Capability
Capabilities is one of the four pillars, or areas of assessment, of the Global Data Barometer and will be examined as a core module given its foundational importance across all aspects of data activity.
Having data available or having the right rules in place for governing data will not lead to significant public good if a country lacks the capability to create, manage, and use data effectively. Capabilities involve having the opportunity to do something of value and relate to issues of access, skills, infrastructure, institutions, and intermediaries. We also draw upon Gurstein’s notion of effective use.
Many of the capability indicators within the Barometer will draw on secondary data, although a number of primary indicators are also included.
To find out more about the development of this core module, you can consult our research handbook.
Capabilities primary indicators
To what extent is the government providing training to develop civil servants’ data literacy and data skills?
Existence
-
Is there evidence of government´s actions to train civil servants on data matters?
- There is no evidence of government supporting civil servants training on data matters.
- There is isolated evidence of government supporting civil servants training on data matters.
- There is some evidence of government supporting civil servants training on data matters, as part of a planned and sustainable strategy.
- There is widespread and regular evidence of government supporting civil servants training on data matters, as part of a planned and sustainable strategy.
Elements
Kinds of capacities:
- Training delivered covers data frameworks and governance topics.
- (No, Partially, Yes)
- Training delivered to public servants covers topics on data gathering.
- (No, Partially, Yes)
- Training delivered covers data analysis, visualisations and storytelling techniques.
- (No, Partially, Yes)
- Training delivered covers specific technical topics for data centred roles.
- (No, Partially, Yes)
User groups:
- Training on data addresses non-technical public servants.
- (No, Partially, Yes)
- Training on data is focused on specific positions already working with data.
- (No, Partially, Yes)
Specific features:
- Training is planned by an established training team, department, or agency.
- (No, Partially, Yes)
- Public servants receive a certification when taking a training so there is a formal recognition as a professional development.
- (No, Partially, Yes)
Extent
-
How widespread, in terms of agencies and ministries, are the trainings assessed for this question?
- The training assessed is available to one or more agencies or ministries, but there are many other agencies or ministries without such training.
- The training assessed is representative of the kind of training that can be found for all, or most, agencies or ministries.
-
How widespread, in terms of jurisdictions, are trainings assessed for this question?
- Assessed training involves sub-national or local public servants of one or more localities, but there are many other localities without such trainings.
- Assessed trainings involve sub-national or local public servants, and are representative examples of the kind of trainings that can be found for all, or most, localities.
- Assessed trainings involve national public servants.
To what extent is there a well-resourced open government data initiative in the country?
Existence
-
Has there been any form of government-led open government data initiative during the study period?
- There is no evidence of any government-led open government data initiative in the country.
- There has been a government-led open government data initiative, but there is limited evidence of recent activity.
- There is evidence of an active government-led open government data initiative.
Elements
Specific features:
- There is a government team in place supporting open data activities.
- (No, Partially, Yes)
- There is an allocated budget for open data activities.
- (No, Partially, Yes)
- There is a well-maintained open data portal.
- (No, Partially, Yes)
- There is guidance and support for government publication of open data.
- (No, Partially, Yes)
- Senior political leaders back the open data initiative.
- (No, Partially, Yes)
Extent
-
How widely does this, or similar, open data initiatives apply?
- The open data initiative covers only a limited part of the national government, or only covers one or more sub-national governments.
- The open data initiative covers only a limited part of the national government, but there are similar initiatives for many other parts of government.
- The open data initiative covers much of the national government, and there are similar initiatives in many sub-national areas.
- The open data initiatives covers much of both national and sub-national government.
To what extent is there evidence that government is providing support for data reuse?
Existence
-
Is there evidence of a government strategy to support and encourage data reuse?
- There is no evidence of government supporting and encouraging data reuse.
- There is isolated evidence of government supporting and encouraging data reuse.
- There is some evidence of government supporting and encouraging data reuse.
- There is widespread and regular evidence of government supporting and encouraging data reuse, framed by a long-term strategy.
Elements
Kinds of capacities:
- There is evidence of government efforts to support open government data reuse.
- (No, Partially, Yes)
- There is evidence of government efforts to support data reuse in a general sense.
- (No, Partially, Yes)
- There is evidence of government efforts to support private sector or NGO data reuse.
- (No, Partially, Yes)
- There is evidence of government efforts to support crowdsourced data reuse.
- (No, Partially, Yes)
- There is evidence of government efforts to support data reuse from various data topics.
- (No, Partially, Yes)
User groups:
- There is evidence of government efforts to support data reuse by civil society organizations.
- (No, Partially, Yes)
- There is evidence of government efforts to support data reuse by media.
- (No, Partially, Yes)
- There is evidence of government efforts to support data reuse by scholars and academic institutions.
- (No, Partially, Yes)
- There is evidence of government efforts to support data reuse by the private sector.
- (No, Partially, Yes)
Specific features:
- Government support for data reuse involves data challenges.
- (No, Partially, Yes)
- Government support for data reuse involves hackathons.
- (No, Partially, Yes)
- Government support for data reuse involves communication and community building efforts.
- (No, Partially, Yes)
- Government support for data reuse involves running information sessions on how to use particular datasets, or how to reuse government data in general.
- (No, Partially, Yes)
- Government support for data reuse involves the release of funding schemes.
- (No, Partially, Yes)
Extent
-
How comprehensive, in terms of jurisdiction, is the coverage of the support assessed for this question?
- Support is given in one or more localities, but there are many other localities without such support, or with support of a lesser quality.
- Support is given in one or more localities and is a representative example of the kind of support that can be found for all, or most, localities.
- Support assessed is at national level.
To what extent do city, regional, and local governments have the capability to effectively manage data?
Existence
-
To what extent do city, regional, and local governments have the capability to effectively manage data?
- There is no evidence of capability to effectively manage data.
- There is evidence of limited or ad-hoc capability to effectively manage data.
- There is evidence of sustained and institutionalized capability to manage data.
Elements
Kinds of capacities:
- There is evidence of local governments having open data initiatives.
- (No, Partially, Yes)
- There is evidence of local governments having current open data policies in place.
- (No, Partially, Yes)
- There is evidence of local governments having rules and or guidance in place to provide a comprehensive framework for data sharing.
- (No, Partially, Yes)
- There is evidence of local governments having rules and or guidance in place for consistent data management and publication.
- (No, Partially, Yes)
- There is evidence of local governments providing training to civil servants on data literacy and skills.
- (No, Partially, Yes)
- There is evidence of local governments providing support for data reuse.
- (No, Partially, Yes)
Extent
-
How widespread are local capacities to effectively manage data?
- No cities or regions show capacity to effectively manage data.
- The examples given are exceptions: the majority of cities and regions do not have the capacity to effectively manage data.
- The examples given represent common practice: many cities or regions have comparable capacity to effectively manage data.
Explore other modules
Core modules
Thematic modules
Capabilities secondary indicators
Capability (C): Data institutions
Source
World Bank – DGSS dataset: https://datacatalog.worldbank.org/dataset/digital-governmentgovtech-systems-and-services-dgss-dataset
Questions:
-Is there a government entity in charge of data governance or data management?
-Is there a data protection authority?
Data transformation by GDB
-Normalize values to 0-1 scale
-Replace missing values with subregional mean
-Combine metrics (avg)
-Match countries
Capability (C): Government online services
Source
UN eGov Online Service Index (2020)
Data transformation by GDB
-Match countries
-Replace missing values with subregional mean
Capability (C): Use of standards and methods in statistic offices
Source
Statistical Performance Indicators: https://datanalytics.worldbank.org/SPI/
Dimension 5.2: Standards and Methods
Data transformation by GDB
-Replace missing values with subregional mean
-Match countries
Capability (C): Digital Government
Source
World Bank – DGSS dataset: https://datacatalog.worldbank.org/dataset/digital-governmentgovtech-systems-and-services-dgss-dataset
Questions:
-Is there a DG/GovTech Strategy?
-Is there a dedicated GovTech institution
-Is there a national strategy on disruptive technologies?
-Is there a government cloud (shared platform)?
-Is there a government service bus / interoperability platform in place?
Data transformation by GDB
-Normalize values of 5 metrics to 0-1 scale
-Combine metrics (avg)
-Replace missing values with subregional mean
-Match countries
Capability (C): Digital skills
Source
WE Forum: http://reports.weforum.org/global-competitiveness-report-2019/executive-summary-2/
Digital skills among active population (score)
Data transformation by GDB
-Normalize into 0-1 scale
-Replace missing values with subregional mean
-Match countries
Capability (C): Knowledge-intensive employment
Source
Global Innovation Index: https://www.globalinnovationindex.org/analysis-indicator
ILO: https://www.ilo.org/shinyapps/bulkexplorer55/?lang=en&segment=indicator&id=EMP_TEMP_SEX_OCU_NB_A
Employment in knowledge-intensive occupations (% of workforce)
Data transformation by GDB
-Normalize 0-100 scale to 0-1 scale
-Replace missing values with subregional mean
-Match countries
Capability (C): Human capital
Source
UN E-Government Survey: https://publicadministration.un.org/egovkb/Portals/egovkb/Documents/un/2020-Survey/2020%20UN%20E-Government%20Survey%20(Full%20Report).pdf
UN eGov Human Capital Index (2020)
Data transformation by GDB
-Replace missing values with subregional mean
-Match countries
Capability (C): Political freedoms and civil liberties
Source
Freedom House: https://freedomhouse.org/report/freedom-world
Data transformation by GDB
-Sum metrics scores
-Normalize values from 0-100 scale to 0-1
-Replace missing values with subregional mean
-Match countries
Capability (C): Internet access
Source
ITU: https://www.itu.int/en/ITU-D/Statistics/Pages/publications/wtid.aspx
Metrics used:
-Fixed broadband basket as a % of GNI p.c.
-Individuals using the Internet, total (%)
Data transformation by GDB
-Replace outliers
-Normalize values into 0-1 range
-Match countries
-Replace missing values with last available data from period 2016-2020, if no date with subregional mean
-Compute metric as average of normalized values
Capability (C): Business use of digital tools
Data transformation by GDB
-Rescale data from 0-100 to 0-1 range
-Match countries
-Replace missing values with subregional mean.