Networks of knowledge sharing

Understanding the driving forces of knowledge propagation through communities and to investigate whether aspects of this process can shine light on quality and/or value associated with certain items of knowledge.

The need and impact

The generation and diffusion of knowledge underpins a large part of society and human behaviour. Highly sought-after and notoriously unquantifiable, knowledge is the subject of interest from many angles: some want to exploit it; others protect it; yet more like to ensure its efficiency, fairness or equity.

We have assembled an interdisciplinary team of researchers to gain a deeper understanding of the driving forces of knowledge propagation through communities and to investigate whether aspects of this process can shine light on quality and/or value associated with certain items of knowledge.

The results of our research are intended to provide a framework for designing best practice and/or policy towards enhancing knowledge-intensive social activities and enterprises.

The approach

Our research programme will have two main thrusts:

  1. Studying open-source software development, representing a specific, highly structured, and well-documented knowledge-generation ecosystem.
  2. Elucidating the magnitude and quality of noncodified knowledge(s) used in technological inventions, with particular focus on indigenous knowledge such as mātauranga Māori.

Both these sub-projects are highly amenable to our specific methodological approach based on network analysis.

Sub-project 1: Measuring the dynamics and value of open-source software development: Network analyses of Github and Cardano

The Github repository is a well-documented and accessible record of open-software development. Blockchain technologies such as Cardano are a type of innovation commons with in-built development platform that interacts closely with market forces and social structures. Both enterprises have transparent processes for quality control and clear attribution of use that mirror, and even surpass in precision and significance, those available in the innovation and science space via publications (patents, articles) and their citations.

In our collaboration involving software developers, economists, and network scientists, we will utilise modern network-analysis tools to study the characteristic dynamics of software development and its intrinsic valuation by the creators’ community. We want to uncover the underlying mechanisms stimulating developers’ activity and triggering the wider adoption of their individual contributions.

Despite its high relevance for today’s technologies, software development has been a severely understudied creative effort. We are poised to fill this knowledge gap by utilising our recent insights gained from quantitative science and innovation studies.

Sub-project 2: Mapping noncodified (e.g., indigenous) knowledge relevant as prior art in patents

Patents have to disclose current knowledge and expertise as prior art. As opposed to Western knowledge that has been codified in publications such as previous patents or scientific articles, indigenous knowledge is carried by the collective memory of local communities.

How does the interaction between these two knowledge systems influence innovation? What is the footprint of indigenous knowledge in historic and contemporary patented inventions? What is the value associated with unattributed and/or appropriated indigenous knowledge used in these? We aim to answer these questions as a team combining expertise in indigenous knowledge (especially mātauranga Māori), innovation economics and network analysis.

Research aims

• Utilise modern network-analysis tools to study the characteristic dynamics of software development.
• Uncover the underlying mechanisms stimulating developers’ activity and triggering the wider adoption of their individual contributions.
• Fill knowledge gap on creative effort for software development.
• Explore the interaction between Western and indigenous knowledge and the influence on innovation.
• Identify the footprint of indigenous knowledge on inventions (both historic and contemporary patents).
• Evaluate the contribution of unattributed and/or appropriated indigenous knowledge.

People

  • Professor Uli Zuelicke
  • Professor Les Oxley
  • Dr Hēmi Whaanga
  • Professor Shaun Hendy
  • Dr Mubashir Qasim
  • Professor Michele Governale
  • Robert O’Brien
  • Dr Izi Sin
  • Dr Adam Jaffe
  • Dr Kyle Higham
  • Tipene Merritt