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Tracking data

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Presentation 'tracking and recognising data as research outputs in their own right by Victoria Moody, Jisc

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Victoria Moody, UK Data Service Co-I, deputy director, director of impact
Part of Jisc research strategy leadership team
18 October 2019
Tracking and recognising data as research
outputs in their own right
What we’re covering
1. If we have sustainable, FAIR data we can re-use them (and reproduce
findings)
2. If we don’t have sustainable, FAIR data we can’t re-use them (and
reproduce findings)
3. Opportunities
• Expand/ industrialise the ecosystem (with tech and policy?)
• Use the tools we have and apply them to ‘unsustainable’ data (where we
can)
• Get the right mix – for sustainable data and mechanisms to reproduce
effectively for ‘unsustainable’ data (or make it differently sustainable)
• Skill share and skill well
1. If we have sustainable, FAIR data we can re-use them
(and reproduce findings)
4
http://dx.doi.org/10.5257/iea/web/2018-10
Growing the corpora of standards to meet the mandate
and requirements for reproducibility:

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Tracking data

  • 1. Victoria Moody, UK Data Service Co-I, deputy director, director of impact Part of Jisc research strategy leadership team 18 October 2019 Tracking and recognising data as research outputs in their own right
  • 2. What we’re covering 1. If we have sustainable, FAIR data we can re-use them (and reproduce findings) 2. If we don’t have sustainable, FAIR data we can’t re-use them (and reproduce findings) 3. Opportunities • Expand/ industrialise the ecosystem (with tech and policy?) • Use the tools we have and apply them to ‘unsustainable’ data (where we can) • Get the right mix – for sustainable data and mechanisms to reproduce effectively for ‘unsustainable’ data (or make it differently sustainable) • Skill share and skill well
  • 3. 1. If we have sustainable, FAIR data we can re-use them (and reproduce findings)
  • 4. 4
  • 6. Growing the corpora of standards to meet the mandate and requirements for reproducibility:
  • 7. 2. If we don’t have sustainable, FAIR data we can’t re-use them (and reproduce findings)
  • 9. “….notions of value are often woven into the uses and understandings of data as well as the visions and promises that are attached to them. This makes data a routine and structurally significant part of the ordering of the social world…” The Data Gaze, David Beer https://doi.org/10.1080/1369118X.2019.1609544
  • 11. 3. Opportunities? Use the tools we have and apply them to what we don’t (where we can) Industrialise and expand the ecosystem (with tech and policy?) Get the right mix – for sustainable FAIR data and mechanisms to reproduce effectively for unsustainable data (or make it sustainable) Skill well and skill share
  • 16. Considerations • Drive to OA extending to data • Meta-standards = ethical outcomes • FAIR codebooks/ syntax libraries • Support a transition from idiosyncratic approaches • Intelligent metadata models • Skill sharing to manage new approaches/ vastness • Skill well…

Editor's Notes

  1. The Lancet Countdown is a unique research collaboration between 24 international academic institutions and inter-governmental organisations. It monitors progress on the relationships between health and climate change, and their implications for national governments.  The Lancet Countdown reports annually, making recommendations for activity to mitigate climate change. It aims to raise climate change as a public health emergency in the political sphere – observationally, it’s beginning to work – but is it causal or correlative?
  2. The Cross-Linguistic Data Formats initiative proposes new standards for two basic types of data in historical and typological language comparison. The aim is to create monolingual resources1 for the world’s biggest languages, but also in form of cross-linguistic datasets which try to cover as many of the world’s languages as possible… Due to idiosyncratic formats, linguistic datasets also often lack interoperability and are therefore not reusable.
  3. Much of the last decade of political and policy debate on poverty has focussed on whether and how we should measure poverty, rather than the action needed to drive better outcomes for the most disadvantaged in our society. If this is to change, developing a metric was not enough; we also need to be able to use it to build a new consensus around poverty measurement and action in the UK. The Commission will base its measurement approach on data from the Family Resources Survey (for poverty and poverty depth) and Understanding Society (for poverty persistence). A combination of these data sources will be used to report on Lived Experience Indicators. Here is a DO file in Stata I’ve extracted to show the syntax code for reproducing the analysis.
  4. Aim: to design and describe processes and methodologies for creating sufficient metadata/trace data from ubiquitous multiple sensors for data identification and verification, obviating the need for data ingesting and archiving processes. Suitable algorithms and APIs to be developed as part of the demonstrator project to enable the creation of intelligent metadata/trace data to be used within newly designed verification citation methods.
  5. “His revelations exposing the rampant misuse of data rocked Silicon Valley and forced numerous Fortune 500 companies to overhaul cybersecurity and user privacy practices.”