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The challenges of open data: 
emerging technology to 
support learner journeys 
Graham Attwell, Pontydysgu 
Jenny Bimrose, IER University of 
Warwick 
PONTYDYSGU
LMI to support learner journeys 
What LMI do learners need? 
What do careers practitioners 
need to know? 
Where can relevant LMI be 
found? 
How do we know it’s high quality? 
Is LMI fit for purpose?
LMI for All 
To develop a careers LMI data tool that supports 
individuals make better decisions about learning 
and work 
 requiring access to, and use of, core national 
data sources
Funded by: 
Developed by consortia: 
PONTYDYSGU
Objectives 
 IDENTIFY: robust sources of LMI to inform 
decisions about learning and work 
 COLLATE: sources in an automated, single, 
accessible location for careers 
 FACILITATE: easy use of LMI data in conjunction 
with other data sources 
 EVALUATE: relevance of the data tool with key 
stakeholders
Process of developing the LMI database 
 Create a repository of careers labour market 
information 
 Take lessons learnt from pilot 
 Assess data sources in terms of usefulness for careers 
and accessibility 
 Link up data sources using a common structure 
 Test out database during hack and modding days 
 To open data up for multiple interfaces for a range of 
users
Process of development: Dynamic/Iterative 
Data 
Accessibility & Open Data 
Stakeholders & Communication
Overview of data sources 
 Office for National Statistics – ASHE, LFS, Census of 
Population, BRES 
 UKCES – Working Futures and ESS data 
 BIS, DfE, & other bodies – access to data on 
education and training courses 
 DWP - access to detailed data on vacancies by 
occupation 
 Devolved nations – statistical agencies 
 Eurostat, Cedefop, etc. – access to European data 
 Other data providers
Overview of data and indicators 
 Employment: historical, projected and replacement 
demand (Working Futures based on LFS, BRES) 
 Pay and earnings (estimates based on ASHE and LFS) 
 Hours (ASHE) 
 Unemployment rates (LFS) 
 Number of vacancies (ESS) 
 Occupational descriptions (ONS) 
 Skills, abilities and interests (O*NET) 
 Current vacancies (fuzzy search) 
 Higher education destinations (HESA)
Employment levels 
by occupation 
How many jobs are there? How many 
in my area? What are the past trends? 
What are likely future trends? 
Labour Force 
Survey, Working 
Futures 
Average earnings 
by occupation 
How much do people get paid for this 
job? How much at the start of their 
career? How much in my area? 
Annual Survey of 
Hours and 
Earnings 
Unemployment by 
occupation 
What proportion of people in this 
occupation are currently out of work? 
Annual Population 
Survey 
Profile of 
qualification level 
by occupation 
What level of qualification do people 
have in this job and what am I likely to 
need? 
Labour Force 
Survey, Working 
Futures 
Vacancies by 
occupation 
How many vacancies are there for this 
job? What proportion are hard to fill? 
Employer Skills 
Survey 
The data big questions…
Challenges in linking LMI sources 
 Data from range of sources 
 Classification and descriptions of occupations – 
use of SOC 
 Use of Annual Survey of Hours and Earnings 
data 
 Local data and sample sizes 
 Forecasting data from Working Futures 
 Access to job vacancy and skills data 
 Need for education and skills opportunities 
data
Emerging technology 
 Open and linked data 
 Supporting multiple platforms and devices 
 Developing data cubes 
 Automatic data upload (ETS) 
 Facilitating and supporting third party 
developers (API) 
 Confidentiality and non disclosure
Lessons learned 
 Technology challenges: interfaces and tools 
for updating data; developing a data cube; 
support for mobile devices 
 Data challenges: various data sets; 
occupational classifications and descriptions; 
standardisation of data from different data 
sets; local data; sample sizes; future trends; 
vacancy data; education and training 
opportunities; exploitation of US O*NET
Tour of the api…
Over to you… 
Work on your own or in groups: 
 Explore the api http://api.lmiforall.org.uk/ 
 Draw up some possibilities for app or web 
developments using the LMI for All database 
Approximately 20 minutes
Things to consider… 
 What ‘big questions’ are you 
trying to answer? 
 Apps to address different 
audiences, their learning 
styles and data needs 
 What about data mashing? 
 Potential to use on different 
devices
The big challenges ahead…
Early developments… 
 Access has now been provided to selected 
developers 
 Purpose – to understand what creative 
applications will emerge 
 Two interfaces from early adopters are 
publicly available, others are working towards 
launch
New services for education and training?
Can be used along side other, qualitative 
information… for example, icould 
2 
1 
Data alongside career videos to encourage and 
inspire young people to think broadly about their 
careers. 
http://icould.com/
…For a wide range of 
audiences…for example, RCU data 
dashboard 
A summary 
dashboard 
presenting 
information on the 
current and future 
employment 
demand for UK 
occupations to link 
LMI to a 
curriculum 
strategy. 
http://rcultd.co.uk/wf/
…In a variety of contexts…for example, 
Career Trax 
Temporary 
extension 
shows Career 
Trax 
embedded in 
the 
‘Right Move’ 
website. 
http://career-trax.herokuapp.com
Next steps 
 Integration of more data, including: 
Short-term - Course data; Job vacancy data 
Long-term - More on skills & abilities 
(O*NET); European data 
 Modding day to develop marketable apps 
 Implementation of data cubes
How to get involved? 
Find out more 
http://www.lmiforall.org.uk/ 
Follow us on Twitter @lmiforall 
Become an early adopter 
Stay in contact! 
Final launch early summer 2015
For more information… 
Email: 
Jenny.Bimrose@warwick.ac.uk 
Peter.Glover@ukces.org.uk 
Further information: 
http://www.lmiforall.org.uk/ 
http://api.lmiforall.org.uk/

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The challenges of open data: emerging technology to support learner journeys

  • 1. The challenges of open data: emerging technology to support learner journeys Graham Attwell, Pontydysgu Jenny Bimrose, IER University of Warwick PONTYDYSGU
  • 2. LMI to support learner journeys What LMI do learners need? What do careers practitioners need to know? Where can relevant LMI be found? How do we know it’s high quality? Is LMI fit for purpose?
  • 3. LMI for All To develop a careers LMI data tool that supports individuals make better decisions about learning and work  requiring access to, and use of, core national data sources
  • 4. Funded by: Developed by consortia: PONTYDYSGU
  • 5. Objectives  IDENTIFY: robust sources of LMI to inform decisions about learning and work  COLLATE: sources in an automated, single, accessible location for careers  FACILITATE: easy use of LMI data in conjunction with other data sources  EVALUATE: relevance of the data tool with key stakeholders
  • 6.
  • 7. Process of developing the LMI database  Create a repository of careers labour market information  Take lessons learnt from pilot  Assess data sources in terms of usefulness for careers and accessibility  Link up data sources using a common structure  Test out database during hack and modding days  To open data up for multiple interfaces for a range of users
  • 8. Process of development: Dynamic/Iterative Data Accessibility & Open Data Stakeholders & Communication
  • 9. Overview of data sources  Office for National Statistics – ASHE, LFS, Census of Population, BRES  UKCES – Working Futures and ESS data  BIS, DfE, & other bodies – access to data on education and training courses  DWP - access to detailed data on vacancies by occupation  Devolved nations – statistical agencies  Eurostat, Cedefop, etc. – access to European data  Other data providers
  • 10. Overview of data and indicators  Employment: historical, projected and replacement demand (Working Futures based on LFS, BRES)  Pay and earnings (estimates based on ASHE and LFS)  Hours (ASHE)  Unemployment rates (LFS)  Number of vacancies (ESS)  Occupational descriptions (ONS)  Skills, abilities and interests (O*NET)  Current vacancies (fuzzy search)  Higher education destinations (HESA)
  • 11. Employment levels by occupation How many jobs are there? How many in my area? What are the past trends? What are likely future trends? Labour Force Survey, Working Futures Average earnings by occupation How much do people get paid for this job? How much at the start of their career? How much in my area? Annual Survey of Hours and Earnings Unemployment by occupation What proportion of people in this occupation are currently out of work? Annual Population Survey Profile of qualification level by occupation What level of qualification do people have in this job and what am I likely to need? Labour Force Survey, Working Futures Vacancies by occupation How many vacancies are there for this job? What proportion are hard to fill? Employer Skills Survey The data big questions…
  • 12. Challenges in linking LMI sources  Data from range of sources  Classification and descriptions of occupations – use of SOC  Use of Annual Survey of Hours and Earnings data  Local data and sample sizes  Forecasting data from Working Futures  Access to job vacancy and skills data  Need for education and skills opportunities data
  • 13. Emerging technology  Open and linked data  Supporting multiple platforms and devices  Developing data cubes  Automatic data upload (ETS)  Facilitating and supporting third party developers (API)  Confidentiality and non disclosure
  • 14. Lessons learned  Technology challenges: interfaces and tools for updating data; developing a data cube; support for mobile devices  Data challenges: various data sets; occupational classifications and descriptions; standardisation of data from different data sets; local data; sample sizes; future trends; vacancy data; education and training opportunities; exploitation of US O*NET
  • 15. Tour of the api…
  • 16. Over to you… Work on your own or in groups:  Explore the api http://api.lmiforall.org.uk/  Draw up some possibilities for app or web developments using the LMI for All database Approximately 20 minutes
  • 17. Things to consider…  What ‘big questions’ are you trying to answer?  Apps to address different audiences, their learning styles and data needs  What about data mashing?  Potential to use on different devices
  • 18. The big challenges ahead…
  • 19. Early developments…  Access has now been provided to selected developers  Purpose – to understand what creative applications will emerge  Two interfaces from early adopters are publicly available, others are working towards launch
  • 20. New services for education and training?
  • 21. Can be used along side other, qualitative information… for example, icould 2 1 Data alongside career videos to encourage and inspire young people to think broadly about their careers. http://icould.com/
  • 22. …For a wide range of audiences…for example, RCU data dashboard A summary dashboard presenting information on the current and future employment demand for UK occupations to link LMI to a curriculum strategy. http://rcultd.co.uk/wf/
  • 23. …In a variety of contexts…for example, Career Trax Temporary extension shows Career Trax embedded in the ‘Right Move’ website. http://career-trax.herokuapp.com
  • 24. Next steps  Integration of more data, including: Short-term - Course data; Job vacancy data Long-term - More on skills & abilities (O*NET); European data  Modding day to develop marketable apps  Implementation of data cubes
  • 25. How to get involved? Find out more http://www.lmiforall.org.uk/ Follow us on Twitter @lmiforall Become an early adopter Stay in contact! Final launch early summer 2015
  • 26. For more information… Email: Jenny.Bimrose@warwick.ac.uk Peter.Glover@ukces.org.uk Further information: http://www.lmiforall.org.uk/ http://api.lmiforall.org.uk/

Editor's Notes

  1. People make important decisions about their participation in the labour market every year. This extends from pupils in schools, to students in Further and Higher education institutions and individuals at every stage of their career and learning journeys. Whether these individuals are in transition from education and/or training, in employment and wishing to up-skill, re-skill or change their career, or whether they are outside the labour market wishing to re-enter, high quality and impartial labour market information (LMI) is crucial to effective career decision-making. LMI is at the heart of UK Government reforms of careers service provision. Linking and opening up careers focussed LMI to optimise access to, and use of, core national data sources is one approach to improving that provision as well as supporting the Open Data policy agenda (see HM Government, 2012). Careers focussed LMI can be used to support people make better decisions about learning and work and improve the efficiency of labour markets by helping match supply with demand, and helping institutions in planning future course provision. Setting the scene in the UK Shifting policy: Resources – operating within financial constraints and cutbacks, need to provide cost-effective services Political priorities – in England, move away from offering separate services for YP and adults, new national careers services – delivering models – integrating technology into all aspects of CEIAG practice is seen as a way to extending services and increasing access by offer flexibility in the way services are delivered, but also help in reducing costs by reducing demand for F2F services Context: Increasing use of technology by young people to seek out careers information and learn – more than half of young people in a recent government survey reported that they use the internet to learn Web 3.0 offers new ways of delivering personalised content to individual users New demands and expectations on CEIAG services by young people – digital natives – young people want access to online, interactive information Current evidence: there is more research of technology use in practice Challenge of keeping up-to-date with technology as it changes so fast – digital immigrants have harder time in keeping skills up-to-date Inconsistent terminology – ‘e-guidance’, ‘web-based guidance’ and ‘internet based guidance’, used interchangeably; need to define what these comprise (i.e. email, online chat, telephone, CAG etc.) ‘A greater integration of new information and communication technologies (ICT) in careers practice on a UK- wide basis is being mediated by changes occurring within public, private and community sectors’ Ref: Bimrose et al., 2011, p. v
  2. The UK Commission is bringing existing data sources together, such as from some of our key national surveys, to make high quality LMI more accessible to support individuals and businesses to make better and more informed decisions about careers and learning options Potential sources that could add value: ASHE National Employer Skills Survey (NESS)
  3. LFS Labour Force Survey ASHE Annual Survey of Hours and Earnings BRES Business Register and Employment Survey ESS Employer Skills Survey
  4. HANDOUT on LMI for All dataoverview LFS Labour Force Survey ASHE Annual Survey of Hours and Earnings BRES Business Register and Employment Survey ESS Employer Skills Survey