The purpose of having a standardized naming convention is to provide an organized framework for the datasets, ensuring interoperability between users and platforms. (See below for Naming Convention for Information Products)
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Two sets of population data for a particular country, one has the population for major cities and the other population data for small towns. The data for major cities are labeled with a “1” and the data for small towns are labeled with a “2”.
- Dataset 1: Major cities in Burundi from Government of Burundi at 1:1M scale
- Dataset 2: Cities in Burundi from Government of Burundi at 1:M scale
Dataset Names (interim solution):
- Dataset 1: bdi_pplp1_1m_gov
- Dataset 2: bdi_pplp2_1m_gov
Feature Class Name (long term solution):
- Combine the two feature classes to 1 using guidance from Verifying Geometry. The resulting label would be: bdi_pplp_1m_gov.
Special Case 2: Data do not span an entire country or region
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Datasets not covering an entire country:
- Dataset 1: IDP Camps in Aceh, Indonesia
- Dataset 2: IDP Camps Afgooye Cooridor, Somalia
Resulting Dataset Names:
- Dataset 1: idn_aceh_cmpp_idp_1m_unhcr
- Dataset 2: som_afgooye_cmpp_idp_1m_unhcr
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- ISO3 Code – As with the geodatabase name, the first part of the naming convention consists of the ISO3 code. For example: wrl, afg, alb, etc.
- Topic – The topic corresponds to the folder in the data structure where the data would reside in flat file formats (shapefile, kml, xls, etc.). These topics can be found in the dataset the dataset naming codes table and table and in the folder structure.
Feature class name: As described above, the feature classes are named using the naming standard outlined above as if they were shapefiles.
Dataset Naming Codes
This table provides some of the codes and sub-codes to be used for naming datasets as described in the File Naming Convention. This list is not exhaustive and tries to address datasets commonly held by OCHA. Additional codes will almost certainly be needed by a country office to handle datasets particular to the local situation. If you would like advice on generating codes for other datasets, or if you have identified codes that you think will be useful for other offices, please Contact ISS in Geneva.
* Sub-codes denoted by an asterisk (*) should ideally be part of one more general dataset, where the features are differentiated in the attribute table and not through a separate feature dataset or feature classe.
These classes are outlined here as use for a temporary solution for incomplete datasets and/or datasets/gazetteers under consideration and/or development.
Naming Convention for Information Products
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