Training, Competencies and Capacity Development

Task Team of the UN Committee of Experts on Big Data and Data Science for Official Statistics

Introduction

The statistical community has the obligation of exploring the use of new data sources, such as Big Data, to meet the expectation of the society for enhanced products and improved and more efficient ways of working. Big Data could also support the monitoring of the Sustainable Development Goals by improving timeliness and relevance of indicators. This should go without compromising their impartiality and methodological soundness.

Big Data is by definition different from traditional data sources currently used by National Statistical Systems (NSSs) requiring the development of new methodologies. Big Data sources pose challenges regarding methodology, quality assurance, technology, security, privacy and legal matters. This means that new skill sets are necessary. Some of which could be hired temporarily, others will need to become an integral part of the institution. It is up to the senior management to decide what will be done by the institute itself and what will be outsourced. Most likely, the statistical institute will need to build long-term partnerships with private sector, academia and research institutes to successfully work with new data sources and new technologies.

An additional complication is that there is not just one kind of Big Data source, and each kind of Big Data may have different requirements as far as new skill sets and new partnerships are concerned. We therefore need to develop methods and tools to identify and assess the needs for new skills.

The Task Team on Training, Competencies and Capacity Development is building on the outcomes of the work of its predecessor, while bringing in the requirements of new competencies and new skill sets for the staff of national statistical systems.

Objectives

The general objectives of this task team are to:

  1. Develop methods and tools (including coordination and facilitation) for
    1. a baseline need identification of "Big Data" skills in NSSs; and
    2. an assessment of institutional readiness of NSSs in using Big Data
  2. Build a competency framework for the Big data acquisition and processing in the current data landscape of NSSs;
  3. Identify and analyze the existing supply of training of data scientists in academic and other centers;
  4. Facilitate establishing a global network of institutions for training and capacity building on Big Data in official statistics, under the umbrella of the UN-CEBD;
  5. Review of experiences and lessons learned from different organizational structures and data science governance across national statistical systems;
  6. Provide guidance on the development of a training program that addresses the gaps and mismatches identified in the competencies analysis [as defined in points (a)-(c)].
  7. Coordinate training plans in line with the Global Survey on Big Data for Official Statistics and other outcomes from tasks teams formulated within the UN-CEBD or other relevant stakeholders.

In its work, the Task Team will review available works on human resources, skills and capabilities prepared by other international bodies, such as, for example the ESS Resources Directors Group Task Force on Skill Gaps or the work done by UNECE High-Level Group for the Modernization of Official Statistics.

Deliverables

  • Overarching Big Data Training Curriculum
  • Big Data Training Catalogue (with updates)
  • Guidance for developing online training courses
  • Big data e-learning courses (in cooperation with other task teams or stand-alone)
  • Online version UN Big Data Maturity Matrix V.1.0
  • Concept of UN Big Data Maturity Matrix V.2.0
  • Governance structures for all Regional Hubs
  • Webinar programmes for all Regional Hubs
  • Communication plans for all Regional Hubs

Subgroups of the Big Data Task Team on Training, Competencies and Capacity Development

This subgroup has already developed a set of guidance materials (primarily for other task teams) for the development of training materials and training courses, including model curricula, addressing needs assessments based on existing tools, and requirements for course development at different levels (awareness, beginner, practitioner).

The subgroup will continue to provide guidance, support and training for other task teams (where required) on how to set learning objectives at the different curriculum levels and sharing good practice in course design.

The subgroup will do reviews of e-learning courses before their deployment and will actively support their deployment on the LMS.

The already developed overarching Big Data Training Curriculum will be reviewed to ensure it meets emerging needs.

The catalogue was established in 2022 and outlines relevant training courses and other materials for big data work and provides links to the available resources. The catalogue needs to be maintained - in terms of verifying existing information and adding new courses/materials that become available. Such reviews/updates are expected twice a year (March, September).

The matrix will be made available to countries in a stand-alone format for self-assessments. In these self-assessments, NSOs can identify their stage of development along detailed components/dimensions of the use of big data, such as legal framework, IT infrastructure, human resources and big data applications in the production of statistics, generating an overall picture.

Work in 2023 will focus on (a) review of underlying concepts of the maturity matrix, (b) developing a pool of resources (using the list of resources from the Big Data Training catalogue as a starting point, but adding other types of resources by identifying and communicating with additional partners), and (c) review and improve the functioning of the existing draft application, including technical issues.

A future version 2.0 could provide a higher granularity of questions/evaluation criteria and improved linking to existing training courses in the extended catalogue list.

The LMS is available to all task teams to host their online training programmes and uses the UN Global Platform to provide access to all countries. Courses hosted are typically developed by different task teams, but go through a review process by subgroup A of our task team before being posted.

The work of this subgroup in 2023 will focus primarily on technical support for the LMS, such as programming issues. The overall work is expected to be limited.

(Note that the LMS also hosts UNSD courses on statistics issues not related to big data.)

This subgroup will work with the existing (and future) Regional hubs. This work will include support on different aspects, depending on the current stage of development of the hubs, such as: (a) identifying relevant objectives for the hubs, (b) establishing functioning management structures of the hubs, (c) identifying project, skill and training needs, (d) developing and prioritizing work programmes, (e) managing inclusion of a wider range of countries in their respective regions in project development work and knowledge exchange, (f) communication and knowledge exchange among the different hubs, and g) developing and delivering communication plans.

Recent Events

6th International Conference on Big Data

Session 10 - Training in use of new data sources and new technologies - Sep 2020

Task Team members

Countries

  • Brazil (IBGE)
  • Canada (Canada School of Public Service)
  • Canada (Statistical Society of Canada, SSC)
  • Canada (Statistics Canada)
  • Chile (INE)
  • Denmark (Statistics Denmark)
  • India (Indian School of Business)
  • Indonesia (Statistics Indonesia, BPS)
  • Mexico (INEGI)
  • Poland (Statistics Poland)
  • United Arab Emirates (Statistics Centre Abu Dhabi)
  • United Kingdom (Office for National Statistics, ONS)
  • United States (Census Bureau)

International Institutions

  • AfDB
  • GCC-STAT
  • ITU
  • PARIS21
  • SIAP
  • UNECE
  • UNITAR
  • UNSD