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1. The Shared Database

Realising the future potential of APHLIS within strengthened African agricultural information systems. 1. The Shared Database. 2. Structure of the regional technology platform - a module of www.erails.net. The Shared Database. Problem Loss of Data Data-Drain Defective fuse (no backup)

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1. The Shared Database

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  1. Realising the future potential of APHLIS withinstrengthened African agricultural informationsystems

  2. 1. The Shared Database 2. Structure of the regional technology platform - a module of www.erails.net

  3. The Shared Database • Problem • Loss of Data • Data-Drain • Defective fuse (no backup) • Poor description of the data • Scarcity of available / accessible data • Missing sink • Unwillingness • High cost of specialized information systems

  4. Estimated development costs of specialized information systems 60 %10 %30 % Backend for data collection anddata Management Frontend to display results Data processing • Other limitations: • Aging technologies • Low flexibility • High operating costs • High training costs • The reuse of the data entered is often limited because they are poorly described and accessible. • => Many specialized information systems have a low life expectancy

  5. Objectives Provide a system for decentralized management and sharing of numeric data from agricultural research. Create a basis for the sustainable operation of the system. Strengthening African ownership. Integration of the sdb into an African platform in collaboration with FARA.

  6. Challenges - the sdb is expected to: • accommodate a wide range of data • describe data according to international standards • take into account currency exchange rate fluctuations • provide a multilingual interface (EN, FR, PT, ES) • cope with poor connectivity • be simple to use in order to keep training costs low • operate on a sustainable basis

  7. Structure of the sdb Quality Reference Geom Data Matrix Location Specification Figures User Role Object Property Variable Class Currency Unit US$ Standard Unit

  8. Classification according to international standards • Objects • 00 Regions – SEEA: Land Use Classification: Proposed to be used in the System of integrated Environmental and Economic Accounting (SEEA) • 01 Soils WRB: World Reference Base for soil resources 2006: A framework for international classification, correlation and communication • 02 Corps - ICC v1.0: FAO Indicative Crop Classification - version 1.0 (ICC) • 03 Activities ISIC Rev.4: FAO International Standard Industrial Classification of all economic activities, Rev.4 • 04 Products CPC Ver.2: UN The Central Product Classification of the UN (CPC) Ver.2

  9. Excerpt from the list of objects

  10. Classification of variables according to Classes and Groups • 01 Weather • 0101 Temperature • 0102 Precipitation • 0103 Wind • 0104 Air humidity • 02 Soil • 0201 Chemical properties • 0202 Physical properties • 0203 Biological properties • 03 Land use • 04 Crop production • 0401 Preparation • 0402 Planting • 040201 Density • 0403 Nutrient management • 0404 Pest management • 0405 Management other • 0406 Irrigation • 0407 Harvest • 040701 Production 1st season • 040702 Production 2nd season • 05 Animal production • 06 Post harvest management • 07 Trade • 0701 Internal • 0700101 Producer price (per kg) • 0700102 Wholesale price (per kg) • 0700103 Retail / consumer price (per kg) • 0702 External • Currency Exchange Rates (monthly) • United Nations Treasury - The United Nations Operational Rates of Exchange

  11. Data input in 4 steps • Sign in (Get an account as Data Manager) • Define data space • Define list of locations • by the selection of administrative units (country, primary and secondary units) • by drawing of individual polygons • Define the observed objects and their characteristics: • select objects from the list standard reference objects (SRO) • specify properties for further distinction of objects • specify expression of object-property for each object. • Define source of information • Elaborate data-matrices. A matrix is a grid that ensures that the values ​​are uniquely referenced in the course of data input. • Define data entry agent: A data manager can specify several data entry agents, to which he can assign matrices for data input.

  12. Define matrices for data entry Account holders can create data-matrices according to their individual needs. They can choose between two models: 1-Variable | x-Objects1-Object | x-Variables

  13. Some features • Export and import of data-matrixes as CSV

  14. Some features Amounts in local currency are automatically converted to U.S. $.

  15. Some features Define specific location (polygon)

  16. Some features Application programming interface (API)

  17. Example of application The African Postharvest Losses Information System 3 CMS 2 EXPERT SYSTEM 1 SHARED DATABASE open data www.erails.net www.aphlis.net sdb.afris.org Narrative & country specific information products Management and sharing of row data Data processing and provision of factual information Combine knowledge and expertise for the development of an algorithm for the calculation of PHL estimates Provide data about factors that affect PHL and that is needed to compute PHL estimates: production, marketing, storage, …. Context and target group specific packaging of information The APHLIS NETWORK

  18. 2. Structure of the regional technology platform - a module of www.erails.net

  19. Knowledge management in an innovation continuum R&D Community Community of practice Knowledge Exchange • Knowledge Generation • Problem definition • Basic and applied research • Technology development • Extension to R&D sector • & primary innovators. • Knowledge Application • Operational testing • Demonstration • Technology transfer • Use in policy, practice and processes • Identification of new problems Knowledge Exchange • Defining problems with customers • Working with customers and R&D community on science based solutions • Linking to indigenous and experimental knowledge • Information collection, synthesis and distribution • Extending knowledge and innovations • Education and training • Operational testing • Outreach and trouble shooting • Information management • Redefining problems and R&D knowledge gaps

  20. Structure of the regional technology platform a module of www.erails.net THEORY Section 1 Science & Technology Content managed by members of the R&D community (R&D) PRACTICE Section 2 Regions Content managed by stakeholders of the Community of practice (CP) Knowledge Exchange Mechanisms

  21. Structure of a regional technology platform THEORY Section 1: Science &Technology Content managed by members of the R&D community (R&D) PRACTICE Section 2: Regions Content managed by stakeholders of the Community of practice (CP) Home Country 1 … Commodity X e.g. Camel Country 2 e.g. Benin Commodity 2 e.g. Maize … Country X Commodity 1 e.g. Banana Domains VC-link 1 e.g. Seeds VC-link 2 e.g. Nutrition ....... … VC-link X e.g. Pests Accounts Region 1 Region 2 … Region X Commodity 1 VC-link|Issue e.g. Banana-Harvest-Tools Commodity 2 VC-link |Issue e.g. Maize – Nutrition - Organic .. . Commodity X VC-link |Issue e.g. Chicken–Trade-Labeling Issue 1 Pages and subpages e.g. Organic - crop residues Issue 2 Pages and subpages e.g. Mineral - Zinc … Issue x Pages and subpages e.g. Tools -Storage WebSites Pages Subpages Knowledge Cluster with features, mechanisms and tools facilitating exchange A knowledge cluster is defined by the pages that are classified according to the same commodity – VC-link - Issue – combination

  22. Management of the science & technology section by the R&D community Content is provided by experts from regional centres and networks of excellence according to guidelines that reflect the information needs of the community of practice. VC-links are commodity specific. planning Issues diagnostics products services education equipment post harvest harvest Value Chain-Links seed nutrition Regional centres and networks of excellence water weeds Crosscutting Thematic networks Marie Claire John Baker (Moderator ) Crosscutting Thematic networks Commodities Issue rice Rice-net maize Maize-net beans Commodity Beans-net Knowledge cluster wheat VC-link Wheat-net sorghum Sorghum-net banana Banana-net BioTech BioTech Agroforestry APHLIS

  23. Management of the content from the regions by the community of practice rice Commodity VC-link Issue maize cassava tomatoes coffee Content is provided by organisations and associations that represent producers, traders, transformers and consumers. Information of each region is classified according to commodity – VC-link - Issue. yam Atlantique Ouémé Regions Colinnes Atacora Mono Borgou Extension service Farmers’organisation 1 NGO Regional commodity associations Countries Benin Congo Ghana Kenya Content is provided according to guidelines that reflect the information needs of the R&D community and stakeholders from other regions. Uganda Zambia Grain council Coffee board

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