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FutureTDM Symposium: Skills & Education

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Kiera McNeice presents the TDM skills and education gap and the need for strategic thinking

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FutureTDM Symposium: Skills & Education

  1. 1. OpenDataMonitor Horizon 2020 Coordination and Support Action GARRI-3-2014 Scientific Information in the Digital Age: Text and Data Mining (TDM) Project number: 665940 Skills and Education: The Need for Strategic Thinking FutureTDM Reducing Barriers and Increasing Uptake of Text and Data Mining for Research Environments using a Collaborative Knowledge and Open Information Approach Kiera McNeice FutureTDM Symposium, Salzburg June 13th, 2017
  2. 2. Barriers to TDM Split into four categories: ▪ Economics and incentives ▪ Legal and policy ▪ Technical and infrastructure ▪ Education and skills 2FutureTDM
  3. 3. TDM Skills and Education 3
  4. 4. Skills in use of TDM tools Barriers to entry still high ▪ Use of TDM tools requires programming knowledge Skills gaps between TDM experts and domain experts ▪ 64% of Chief Data Officers come from IT/data backgrounds5 Skills gaps between academia and industry ▪ Graduates’ skillsets “do not match TDM needs” Hiring experts can be prohibitively expensive FutureTDM 4 5. Dawn of the CDO
  5. 5. FutureTDM recommendations ▪ Ensure everyone working with data has access to education, information, and experts to consult about TDM ▪ Universities and libraries establish information hubs where researchers and citizen scientists can access TDM training, resources, and advice ▪ Ensure education prepares TDM practitioners for the diversity of TDM tools and applications ▪ Promote exchanges of skills and knowledge between companies and universities FutureTDM 5
  6. 6. Broader Skills and Awareness 6
  7. 7. Education, skills, awareness Broader skills and awareness needed ▪ Awareness of benefits of TDM ▪ Basic data literacy across all sectors ▪ Data analytical skills ▪ TDM research and development ▪ Turning TDM results into business insights “More than ten million adults in England lack the basic digital skills they need.”1 7FutureTDM 1. Department for Culture, Media & Sport, The Rt Hon Karen Bradley MP
  8. 8. Why support TDM skills? “Data science is the new IT.” ▪ Data analytics skills will be crucial to the next generation of researchers ▪ TDM can make research more effective and efficient ▪ Potential value to all research fields and sectors of the economy FutureTDM 8
  9. 9. TDM is relevant to all sectors 9FutureTDM
  10. 10. In practice: Varies across sectors, limited spread of awareness “I had never heard of TDM until I moved to the publishing industry.” -- Former social science researcher “Fewer than one in 20 researchers are carrying out any kind of TDM in this domain.” -- Research statistician FutureTDM 10
  11. 11. Lack of data analysis skills In a survey3 of 461 data management professionals: ▪ 38% of organisations do not handle any big data ▪ 40% cite inadequate staffing or skills to do so ▪ 61% say better big data management is needed to improve their data analytics In a survey4 of 125 ICT decision-makers: ▪ 66% lack skills to implement big data technologies ▪ 69% lack skills to capitalise on collected data 11FutureTDM 3. TDWI Best Practices Report: Managing Big Data 4. Trends vs Technologies: A research report from Capita in partnership with Cisco
  12. 12. Poor understanding of what TDM can do “Customers don’t know what they want – it’s like trying to sell cool bicycles when there are no roads.” FutureTDM 12
  13. 13. FutureTDM recommendations ▪ Establish training and courses in data literacy and “computational thinking” early in the educational system and in lifelong learning ▪ Integrate education about core principles of data management and analysis across all subject areas, not just traditionally quantitative fields ▪ Encourage cross-discipline and cross-sector sharing of skills, knowledge and best practices ▪ Provide evidence of the benefits of TDM to encourage investment in and development of TDM skills FutureTDM 13
  14. 14. The Role of Universities 14
  15. 15. The role of universities Involved in all steps of the TDM value chain ▪ Content creation (research data, papers, etc.) ▪ Content dissemination (via repositories, licensing) ▪ TDM activities (dedicated departments, broader programmes) ▪ Value creation (deriving new knowledge and insights from TDM) Need better awareness and education across all steps FutureTDM 15
  16. 16. The role of research libraries Natural candidates to coordinate support for TDM ▪ Already undertake a variety of research-supporting activities ▪ Several of these are already relevant to TDM (e.g. data management, open access) ▪ Already coordinate support across different university departments (e.g. legal, financial) ▪ Can mediate and facilitate sharing of knowledge across different domains, bridging gaps FutureTDM 16
  17. 17. Need for strategic, coordinated approaches Relying on ad hoc interpersonal networks limits sharing of skills, knowledge, best practices ▪ Universities are large networks with complex hierarchies ▪ Wide variety of stakeholders with different needs ▪ Need for dedicated staff time/resources, supported by policy 17
  18. 18. What Can Universities Do? 18
  19. 19. What can universities do? Demonstrate need ▪ Ghent University: Surveys and interviews identified data management and data science as key skills to develop and support Involve all stakeholders ▪ Ensure buy-in from researchers, research faculty, education faculty, IT, other specialized departments… Understand internal processes ▪ Know how educational courses are structured, and how departments communicate, to work with existing processes FutureTDM 19
  20. 20. What can universities do? Consolidate information and resources ▪ Bringing together fragmented knowledge from different departments and sectors helps everyone share best practices Identify early adopters and promoters ▪ Particularly domain experts with personal interest in supporting TDM and other data-related practices Introduce incentives ▪ Talk to stakeholders to understand what would benefit them – incentives may not need to be financial! Coordinate with industry ▪ Ensure people are learning relevant skills and techniques FutureTDM 20
  21. 21. What can universities everyone do? Share success stories! ▪ …of integrating TDM awareness into curricula ▪ …of implementing support for TDM and other data-related activities ▪ …of solving TDM-related skills or infrastructure problems ▪ …of exciting applications of TDM tools and technologies FutureTDM 21

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