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Principles and key responsibilities in RI, RDM, RIAs and their intersection

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Dr Paul Taylor presented at the Adelaide Research Integrity Advisors Data Management Workshop on 16 June 2017.

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Principles and key responsibilities in RI, RDM, RIAs and their intersection

  1. 1. RIA Research Data Management Workshop Principles and key responsibilities in RI, RDM, RIAs and their intersection Dr Paul Taylor Dr Daniel Barr Director, RIGS Manager – Integrity, Ethics, Biosafety RMIT University Deakin University
  2. 2. “Research is the systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions” Oxford English Dictionary Online http://madamepickwickartblog.com/wp-content/uploads/2010/07/python2.jpg The research process is made up of non-linear steps and shifts
  3. 3. ( ) • Safe and ~100% effective vaccines • Reduction of precancer within 3 years of introduction • Accumulation of non-linear steps • A complex equation of research impact = Research always has impact
  4. 4. RHF joins SUEED to work on Mills Cross Collaboration with Bernie Mills commenced - RHF joins group - also works with Hanbury Brown Johns Perry Sydney Engineering etc Dave McGrath joins RP Dave Skellern joins Macquarie as Prof of Electronics Neil Weste recruited to Macquarie JA joins RP to run GaAs Prog License for technologies Radiata formed by Dave , Neil and Terry JOS joins RP to run SP Prog Chin Kwong leaves to start company Paul Jackson completes PhD Graham Daniels moves as well Chris Joins SUEED Looks for Big Project to provide PG training Bernie Mills joins SU Physics - gets US funding Graham Daniels joins CSIRO TP Joins RP Work started on FST DNC and Geoff Poulton move to new program RHF completes PhD - joins FST project and academic staff and supervises students Join O'Sullivan joins News Ltd then Radiata RHF Joins RP with plan for rebuilding RP 1980 Australia Telescope Proposal and funding CSIRO VLSI Program Craig Mudge Signal Processing Antennas Microwave circuits and GaAs Program AT Antenna Design under DNC - Asst Chief - ex Interscan OTC Antennas Gnangarra and Vietnam $100M estimated return to Australia (Peter Meulman) Jon Ables Correlator Chip Development Warwick Wilson develops correlator Australia Telescope VLSI Design capability from VLSI program FFT Chip Design FFT Chip John O'Sullivan IR&D funding Dave McGrath and Brian Connolly start Lake DSP $30 M Cap A4 Chip for audio applications Accusound Loudspeakers IEEE Standard Funding for collab program with RP through Macquarie JRC RADIATA gets START funding and Develops chip AUSTEK Microsystems Fleurs Given to SUEED Development of FST as basis for EE PhD projects Mills Cross commenced Chris involves Ron Aitchison, Cyril Murray an Ian Docherty in new projects Summit Systems Datamax Dave Skellern completes PhD - sets up Comms Lab at SUEED - establishes collaborations with HP etc John O'Sullivan completes PhD and goes to Holland JDOS' PLANS Program - FFT techniques in Wireless Networks CSIRO Div of Radiophysics circa 1960 RHF AWA, OTC, Ducon Radiata demonstrates chip - bought out by CISCO $600M Aussat Antennas Galaxy antennas etc Multibeam antennas Radiata builds up staffing Neil Weste completes PhD in Adelaide and goes to USA to Bell Labs, Symbolics then TLW Neil Weste writes now classic book on CMOS design with KE Transconductance Multiplier Exicom 38 GHz links A Cosmic Genealogy 1991 strategy meeting John Archer completes PhD and goes to USA Summit taken over by Datacraft Terry Percival completes PhD, joins AT project then OTC Continuing RA program, refurbishing Parkes + NASA + ESA etc, etc Foundations Strategy Parkes Telescope completed Culgoora Rafioheliograph Interscan Defense contracts Triune startup (failed) Corrugated feed horn - BMT Wireless Lan Patent - O'Sullivan, Percival, Deane, Ostry, Daniels Mead Conway Neil Weste President of Symbolics Radioastronomy Cochlear implant Cat videos on smartphones Allied Forces WWII radar Credit: Dr Bob Frater AO FAA FTSE The impact of research is broad and unpredictable
  5. 5. Research Impact • Hammond, R. A. The proboscis mechanism of Acanthocephalus ranae. J. Exp. Biol. 45, 203–213 (1966). • 22 citations… and then a 23rd.
  6. 6. Long-term, unpredictable Research Impact
  7. 7. Research impact and integrity • Research always has impact • The impact of research is predictably unpredictable • Because of this we must be able to trust research • The principles of research integrity: – make research trustworthy – can make research excellent – underpin the positive impact of research – are the norm
  8. 8. The principles of research integrity are • Honesty, responsibility and accountability in all aspects of research. • Professional courtesy and fairness in working with others. • Good stewardship of research on behalf of others. Adapted from the Singapore Statement on Research Integrity and the Australian Code for the Responsible Conduct of Research
  9. 9. The principles of research integrity are translated into practice by humans (researchers) working in a complex system of expectations and traditions • Morals • Personality • Skills and experience • Cultural background • Discipline • Collaboration • Community • Institution • Funding Source • Publisher
  10. 10. Research integrity / Accepted and responsible research practice Adherence to regulation Working safely Demonstration of respect for participants, animals, environment Rigour and objectivity Research data management Sharing research data Publication and communication of research Citation of the work of others Acknowledgment of contributions to research Authorship Peer review Conflict of interest management Supervision of research trainees Research integrity education and training Accuracy in research proposals Use of research funds Dual use of research Raising concerns about the integrity of research Excellent Conduct Responsible Conduct
  11. 11. Responsible research data management Key responsibilities: • Made, retained, accessible and secured • Shared openly and promptly, once confidentiality, ownership and priority are considered • Communicated honestly and accurately • Appropriately cited and permission for use or reuse is obtained • Clear and accurate records that allow verification or replication by others
  12. 12. Research data and records are the ‘gold’ of research - data in Australian public research is worth at least $1.9b per annum. Source: Houghton J & Gruen N, Open Research Data Report (2014), http://ands.org.au/resource/cost-benefit.html Sharing detailed research data is associated with increased citation rate Source: Piwowar HA, Day RS, Fridsma DB (2007) PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308 Data archiving is a good investment - Investment in data archiving and repositories yields higher return (resultant publications) per $ spent than spending on grant funding Source: Piwowar HA et al (2011) Nature Figure 1. Distribution of 2004–2005 citation counts of 85 trials by data availability. Why does it matter?
  13. 13. Research is a human endeavour. Sometimes researchers make honest mistakes. Sometimes researchers depart from accepted practice and breach the principles of research integrity deliberately, recklessly or negligently.
  14. 14. Increasing Departure Research integrity / Accepted practice Responsible conduct Excellent conduct Questionable Research Practices Breach of research integrity Research Misconduct
  15. 15. Fabrication Responsible conduct Falsification Plagiarism Increasing Departure Research integrity / Accepted practice Excellent conduct Research Misconduct Breach of research integrity
  16. 16. “Our finding suggest that US scientists engage in a range of behaviours extending far beyond falsification, fabrication or plagiarism” Martinson, Anderson & de Vries Nature 2005 435:737-738
  17. 17. Increasing Deviation/Departure/Breach Research integrity / Accepted practice Research Misconduct Inadequate record keeping Changing design/methods in response to a funding source Dropping data points on gut feeling Inadequate design, method, analysis or interpretation Poor reporting of methods Misleading authorship Poor reporting of results Not following ethics approval Same data in two or more publications Responsible conduct Excellent conduct Questionable Research Practices Conflict of interest mismanagement Loss or destruction of data Avoidable failure to follow ethics approvals Falsification Irreproducible research Irresponsible authorship Irresponsible recycling Irreproducible research Irreproducible research
  18. 18. Honest mistakes with research data management Ferric C. Fang, R. Grant Steen, and Arturo Casadevall. Misconduct accounts for the majority of retracted scientific publications. PNAS 2012; doi:10.1073/pnas.1212247109
  19. 19. Research Integrity Advisors • RIAs provide advice to anyone about the responsible conduct of research • RIAs only provide advice RIAs are • One of the best things about the Australian Code, and a requirement of it • Normally senior researchers however what’s more important is that an RIA knows how the principles of research integrity are applied to research practice in their discipline
  20. 20. RIAs and Cultures of Research Integrity • RIAs clarify expectations by providing advice and guidance on governance including the Australian Code • RIAs are a tool for education and training • The presence and promotion of RIAs to the research community of an institution sends a message that research integrity is important
  21. 21. RIAs and Advice about Research Data Management Current topics in data and research integrity • Use of research data management plans for all research • The security of cloud-based storage • Open data and understanding ownership, ethics, confidentiality and priority claims • Use of reporting standards – discipline-based • Post-publication peer review and images in biosciences
  22. 22. RIA Research Data Management Workshop Scenarios
  23. 23. Missing in action… • A student makes an appointment with you to discuss some concerns she has about access to data. • Sarah says that her supervisor, Marie, has left the university and taken all the data with her. • Marie is no longer letting Sarah access the data that Sarah has been using, some of which Sarah collected.
  24. 24. • What advice do you give Sarah? • Who owns research data? • Can it move between institutions? • Is this different in STEM and HASS disciplines (generally speaking)?
  25. 25. Strange access… • A post doc, Geoff, from your department has noticed some strange access records for a shared database that he and his colleagues work on. He makes an appointment to meet with you. • At the meeting, he reveals that the unusual accessions used hi supervisor’s login details. He also claims that some of the raw data has been changed, but that none of this appears on the change log that the research group maintains. • It’s his view that the changes make the results of the research more positive.
  26. 26. • What is your advice to the post doc? • What other considerations cross your mind at this point? • Is there any action you might take now?
  27. 27. “Missing in action 2: the missening” • The pressure is on. A progress review meeting for a large longitudinal survey is next week. Brent needs to complete the initial analyses so that the group has something to present to the Project Board. • Getting access to the computers at work can be hard. Brent loads up a USB stick with the raw data. This hasn’t been de-identified yet, so he includes the key. • Now that he has bought himself some additional time, Brent decides he can stop by the hotel on the way home for a few drinks with the rest of the research group. • You know what happens next…
  28. 28. • Brent comes to see you for advice the next day… • What advice do you give to Brent? • Does anyone else need to be involved in this process? • What needs to happen next? • How might this be prevented in the future?
  29. 29. Authorship… • A student appears in your office doorway… • “I need to talk to you about authorship” • Grace has been workng with Brent on the massive longitudinal survey project. She’s been part of the recruitment group, and has been involved in a lot of preliminary analyses and interpretation of data. • “I’ve done all this work, and made a huge contribution, but I’m still not an author on any papers from the group. I don’t know what else I need to do before I start getting recognition for the work that I’m doing”
  30. 30. • Does Grace have the right idea about data and authorship? • What is your advice to Grace about what she needs to do next? • Is this the same in all disciplines? If it’s different, what are some of the key differences between disciplines?