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Joined-up Data Standards

Joined-up Data Standards Navigator FAQs


The Joined-up Data Standards Navigator is a network of mapped data standards or classifications of data that are relevant to the field of development in the area of socioeconomic sectors, indicators, country classifications or surveys.

The Navigator cross-links standards in a machine-readable way to enable users to understand the relationships between different international data standards, and to make comparisons between them.

The Joined-up Data Standards Navigator is developed and maintained by Development Initiatives as part of the Joined-up Data Standards project.

As people who work with data on international development and humanitarian financing, we know how complex and time-consuming it can be to compare and work with data published to different standards and grouped by different classifications.

The Joined-up Data Standards Navigator was developed as a resource for those needing to work across multiple data standards, removing the manual work needed to understand how one standard or sector code relates or compares to another.

The Joined-up Data Standards Navigator is an easy-to-use resource for anyone who works with data relating to development either at an international or a national level.

If you are a data user handling complex data analyses who needs to compare data published to any of the mapped standards, or if you are a data publisher who wants to ensure their data is accessible and useful, the Navigator is for you.

The Joined-up Data Standards Navigator provides you with easy-to-use tools to make your life simpler and to increase the efficiency of your analysis. Our search and translate tool and our spreadsheet tool allow you to run a simple search to find out if and how data standards compare, saving you from the painstaking task of manually mapping the data yourself.

The search and translate tool allows you to browse and find the relationships between standards using simple or advanced search.

The spreadsheet tool provides you with the best translation of socio-economic activities between different international data standards, or retrieves the relevant international code for a given country. All of this will help save you time and allow you to focus on your analysis.

Our Joined-up Data Standards Navigator enables you to easily connect your data with that published in other international standards. By doing so, you will increase the potential reach and impact of your data, as you make it easier for users to access and analyse it.

Adding your standard to the Navigator will:

  • make it easy for data users to put your data to good use
  • show how your standard relates to others
  • support interoperability across different organisations and sectors.

The more standards that are mapped in the Navigator’s network, the more useful it becomes.

The data standards held in our Navigator network are linked together using the Simple Knowledge Organization System. This provides a universal and established ‘language’ for defining relationships between concepts (terms) and also provides a means of systematically comparing concepts across the mapped data standards.

Joined-up Data Standards Navigator search and translate tool

Our search and translate tool is an easy-to-use tool to help data users understand the relationships between different data standards. The tool offers both simple and advanced search functionality.

Simple search

The simple search enables you to identify all instances of a particular term or code from within our network of mapped standards. So, you can search for ‘health’ and be shown every occurrence of that term in the standards we have mapped (or within grouped ‘projects’). For example, when searching for ‘health’ within our ‘sectors’ project, the results will include:

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From there you can click an individual ‘concept’ or occurrence from within the search results:

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And explore how it relates to fields in other standards:

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Simple search allows you either to look for a specific project or browse for a specific term (or code) across projects.

Advanced Search

The advanced search filters enable you to be more specific about the results you will be shown, allowing you to select which data standards you would like to translate from and to.

For the advanced search to return valid results you must select:

  1. a specific project to be searched,
  2. the translation that you would like to be returned, such as exact or close relationship between standards
  3. which data standards you would like to translate from
  4. which data standard you would like to translate to.

Example: to find if there are any exact matches to the SDG indicator 1.1.1 (“Proportion of population below the international poverty line”) in the MDG framework, the search parameters would be:

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The Navigator’s output to this query is:

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This in turn informs me that the exactly the same indicator was also part of the MDGs identified by an indicator code 1.1. Clicking on the hyperlink will redirect you to indicator’s page where more information on it can be found.

When looking at a ‘concept’ within the network (for example an SDG target or a sector code), you’ll be shown what concepts/fields within that standard are broader or narrower than the one that you have selected.

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A broader concept is one that has a more general meaning than the concept that you have selected, and could simply be understood as an umbrella term, or the parent category. Most data standards are already grouped using this type of logic.

In the ‘basic health’ example above, the CRS sector code ‘Health’ is a broader match to ‘Basic health’ as it sits above basic health in the hierarchy – it is more general, a broader term. .

A narrower concept is one that is more specific than the one you have selected, so could be understood as being the child term. In the example above, ‘basic health infrastructure’ is a code that is narrower than ‘basic health’ – it is a more specific but sits within the ‘basic health’ family and under the umbrella of a health sector.

Broader and narrower concepts are used to link elements within a given data standard, such as sectors and sub-sectors in the OECD DAC CRS standard or goals, targets and indicators in the SDG framework. Representing internal relationships within a data standard ensures that not only humans but also machines can read them in a logical manner. These relationships are grounded in Simple Knowledge Organisation System (SKOS) a common model for linking and organising information.

As with the broader and narrower concepts, these terms relate to the relationships between the term you have selected and others. However, these are the matches that are made across other standards within the network.

The relationships denoted by broader/narrower/exactly/close matching concept help build the data standards map that sits at the heart of the Joined-up Data Standards Navigator.

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Broader matching concepts refer to fields in other standards related to the one you have selected, but that are more general in their focus. In the example above, ISIC’s field ‘agriculture forestry and fishing’ is broader than the OECD DAC CRS sector code ‘agriculture’.

Exactly matching concepts refer to fields in other standards that are a direct match for the one that you have selected. In this example, UN Classification of Functions of Government’s ‘agriculture’ is a direct match to the CRS sector code ‘agriculture’.

Narrower matching concepts refer to fields in other standards that relate to the one you have selected but that are more specific. In this example, the SDG indicator ‘Correct and prevent trade restrictions’ relates to the CRS sector code ‘agriculture’ but is more specific in focus.

You may also see a close matching concept, which refers to a field in another standard that, by W3C standards, is sufficiently similar that it can be used interchangeably with the field you’ve selected.

Joined-up Data Standards Navigator spreadsheet tool


Our spreadsheet tool allows you to get the best translation from one sector code to another or to retrieve a relevant international code for a given country from directly within the spreadsheet you are working in.

Currently the tool is available as a Google Sheet Add-on. It can be used directly in a Google Sheet and results can be downloaded in Microsoft Excel format. A Microsoft Excel macro will be available in the future.

How to get the tool

  1. From your active Google Sheet, select “Get add-ons” from the top “Add-ons” menu.
  2. Search for "Joined-up Data Standard Navigator spreadsheet tool"
  3. Click on '+ FREE'
  4. Sign in to your Google Account if prompted
  5. Review the summary of add-on’s requirements and select 'Allow'.
  6. JUDS Navigator spreadsheet tool’ is now available in your 'Add-on' dropdown menu within your Google Sheet.

Function: translateSectorCode()

This function returns the best translation between codes used by data standards describing socio-economic sectors and economic activities. These include: OECD DAC CRS (crs), UN Classification of Functions of Government (cofog), UN International Standard Industrial Classification of All Economic Activities (isic), IRS National Taxonomy of Exemption Entities (ntee) or World Bank themes (world_bank_themes) and sectors (world_bank_sectors).

The abbreviations used by the function to recognise individual data standards are shown in bold red and in brackets in the list above.

To use the function, select the cells containing, or enter directly into the function:

  • where to translate the code from,
  • which standard to translate to
  • the sector code from the data standard you wish to translate from

Example: to translate from OECD DAC CRS code 323 (“Construction”) to UN International Standard Industrial Classification of All Economic Activities, the function would be:

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Cell A1 denotes the starting classification, B1 is the standard to translate to and C1 is the code I need to translate. D1 denotes the cell where the output to the above query is displayed. In this example, “F” is the code for “construction” in ISIC data standard.

This function first searches for an exact or close match. If there is not an exact or close match, the function delivers a broader search result, along with a notification.

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When no match can be found the function simply returns a notification.

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Function: translateGeoCode()

This function allows you to retrieve the following codes for each country: OECD DAC recipient or donor code (dac), UN FAO country code (faostat_num), FAO Global Administrative Unit Layer (gaul_num), IMF IFS code (imf_ifs), ISO 2 (iso_2), ISO 3 (iso_3), UN country code (un_num).

The abbreviations used by the function to recognise individual data standards are shown in bold red and in brackets in the list above.

To use the function select the cells containing, or enter directly into the function:

  • country name
  • type of code to be returned.

Example: to find the DAC recipient code for Belize, the function would be as follows:

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If there is no code that matches user query, the function will return a notification:

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This function is not case sensitive and will attempt to find a given country name, even if an incomplete name is entered. For example, searching “Sao” will render results for São Tomé and Príncipe and searching for “Côte” will render results for “Côte d’Ivoire”.

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