David Johnson
Senior Lecturer/Associate Professor at Department of Informatics and Media
- Telephone:
- +46 18 471 77 02
- E-mail:
- david.johnson@im.uu.se
- Visiting address:
- Ekonomikum (plan 3)
Kyrkogårdsgatan 10 - Postal address:
- Box 513
751 20 UPPSALA
Download contact information for David Johnson at Department of Informatics and Media
- ORCID:
- 0000-0002-2323-6847
Short presentation
I am an Associate Professor (Docent) of Information Systems. I am interested in data infrastructures, particularly those that support data-intensive scientific research, and the practices around using data and artificial intelligence.
Keywords
- information systems
- artificial intelligence systems
- information infrastructures
- interoperability
Biography
I am an Associate Professor (Docent) of Information Systems in the Department of Informatics and Media. I teach and research themes associated with data and artificial intelligence.
I am also a Visiting Fellow at the University of Oxford's Kellogg College. I was privileged to have previously held a Junior Research Fellowship from 2015-2018 at Kellogg College. I am also a Senior Associate Tutor (Honorary) at Oxford's Department for Continuing Education.
I am an award-winning educator, having received a University of Oxford Teaching Award (Mathematical, Physical and Life Sciences Division) in 2016 and the New & Future Educators Award jointly given by the Association for the Advancement of Artificial Intelligence (AAAI) and Association for Computing Machinery (ACM) in 2022.
Previously I was a Senior Researcher in the University of Oxford's Department of Engineering Science and held research posts in the Data Science Institute at Imperial College London and Oxford's Department of Computer Science. I have been a consultant for the United Nations, advising on big data and data science.
I hold a PhD in Computer Science from the University of Reading, UK, and a Postgraduate Certificate in Teaching and Learning in Higher Education from the University of Oxford.
I am a director of our Masters Programme in Information Systems.
I act as course director for the following courses:
- 2IS081 Data Mining and Applied Machine Learning (Bachelors)
- 2IS073 Digital Infrastructure (Masters)
- 2IS074 Artificial Intelligence and Machine Learning (Masters)
- 2IS077 Big Data Analytics (Masters).
I am section leader for Information Systems at my department in Uppsala and a member of the Uppsala University Computational Social Science Lab.
Research
My research to date broadly falls into the theme of data infrastructures, primarily for life sciences research. Data infrastructures are computing architectures, tools, and services designed to collect, store, manage, process, and disseminate data. I have participated as a researcher in European-funded research projects from the EU Sixth Framework Programme (FP6) to Horizon 2020.
More recently, I have become interested in the practices around data and artificial intelligence (AI). I am currently working on a project to study the replication practices of AI research in the life sciences, and on a Vinnova-funded project following the adoption of large language models (LLMs) for citizen services departments within Uppsala Municipality.

Publications
Selection of publications
AI i samhällets tjänst: Utveckling med tillit och transparens
2023
Data Discovery for the SDGs: A Systematic Rule-based Approach
Part of GoodIT '23, p. 384-391, 2023
- DOI for Data Discovery for the SDGs: A Systematic Rule-based Approach
- Download full text (pdf) of Data Discovery for the SDGs: A Systematic Rule-based Approach
Part of AI Matters, p. 16-21, 2022
ISA API: An open platform for interoperable life science experimental metadata
Part of GigaScience, 2021
- DOI for ISA API: An open platform for interoperable life science experimental metadata
- Download full text (pdf) of ISA API: An open platform for interoperable life science experimental metadata
COPO: a metadata platform for brokering FAIR data in the life sciences
Part of F1000 Research, 2020
- DOI for COPO: a metadata platform for brokering FAIR data in the life sciences
- Download full text (pdf) of COPO: a metadata platform for brokering FAIR data in the life sciences
PhenoMeNal: Processing and analysis of metabolomics data in the cloud
Part of GigaScience, 2019
Recent publications
Towards Modelling and Simulation of Organisational Routines
Part of Computational Science – ICCS 2024, p. 367-379, 2024
- DOI for Towards Modelling and Simulation of Organisational Routines
- Download full text (pdf) of Towards Modelling and Simulation of Organisational Routines
AI i samhällets tjänst: Utveckling med tillit och transparens
2023
AI for the benefit of society: Progress with trust and transparency
2023
DEBATT: AI-politiken är i desperat behov av nyansering och reformer
2023
Part of Critical Discourse Studies, 2023
- DOI for Saying `Criminality’, meaning ‘immigration’?: Proxy discourses and public implicatures in the normalisation of the politics of exclusion
- Download full text (pdf) of Saying `Criminality’, meaning ‘immigration’?: Proxy discourses and public implicatures in the normalisation of the politics of exclusion
All publications
Articles in journal
Part of Critical Discourse Studies, 2023
- DOI for Saying `Criminality’, meaning ‘immigration’?: Proxy discourses and public implicatures in the normalisation of the politics of exclusion
- Download full text (pdf) of Saying `Criminality’, meaning ‘immigration’?: Proxy discourses and public implicatures in the normalisation of the politics of exclusion
Part of AI Matters, p. 16-21, 2022
ISA API: An open platform for interoperable life science experimental metadata
Part of GigaScience, 2021
- DOI for ISA API: An open platform for interoperable life science experimental metadata
- Download full text (pdf) of ISA API: An open platform for interoperable life science experimental metadata
COPO: a metadata platform for brokering FAIR data in the life sciences
Part of F1000 Research, 2020
- DOI for COPO: a metadata platform for brokering FAIR data in the life sciences
- Download full text (pdf) of COPO: a metadata platform for brokering FAIR data in the life sciences
PhenoMeNal: Processing and analysis of metabolomics data in the cloud
Part of GigaScience, 2019
Interoperable and scalable data analysis with microservices: Applications in metabolomics
Part of Bioinformatics, p. 3752-3760, 2019
- DOI for Interoperable and scalable data analysis with microservices: Applications in metabolomics
- Download full text (pdf) of Interoperable and scalable data analysis with microservices: Applications in metabolomics
Computer Simulation, Visualization, and Image Processing of Cancer Data and Processes
Part of Cancer Informatics, 2015
- DOI for Computer Simulation, Visualization, and Image Processing of Cancer Data and Processes
- Download full text (pdf) of Computer Simulation, Visualization, and Image Processing of Cancer Data and Processes
High dimensional biological data retrieval optimization with NoSQL technology
Part of BMC Genomics, 2014
- DOI for High dimensional biological data retrieval optimization with NoSQL technology
- Download full text (pdf) of High dimensional biological data retrieval optimization with NoSQL technology
Optimising parallel R correlation matrix calculations on gene expression data using MapReduce
Part of BMC Bioinformatics, 2014
- DOI for Optimising parallel R correlation matrix calculations on gene expression data using MapReduce
- Download full text (pdf) of Optimising parallel R correlation matrix calculations on gene expression data using MapReduce
Semantically Linking In Silico Cancer Models
Part of Cancer Informatics, p. 133-143, 2014
- DOI for Semantically Linking In Silico Cancer Models
- Download full text (pdf) of Semantically Linking In Silico Cancer Models
Part of IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, p. 824-831, 2014
Dealing with Diversity in Computational Cancer Modeling
Part of Cancer Informatics, p. 115-124, 2013
Connecting digital cancer model repositories with markup: introducing TumorML version 1.0
Part of ACM SIGBioinformatics Record, p. 5-11, 2013
Articles, review/survey
Conference papers
Towards Modelling and Simulation of Organisational Routines
Part of Computational Science – ICCS 2024, p. 367-379, 2024
- DOI for Towards Modelling and Simulation of Organisational Routines
- Download full text (pdf) of Towards Modelling and Simulation of Organisational Routines
Data Discovery for the SDGs: A Systematic Rule-based Approach
Part of GoodIT '23, p. 384-391, 2023
- DOI for Data Discovery for the SDGs: A Systematic Rule-based Approach
- Download full text (pdf) of Data Discovery for the SDGs: A Systematic Rule-based Approach
Part of Proceedings of the 36th AAAI Conference on Artificial Intelligence, p. 12766-12773, 2022
Towards Explainable, Compliant and Adaptive Human-Automation Interaction
Part of Proceedings of the 3rd EXplainable AI in Law Workshop (XAILA 2020), 2020
- Download full text (pdf) of Towards Explainable, Compliant and Adaptive Human-Automation Interaction
"Why did you do that?": Explaining black box models with Inductive Synthesis
Part of International Conference on Computational Science (ICCS), 2019
- DOI for "Why did you do that?": Explaining black box models with Inductive Synthesis
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Teaching Agile Methods to Software Engineering Professionals: 10 Years, 1000 Release Plans
Part of XP 2017: Agile Processes in Software Engineering and Extreme Programming, p. 151-166, 2017
- DOI for Teaching Agile Methods to Software Engineering Professionals: 10 Years, 1000 Release Plans
- Download full text (pdf) of Teaching Agile Methods to Software Engineering Professionals: 10 Years, 1000 Release Plans
DSIMBench: A benchmark for microarray data using R
Part of BPOE 2014: Big Data Benchmarks, Performance Optimization, and Emerging Hardware, p. 47-56, 2014
- DOI for DSIMBench: A benchmark for microarray data using R
- Download full text (pdf) of DSIMBench: A benchmark for microarray data using R
Abstraction in Physiological Modelling Languages
Part of Symposium On Theory of Modeling and Simulation, p. 76-83, 2013
Modular markup for simulating vascular tumour growth
2012
TumorML: Concept and requirements of an in silico cancer modelling markup language
p. 441-444, 2011
- DOI for TumorML: Concept and requirements of an in silico cancer modelling markup language
- Download full text (pdf) of TumorML: Concept and requirements of an in silico cancer modelling markup language
The Case for Using Markup for Biomechanical Modelling
2011
A middleware independent grid workflow builder for scientific applications
2009