers, journalists, supporting organizations, etc. Consult • Solicit explicit feedback or input on a project or plan. • Surveys (satisfaction) • Published content rating and commenting Dialogue • Initiate or participate in two-way dialogue focusses on mutual learning and solutions. • Can include co-creation of new ideas. • Discussion space on data portals • Organising events to increase awareness and interactions frequency. • Data Literacy (lectures in Universities or organisations) Collaborate • Share work on common objectives of the organization and its stakeholders. • Can include co-creation as well as co- implementation of new ideas. • Partnerships, Procurement, etc. • Consolidated relationship Diagram inspired by https://www.bsr.org/en/our-insights/blog-view/a-guide-to-stakeholder-engagement-for-healthier-communities
- 9. Stakeholders' engagement 9 Hackathons & Competitions Useful for publicizing datasets, engaging stakeholders, rising awareness Not for developing long-term collaboration, sustainable services, generating impact. Problem-solving approach: Incubation, PPPs Promoting data literacy among all stakeholders Help users and re-users understand data, how to acquire data and how to apply data to specific needs. Lectures in Universities / Internships: access to data hungry population, future practitioners, entrepreneurs. Connect to local interest groups and communities of practice Tutorials on data portals Evidence-based decisions and policymaking Covid-19 Dashboards Sendai Framework for Disaster Risk Reduction SDGs reporting
- 10. Better alignment between data demand and offer Identify barriers, incentives, enablers to re-use released data New use cases Demonstrate measurable impacts Identify and report (re-)use cases Created services, jobs, business opportunities Could be promoted on data portal Enhance country visibility and classification Play a leading role Influence the ecosystem general architecture Consolidate reputation and trust Develop formal / informal partnerships and networks Secure resources Attract open data donors and investors (providing finance, connecting stakeholders (including the private sector), providing technical assistance and knowledge transfer) Motivation 10
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- 12. Body of rules, procedures and practices that relate to the way interactions between the actors are framed. 1. Identifying the most relevant actor(s) to embrace the role of orchestrator depending on the nature and evolution of the ecosystem. 2. Building a collaborative governance of the ecosystem 3. Clear consideration (roles, benefits, needs, means, BMs) for all stakeholders ensure the willingness to make the data ecosystem sustainable. 4. Importance of considering and aligning stakeholders' different cultures. 5. Importance of stakeholder networks, to share good practices, to benchmark initiatives, but also to provide insights Ecosystem Governance 12
- 13. Technical enablers Establishment of Sustainable data Ecosystems 13 1. Creation of a platform provides a strong incentive to structure the ecosystem. a. Choosing the platform architecture (tools and capacity) based on the specific features of the ecosystem. b. Aligning the data ecosystem with other components such as cloud and software ecosystems. c. Integrating in the platform not only data but also services and even computational infrastructure. d. Put the APIs at the core of the approach. 2. Data standardisation is an enabling condition to the emergence of data ecosystems. a. Suitable data and metadata models, standardised where possible. 3. Facilitate the access to disaggregated data, real time data and time series.
- 14. 14 Beyond the data provision paradigm, ecosystem thinking is a reliable approach to understand and to steer the development of data ecosystems and to extract public value from data Data ecosystems rely on strategic vision and long-term engagements Defining and integrating the relevant stakeholders enabling the success of the ecosystem. Strong political and societal support facilitate the sustainability of the data ecosystem.
- 15. thank you contact information For more info, please contact us at slim.turki@list.lu linkedin.com/in/slimturki/