Development of a Spatial Data Infrastructure for the Water Sector of Benin

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1 Development of a Spatial Data Infrastructure for the Water Sector of Benin J. van der Kwast, MSc, PhD Senior Lecturer in Ecohydrological Modelling UNESCO-IHE Institute for Water Education j.vanderkwast@unesco-ihe.org

2 Introduction: Benin Capital: Porto-Novo Largest city: Cotonou Population (2012): 9,598,787 Density: 87.1/km 2 Area: 112,662 km 2 Language: French Government: Multiparty presidential republic President: Yayi Boni

3 Introduction Benin has adequate water resources for food production, drinking water and nature conservation Nevertheless, unsustainable agricultural and other land-use practices and water use, combined with the anticipated effects of climate change and population growth threaten the water resources

4 Introduction Benin is already confronted with large environmental problems such as seasonal water shortages, (urban) pollution, salinization and increasing damage due to flooding

5 1. Stratégie et gouvernance - 2 Driving Forces and Vulnerability Driver: Sea level Rise Driver: Population Growth Driver: Economic Growth

6 Strategy and Governance

7 GIS and IWRM Climate Change Health Population Growth Agriculture Drinking water IWRM Economy Sanitation Environment

8 Institut National de l Eau (INE) Nuffic NICHE-BEN-167 project: Establishment of a Water Institute to deal more effectively with water and sanitation problems

9 Context of the feasibility study Sharing of data is necessary for Integrated Water Resources Management Need for a system for sharing data The current systems are autonomous, with short term objectives, no interoperability among the systems Absence of a culture that enables communication and sharing of data No tool has been established to enable exchange of data

10 Context of the feasibility study BDI BDI HAB ASECNA AKVO Base de données IGN Plan Delta

11 SNIEAU Système National d Information sur l Eau (SNIEAU, National Water Information System) Objective: Establish a national system for sharing reliable information on water facilitating decision making for integrated water resources management and sustainable development

12 Agriculture Health Added value, available for the water sector Development of apps and services Drinking water Sanitation SNIEAU Entrepreneurs/ researchers Economy Decision Support Systems

13 Vision of SNIEAU By 2016 Benin has a unifying, reliable and accessible system for sharing information and data for improved management of water and related resources through an exchange network between the institutions in order to improve intersectoral communication for a synergy of actions towards a harmonious and sustainable development

14 Organisation SNIEAU Working Group Stakeholders: ministries and other institutions that produce and/or use data for the water sector 2 representatives per organisation Involvement in the design and monitoring of the development of SNIEAU Secretariat DGEau Technological responsibility and coordination INE Technical assistance and education PPEAII NICHE

15 Milestones in the realisation of SNIEAU February : Presentation of the project June : Start of the Working Group October : Finalisation of the inception phase January : Finalisation of the feasibility study February : Presentation of the feasibility study

16 Justification of choice of technology

17 Where is the data? Nombre d'institutions (en %) Papier DVD/CD Disques durs externes Serveur

18 Where is it archived? 100 Nombre d'institutions (en %) Papier DVD/CD Disques durs externes Serveur

19 How is data shared? Paper: 82% Digitally (USB stick, DVD/CD, ): 94%

20 Main challenges Instability of the power supply Instability of the internet connection Most data are still shared on paper

21 Technical solutions for SNIEAU Centralised architecture External hosting Open source software

22 Centralised architecture Institute A Institute B SNIEAU Institute C

23 Distributed architecture SNIEAU Institut A Institut B Institut C

24 Hybrid architecture Institut A Institut B SNIEAU Institut C

25 Advantages and disadvantages of Architecture Type different architectures Avantages Less investments in hardware and software Désavantages Requires great confidence and a clear legal framework Centralised Distributed Hybrid Less cost for securing power and internet supply Secure backups True networking, where everyone is fully in control of his data Policy developed in each institute Combines the advantages of the other two solutions Creates redundancy Difficulty of defining a common policy Large investment cost for each institution Combines the disadvantages of the other two solutions Large investment cost

26 Choice for hosting Hosting type Advantages Disadvantages Internal External Confidentiallity better preserved Ensuring large up-time of the service (e.g. >95%) Minimized costs Large investment in hardware, software, human resources, skills Need to secure the power supply and internet connection The privacy policy is not always clear

27 Hosting Installation and maintenance: Upande Ltd., Nairobi, Kenya ( Amazone cloud 5 years maintenance contract

28 Choice for open source software Open source software often provide better interoperability between internal and external components Open source software often use international standards Proprietary tools impose limits to the user; it is difficult to make improvements, complicated to change supplier (lock in) Open source software is improved continuously thanks to the participation of the user community Quick implementation of new developments (at the forefront of technology) Opportunity for innovation for Benin

29 GeoNode Source:

30 Which data? Fundamental data: Fundamental data is a dataset for which several government agencies, regional groups and/or industry groups require a comparable national coverage in order to achieve their corporate objectives and responsibilities.

31 Application matrix Structure responsable Spécificité thème (couches, types, sources de données) Géométrie de la couche Intitulé du thème ou application Demande utilisateur ou total coef.

32 Application matrix Analysis of the actual situation based on an inventory of products and services Evaluation of the use of frequency layers Identify priorities for the update Priorities for quality improvement Add the desired situation Set priorities for the acquisition of new data Impacts improvements on the underlying information systems Gives arguments for financial support

33 Why is sharing so difficult? Individuals, institution and governments often see risks in sharing data (UNECA, The SDI Handbook for Africa): a priori suspicion of the quality of third party data is common. a priori presumption that the institutions own data (generally deemed of high quality by the latter) may be wrongly used if shared with a third party, or even that ownership thereof may be lost. fear that other users discover the poor quality of their data by sharing them.

34 Metadata Metadata should clarify terms of use of data The user should be able to determine if the data is suitable for his/her purpose

35 SDI Data Policy A sound data policy should look carefully at ways to remove the potential risks so that the data producers are happy and confident in sharing their data Commitment of all contributing stakeholders is needed

36 Need for a policy What data types/themes will be stored in the system? Who will upload the (meta)data? When will the (meta)data be uploaded? Who is responsible for the (meta)data? Who will check new data added to the SDI? Who can be addressed for issues with the SDI?

37 Business models Value of information is the amount a decision maker would be willing to pay for information prior to making a decision

38 Business models Publicly funded data are a public good, produced in the public interest and thus should be freely available to the maximum extent possible.

40 Costs of selling data Organisations can overestimate the return on investment of selling the data they own (including making it available through a freemium business model) if they underestimate the costs that can be involved, such as: legal costs of creating and enforcing restrictive licences development costs of restricting access and use of data administrative costs of issuing licences sales and marketing costs to promote the data

41 Strategic risks of selling data Low willingness to pay (like with music, movies, etc.). People are becoming less prepared to pay for digital products that can easily be copied and shared with others Competitors or communities might also be able to undermine your data business by releasing their data as open data.

42 Organisation of SNIEAU 2 administrators: User management Management of the platform Communication of anomalies 1 steering committee 1 representative of each organisation Quarterly meetings Tasks: decisions, sustainability, initiative to keep SNIEAU active Yearly reporting with conclusions and recommendations Team for technical assistance

43 Actions for the near future

44 SNIEAU: an infrastructure The infrastructure has been put in place For you to ride now!

45 Actions for the near future At the level of each organisation: Participate in the SNIEAU network Establish an organisational framework for data management Submit your data Improve your information systems Discuss your needs

46 Actions for the near future For SNIEAU Establish the organisational structure Take actions needed for further development of SNIEAU Plan and organise trainings Become the source of information for large projects, e.g. Plan Delta Ouémé

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