Dr Philip Garnett

“You should prefer a good scientist without literary abilities than a literate one without scientific skills.” – Leonardo da Vinci

I am a complex systems scientist and lecturer of operations management and business analytics based at the University of York UK. I am also a member of the York Centre for Complex Systems Analysis (University of York UK).

My scientific background is in the modelling and simulation of biological systems. I started my academic career as a geneticist (BSc Genetics, University of Nottingham, UK) and quickly realised that it was the modelling aspects of this field that I was most interested in. For example, the modelling of drift and selection in populations (work that has carried forward into work on ngrams). I then went on to study for an MSc Information Processing (University of York, UK), and eventually did a PhD in Computational Biology (University of York, UK). Over time, my interest in modelling social systems also developed. Now as a lecturer in Operations Management and Business Analytics my research still combines aspects of modelling and simulation, along with the analysis of complex or difficult data.

I am interested in how simple interactions between agents (such as people or organisations) can produce complex and often unexpected (emergent) behaviours in a system. My PhD work focused on the modelling and simulation of Auxin Transport Canalisation (for review see, Computer simulation: The imaginary friend of auxin transport biology). My current research interests are focused around applying systems theory, complex systems theory, and network analysis techniques to a wide range of problems, largely focused on the processing of information. Combined with modelling and simulation techniques I am interested in what the analysis of information can tell us about how organisations and society works. I am also interested in the power of information and its consequences for our privacy and liberty.

Current Research Projects:

I am currently working on a few related research projects, many of which are collected under the meta-project Algorithmic Indexing:

Business History:

Hillards Super Market: Hillards was a significant player in the supermarket industry up until its takeover by Tesco in 1987. Founded in 1885, it grew from a single store to over 200 in its one hundred years of trading.  This project is rescuing the remaining archive material through a process of digitisation, to produce a high quality searchable digital resource. Using advanced data analytics methods that many of my research projects have in common. This project is supported by a grant from the British Academy of Management, website the Hillards Archive.

Industry Networks: Using the Banking and Mining sectors of the 20th century as a test case, this research investigates how banks and mining companies were linked together and how these connections may have influenced both the individual companies and the sector as a whole.

Document Analysis/Digital Humanities:

Documentary evidence, often in the form of PDF files, is often released in support of court cases and public inquiries. This evidence is on the face of it released to improve the transparency of the process. However, questions remain about how transparent this type of evidence release truly is. Selective release and redaction of documents could be as much about the control of a narrative as it is about transparency. The datasets released are often hard to read and search, and therefore it is difficult to determine if they support the outcome or conclusions of the inquiry or court case or not. Using similar advanced data storage, analysis, text mining, and linking methods as we use on the Hillards project, this aspect of my research attempts to improve the accessibility of public datasets to allow people to draw their own conclusions about the process, the outcome, and the evidence.

Private Chelsea Manning Court Documents: This project applies the above methods to the court documents released as part of the on-going Chelsea Manning trial.

Public Inquires, Leveson and Chilcot: Public inquires of this type are increasingly releasing some of the the evidence that was collected and used during the process. This project applies the above techniques to these resent and on-going public inquires to make the evidence more accessible and therefore easier to relate to the outcome of the process. There is a subproject to this looking at the Danial Morgan Murder, website here, there is also a blog post.

Journal Text Mining: Journals are individually important to academic research, as they remain one of, or perhaps the primary method of dissemination of academic research. They are also interesting as a corpus, and perhaps much can be gained by the systematic mining of journals.

General Research Interests: Complexity Theory, Network Analysis and Big Data, PhD applications in these areas are welcome.

  • The analysis of social and new media. I am interested in how organisations use and monitor social and new media, such as Twitter, Facebook and online web forums. I also research how information flows through social media and new trends and fashions come and go.

  • Modelling and simulation of organisational behaviour. How do the interactions of connect organisations shape the development of economic sectors? What are the significance of hidden and explicit connections between businesses, such as shared directorships? This research uses network analysis techniques and modelling to investigate now relationships between business and the people running them influence those businesses and the wider economy.

  • Data Mining and Analytics. Business (and society at large) generates huge amounts of information. Leveraging this mountain of information to extract value is becoming increasingly challenging. We use modelling and analytical techniques to help mine information out of Big Data.

  • The effect of Big Data analytics on privacy and liberty. Information can be both a defender liberty, as it can increase transparency in society. It however can also be be used to erode our civil liberties and freedom, by increased surveillance by both the state and private sector.

  • Systems of systems. Increasing dealing with the complexity of physical, natural and human systems, and how they are connected demands new approaches to their study. We use the notion of systems of systems to model different aspects of society, such as the distribution of risk in financial systems.

  • Business history. Analysis of historical data can often lead to insights into the presence and the future. We apply all the techniques we use to model and analyse contemporary data to historical business history. As a way of learning from the past, and overturning misconceptions.


  • Modelling and Simulation of Complex Systems.
  • Data mining.
  • Big Data – including storage in of data Graph Databases, Neo4J, NoSQL and MySQL.
  • Programming Java, C/C++, GPGPU, PHP.

Update posts can be found on the blog page, and I have a YouTube channel.