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Data Inventory Draft Technical Report


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5Brainstorming Session with TCE Officers


A brainstorming session with TCE officers was held at the end of the assignment. The objective was to present the results of the inventory, to propose a framework for the implementation of the EIS and to gather from TCE officers (a) advices on essential data and information to be considered for the EIS and (b) suggestions for the design of the application modules. Details on the outcomes of the meeting are reported in Annex C.

In general, the meeting concluded that, although information available in FAO HQs is valuable and should be used within the EIS, data – especially at sub-national level – is insufficient and actions to collect and make available essential data is required. A list of datasets identified as priority and recommended for collection is reported in Annex C1.

The EIS - conceived as a modular system providing key indicators in support to emergency operations - was well received by the participants who suggested to proceed with the implementation of the modules identified during the consultancy. These modules, listed below, are described in detail in Section 6


  • Impact of disaster and needs assessment: Country Report module

  • Planning of operations: Seeds/tools Delivery module and NGOs module

6Preliminary Proposed Modules for the EIS


This section shows schemas for the implementation of the EIS functions that were identified by the TCE officers during the brainstorming session (see chapter 5). This subject is dealt with in general terms since technical details related to the development of the modules should be defined in consultation with the officers responsible for the data and systems to be interfaced with the EIS.

The general concept is to maintain each module independent from the others to enable additions, removals and upgrades of modules without affecting other system components. However, outputs of a module might be taken as inputs for other functions enabling in this way a “stratification” of applications according to the user’s convenience. The picture below is a graphic representation of this concept. It is obvious that linked modules are interdependent.

It should be noted that the functionalities and types of outputs described in the following paragraphs are indicative, and only represent a subset of the possible capabilities of the modules.

The picture above shows a generic and extremely simplified system architecture. Datasets are either obtained by other systems (System A, B, C…), external to the EIS, or directly maintained within the EIS (Data 1, 2, 3…). Modules at higher levels (Stratum B, C…), could use EIS data or EIS’s partners data in combination with the information derived from other modules.




6.1Disaster impact and Needs Assessment: a Country Report Module


It is meant to provide instantaneously background information to officers and consultants in the assessment phase. It has a very wide scope and can be developed in many different ways. A starting point is the data identified and considered suitable for the purpose by the TCE officers during the brainstorming session and listed in the table of Annex C2. Collecting information from the system knowledge-base, the module would produce a set of standard reports providing the most up-to-date information available in FAO on the country/area of interest. This module can also benefit from the FAO Country Report systems made available by the technical divisions. However, this module it is expected to combine this information with other emergency-specific data and indicators.


6.1.1Functionalities


  • Search by country/area

  • Providing a list of available reports that can be selected or unselected by the user

  • Combine selected reports into a single, structured document


6.1.2Data Inputs


The following are only some of the datasets that can be used by the module to compile the reports.

  • Rainfall estimates from ARTEMIS (it can be produced in aggregated or disaggregated forms at minimum temporal resolution of 10 days)

  • Land use from AGL at sub-national level or, if not available, Global land cover characteristics (1Km resolution) from USGS

  • Global Agro-ecological Zones from FAO-AGLL

  • Crop calendar from GIEWS or more detailed if possible (information recommended to be collected at sub-national level)

  • Agricultural market prices and production at sub-national (preferred) or national level from FAOSTAT and GIEWS

  • Number and type of livestock from DAD-IS, FAOSTAT and AGA livestock distribution database when available

  • Number and type of fishery from FISHSTAT at national level

  • Plantation types and extents

  • Population (urban/rural, gender, age) from UN Population Division

  • Percentage of population affected by HIV, malaria (urban/rural) from UN Population Division

  • Number f deaths (urban/rural) from UN Population Division

  • History of the country, political factors from CAP, WB, Country Profiles, IMF country profile, EU

  • Nutritional data from WHO

  • Internally displaced people, returnees & refugees; host population at district level from UNHCR, if available

  • Purchased farming tools from FAO Oracle Procurement

  • Existing farming tools at national level

  • Animal diseases (type of disease and livestock affected at national level) from EMPRES

  • Existing irrigation systems from IES – AGLW

  • Farming systems/livelihood zones (important but not available at a suitable resolution/map-scale)

  • Information on past and present assistance in the area from FPMIS

  • List and contacts of NGOs operating in the area


6.1.3General Structure


The structure of this module is similar to the one described in section 6.1 although it requires establishing links with a larger number of systems such as ARTEMIS, GIEWS, FAO Oracle Procurement Database, FPMIS and others. The information extracted from FAOSTAT, FISHSTAT, DAD-IS, IES, the Global AEZ, etc. could be transferred on regular basis to the EIS database instead of creating other links or interfaces with these systems. This would sensibly easy the complexity of the module.
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