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Malaysia Open Data Readiness Report Delivery


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Formal presentation of the findings of the Malaysian Open Data Readiness Assessment, by the World Bank

Published in: Government & Nonprofit
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Malaysia Open Data Readiness Report Delivery

  1. 1. Open Data for Malaysia
 Open Data Readiness Assessment MAMPU and World Bank Ton Zijlstra,, @ton_zylstra Carolina Vaira #jomkongsidata 25th May 2017
  2. 2. Outline ● What open data is, how it creates value
 ● The ODRA Methodology ● Key Results ● Recommendations / Actions 2
  3. 3. Data, 
 that is public, and in machine readable formats can be freely downloaded, used, re-used & redistributed by anyone for any purpose
  4. 4. four good reasons more efficient public services more effective public services more transparency socio-economic activity
  5. 5. OPEN data open DATAvs
  6. 6. Open Data Readiness Assessment (ODRA)
  7. 7. ODRA ● A quick diagnostic tool
 ● Not a scorecard, evolving, not absolute
 ● Gives a cross-government overview ● Suggest actions possible in current situation 7
  8. 8. 8ODRA looks at 8 dimensions
  9. 9. ODRA for Malaysia ● At request of & in close collaboration with MAMPU ● Desk research: policies, laws, statistics
 ● Interviews with dozens of agencies
 ● Interviews with academia, business community, civil society ● Comparison with international practices ● Draft report for feedback and WB internal review 9
  10. 10.
  11. 11. Overall Findings ● Most building blocks are in place
 ● Very rich in digital data, ● Well developed structures and capabilities, ● General policy goals well aligned ● Lead agency with high level support, ● Circular, ● Portal, ● Engagement activities
 ● Building blocks need more connections to really drive impact of open data ● Legal aspects, agency buy-in, data provision, and stakeholder relations need most attention 11
  12. 12. Overall Findings: Dimensional Assessments 1. Senior Leadership 4. Data Availability and Management 6. Civic Engagement and Capabilities for Open Data 2. Policy and Legal Framework ODRA 7. Funding an Open Data Program 3. Institutional Structures, Responsibilities, and Capabilities 5. Demand for open data 8. National tech and skills infrastructure
  13. 13. Legal aspects ● No single guiding legal framework ● Strongly devolved decision making on sharing data (to both government and public) ● Obstacle: uncertainty and inconsistency, case by case decisions, escalated to high level
 ● Opportunity: agency by agency, decisions can be based on expected impact for data holding agency itself 13
  14. 14. Agency buy-in ● More government champions needed, more awareness and buy-in ● Perception of open data as useful government instrument will increase momentum ● Connecting data provision to domain / sector related policy goals ● Strong demand for examples from elsewhere
  15. 15. Data Provision ● Often hard to get data currently, also G2G ● Case by case decisions at high level ● High-value data sets, continuity ● Fee structures likely inhibit latent demand 15
  16. 16. Stakeholder relations ● Strong demand from academia, business community, and some civil society organisations (less from wider civil society and media) ● Unmet demand (geo, Denge, stats, other) ● Need for more continuous relationships, and at agency level. Also to help develop demand. ● Not just after but also before publication of data ● Offers of help to improve quality of data 16
  17. 17. Recommendations for action ● Increase impact of current situation ● Efficiency and effectiveness for the public sector ● Enable socio-economic impact 17
  18. 18. Increase impact of current situation ● Increase awareness and buy-in inside agencies, find more advocates ● Focus on (granular, specific) outcomes ● Link to sectoral policy goals ● Meet existing demand ● Collect and share examples ● Agency by agency approach 19
  19. 19. value, efficiency, impact linking open data to sectoral policy goals policy issue stakeholders open data
  20. 20. ideally data provision reflects national policy goals
  21. 21. if you know why, you’ll see the impact
  22. 22. Efficiency and effectiveness for the public sector ● Clarify legal situation for specific agencies / data sets ● Streamline decision making processes for providing data, make default decisions, automate frequent requests, provide as open data (Circular) ● Look at fees, abolish when economically illogical ● Meet interagency demand with open data, as the cheapest way to exchange ● Welcome assistance from other stakeholders ● Agency by agency, MAMPU for guidance 23
  23. 23. Enable socio-economic impact ● Improve openness of existing published data (machine readability, open license) ● Publish agency inventories of existing data (triggers demand) ● Simplify ways to request data, and to entertain questions (articulates demand) ● Invest energy in intensive and frequent contact between external stakeholders and agencies ● Create a continuous dialogue around demand and possibilities (e.g. ODUG) 24
  24. 24. Wie is hier extern collaborative connections more than implementation
  25. 25. Terima kasih