Reflections on a (slightly unusual) multi-disciplinary academic career
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Talk given at the School of Computer Science, The University of Manchester, UK Postgraduate Research Symposium 2019 the Carole Goble Doctoral Paper award was given for the first time
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Reflections on a (slightly unusual) multi-disciplinary academic career
- 1. Reflections on a (slightly unusual) multi-disciplinary academic career Professor Carole Goble CBE FREng FBCS CITP The University of Manchester, UK carole.goble@manchester.ac.uk
- 2. 40 years this coming October…. …. At Manchester
- 3. I didn’t intend to stay at the university… 1980s Ian Cottam Behind many a successful professor is a super supportive partner Access Grid
- 4. …I didn’t intend to be an academic… 1980s Teaching lectureship Women in Computing 1st CoI on a grant: 1988 1st Publication: 1990 1st Conf attended: 1991 1st Conf presentation: 1992 1st Intl Conf presentation: 1993 1st PI on a grant: 1994 1st Keynote: 2000 Full Professor: 2000
- 5. … I became one anyway… 102funding awards 114journal articles 149refereed conference articles Ncollaborators (Linked-In 1496 connections) 60+ keynotes 60+Research Fellows Software and Resources beyond Proof of Concept
- 6. … some PhD stuff… oppositions supervisions Mr Cottamand one for me we can walk different paths
- 8. 1. Mentors don’t worry about gender, location or discipline… Apprenticeship Career Mentorship Career Enabling
- 9. 1. Mentors don’t worry about gender, location or discipline… Collaborators / Influencers
- 10. 2. Empirical Research • ". . . the fundamental difference between a theoretician and an engineer is that an engineer is away and doing something once he's [sic] grasped that there's a way of doing something, and the theoretician is strangely enough most of the time lagging behind, cleaning-up -- that's the best word I can use . . ." Tom Kilburn 1992 Tom Kilburn
- 11. 2. Empirical Research Theory Computer Science Application Computational Science Practice Software Engineering PRODUCT PRINCIPLE USE CASE fundamental applied
- 12. 2. Empirical Research (e-)Science 1. Empirical describing natural phenomena 2. Theoretical using models, generalizations 3. Computational simulating phenomena 4. Data intensive unify theory, experiment, and simulation New research outputs Open, reproducible science
- 13. 2. Empirical Research Team Based Researchers Computational Biologists Research Software Engineers Data management specialists Mix of complementary skills I’m a Co-ordinator and Resource Investigator*… *Belbin Team Role Theories
- 14. 2. Empirical Research Team Based A PhD in a team • Freedom to innovate • Support & stimulation • Fast track take up Watch for • Setting boundaries • Sucked into project delivery • On-boarding frustration Researchers Computational Biologists Research Software Engineers Data management specialists PhD students
- 15. 2. Empirical Research Team Based Practice - Software and Resources beyond Proof of Concept VIEWER Practice - Standards COHSE Researchers Computational Biologists Research Software Engineers Data management specialists JERM Ontology myGrid Ontology
- 16. Research Software Matters 2010 - 2024 A national facility for cultivating and improving research software to support world-class research. 2006-2010
- 17. 3. Multi-disciplinary Collaboration people from different disciplines working together, each drawing on their disciplinary knowledge*. *http://www.arj.no/2012/03/12/disciplinarities-2/ Life Sciences Plant and Animal health Drug Discovery Systems & Synthetic Biology ‘Omics Industrial Biotechnology Biodiversity Digital Libraries HelioPhysics Astronomy Rare Disease,Virtual Physiology Health Informatics, Precision Medicine Museum Collections Social Science
- 18. 3. Multi-disciplinary Collaboration Biodiversity EU Life Science Data Infrastructure Industrial Biotechnology Extreme matrix management is another talk….
- 19. Go to where your collaborators are
- 22. KnowledgeTurning in Science [Figures: Josh Sommer, Chordoma Foundation] GobleC., De Roure D., Bechhofer S. (2013) AcceleratingScientists’ KnowledgeTurns, doi:10.1007/978-3-642-37186-8_1 Research Commons Access to resources, Flow of Information Coordination & Collaboration Automated processing Mobilisation of the community Scale and Change The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3 (2016) doi:10.1038/sdata.2016.18
- 23. Data in Science in a Nutshell Wonderfully messy.Wonderfully human.The spreadsheet is king. A world of possibilities. Cool Machine Learning Uncool Stewardship Incompatibility * Metadata Method Service ethic Interoperability
- 24. Social Studies of Science Scientific Instrumentation Scientific Information Technology Scientific Community Steven Shapin Pump and Circumstance: Robert Boyle's LiteraryTechnology (1984) https://doi.org/10.1177/030631284014004001
- 25. Computer Science & Software Engineering Distributed Computing Knowledge Computing Social Computing Computational Workflows Open Science Cloud based services Web services Portability Containers Sharing & Collaboration Provenance TransparencyInteroperability Reproducibility FAIR e-Labs & collaboratories Interop SemanticWeb Ontologies Linked Data Reasoning nanopublications
- 26. E.g: Computational Workflows automate data and processing tasks • Functional programming, lambda calculus … • Visual programming … • Service-oriented and Cloud computing, repair, preservation, packaging … • Semantic description: validation, planning, optimisation, discovery, automated annotation … • Provenance tracking, credit propagation … • Sharable method • Social workflow collaboratory • Workflow research objectsLots of e-Infrastructure, tools and support
- 27. A systematic strategy for large-scale analysis of genotype– phenotype correlations: identification of candidate genes involved in African trypanosomiasis 2007, Vol. 35, No. 16 5625-5633 2007 2017
- 28. 2018
- 29. Impact -> time, staying power, trust 2003 2007 2008 EU Workflow collaboratory 2018-2023 Projects using the infrastructure Other people’s projects using the infrastructure 2010-2014
- 30. Multi-Disciplinary Research… Juggle, Balance, Communicate Respect the ego-system Be Patient BuildTrust & Respect Be Useful Be Reliable Return favours Avoid servitude Learn the culture • Embed • Bigger picture • Rewards • Work practices, language Align and revisit • Problem • Expectations • Timings • Availability • Resources Complement
- 32. • Plan with everyone • Manage expectations • Define boundaries • Be pragmatic • Ask “stupid” questions • Build a network (mentors) • Exploit your unique skillset • Avoid servitude • Swim against the flow • Publish for your career • Adjust to your audience • Have fun
- 35. Write for the different disciplines Value impact & influence through all methods BOSC 2007 Multi-Disciplinary Scholarly Communication 84,371 views
- 36. Scholarly Communication Take more seriously in Computer Science • Paper -> Reproducible Research Objects • “Executable papers” • Publish -> Release
- 37. TL;DR summary • slightly unusual – we can walk different paths & mentors matter. • multi-disciplinary academic career – empirical research smoothed the way for me – multi-disciplinary is rich with possibilities, but… …requires mindfulness. …the social and technical are hard to separate. • think beyond the PDF!
- 38. Acknowledgements • The eScience group • The Information Management Group • All my collaborators and mentors • All my students • All my funders • Simon Harper for this great honour • And of course Ian Cottam…otherwise I wouldn’t have been here.