From integration to interaction: A knowledge ecology framework

By Zoë Sofoulis

Zoë Sofoulis (biography)

Would a focus on ‘knowledge ecology’ provide a useful alternative to ‘knowledge integration’ in inter- and trans-disciplinary research?

My experience in bringing perspectives from the humanities, arts and social sciences (HASS) to projects led by researchers from science, technology, engineering and mathematics (STEM) has led me to agree with Sharp and colleagues (2011) that ‘knowledge integration’ is essentially a positivist concept, dependent on the idealist model of a unified field of scientific knowledge to which every bit of science contributed.

Many partners and co-researchers from STEM backgrounds, it seems, cannot recognise other knowledge paradigms and can only ‘integrate’ knowledge in the form of quantitative data. HASS research is excluded or disqualified as merely ‘anecdotal’ or ‘subjective’. Like racial or cultural assimilation, knowledge integration seems to require non-dominant knowledges to disguise or erase their unique differentiating features in order to blend with the dominant positivist paradigm. To use an ecosystems metaphor, positivist science behaves like an apex predator committing “epistemicide” (De Sousa Santos 2009, 116) gobbling up other knowledges and creating an epistemological monoculture.

The idea of a ‘knowledge ecology’ or a ‘knowledge ecosystem’ comes from management theory that draws on ecosystem sciences and new media theory to talk about non-hierarchical ways to facilitate productive knowledge flows in an information-based economy. It resonates with humanities-based epistemological pluralism, which understands that each knowledge framework illuminates, as well as conceals, different aspects of reality.

The idea of ‘knowledge ecology’ implies groups of diverse players of different sizes and roles, each finding their niche in a system of knowledge flows.

Beyond celebrating epistemological diversity, I wondered if the analogy could be pushed to work harder as a framework for describing some of the challenges encountered in the complex dynamics of transdisciplinary and cross-sectoral projects.

I started with a generic template for describing an ecosystem and translated the components into knowledge system terms, as follows:

Biotic factors – translated into the diversity of knowers and knowledges of different modalities that are involved in a particular project (or knowledge ecosystem). This includes the subjects of social research.

Abiotic factors – equivalents of non-living ecosystem components (water, temperature, gases, nutrients) are the political-economic factors that favour certain kinds of knowledges and knowers: the political climate, research priorities and funding policies, research facilities, equipment, and other knowledge infrastructures.

Interaction of biotic and abiotic factors – how differential access to research resources constrains and enables interactions between different knowers and knowledges of an ecosystem in a particular political-economic context.

Interaction among biotic factors – knowledge equivalents of ‘food chains’, predator/prey (“integration”) and other kinds of relationships between knowledges and knowers, including symbioses, cooperation, synergy, etc.

Inside and outside system boundaries – consideration of boundaries between disciplines or special knowledges, and flows across boundaries that operate within a knowledge ecosystem and between it and other ecosystems; questions of knowledge transfer and translation.

Evolution – factors producing new or altered knowledge ecologies, and changes brought about though successful translations and collaborations.

These are summarised in the table below, where the first column contains the ecosystems science concepts, and the second and third summarise their knowledge ecology equivalents.

An additional column can be added to either describe a particular case study or to help participants in a new study “get to know each other” and identify their “niche” in the knowledge ecosystem.

1. Biotic factors (organisms) Knowers and Actors
Knowledges and Modalities
* Different kinds of knowers and knowledges brought to bear on a problem or project.
* Research modes, methods, evidence standards.
2. Abiotic factors (climate, geography, etc) Policy Settings and Resources * General policy climate and knowledge landscape.
* Resources: research funding and infrastructure, centres and networks.
3. Interaction of biotic with abiotic factors Knowledge/
* Conditions of knowledge production.
* Distribution of research resources.
* Interactions between different researchers and fields enabled or constrained by access to resources.
4. Interaction among biotic factors (organisms) Relations between knowers, knowledges; knowledge practices * Interactions on multi disciplinary teams, and with communities.
* Knowledge ‘food chains’, parasitism, predation,  symbioses, etc.
* ‘Charismatic mega-fauna’ (Big Names). Endangered knowledges, monocultures.
5. Inside and outside system boundaries Boundaries, Translation,
Contributions beyond
* Drawing, defending, transgressing boundaries around disciplines and expertise.
* Knowledge transfer, translation, brokering.
* Site specific and untranslatable knowledges.
6. Evolution Evolution of new or altered knowledge ecologies * New kinds of knowers and knowledges and how they are emerging.
* Successful pathways for knowledge transfer, translation and collaboration.

The model has proven to be a useful heuristic for organising ideas and discussion about the multiple people and organisations, as well as epistemological and contextual factors, that are in play in collaborative projects that bring together different kinds of knowledges, knowers and modes of knowledge production. The elision of knowers and knowledges proves handy as one can talk about challenges for creating knowledges in the team without getting personal.

What do you think? Do any of these ideas resonate with your experience? Can you see applications in either analysing project experiences after the fact or at the scoping stage of proposals to help all parties better understand the proposed project in context and their niche in it?


De Sousa Santos, B. (2009). A Non-Occidentalist West? Learned ignorance and ecology of knowledge. Theory Culture Society, 26, 7-8: 103-125.

Sharp, L., McDonald, A., Sim, P., Knamiller, K., Sefton, C. and Wong, S. (2011). Positivism, post-positivism and domestic water demand: Interrelating science across the paradigmatic divide. Transactions of the Institute of British Geographers, 36: 501-515.

To find out more about this framework and its applications, see:

Fam, D. and Sofoulis, Z. (2017, forthcoming). Trouble at the disciplinary divide: A Knowledge Ecologies analysis of a co-design project with native Alaskan communities. In, D. Fam, J. Palmer, C. Riedy and C. Mitchell (Eds.). Transdisciplinary Research and Practice for Sustainability Outcomes. Routledge/Earthscan: London, United Kingdom.

Sofoulis, Z. (2015). A Knowledge Ecology of Urban Australian Household Water Consumption. ACME: An International E-Journal for Critical Geographies, 14, 3: 765-785. Online:

Sofoulis, Z., Hugman, S., Collin, P. and Third, A. (2012). Coming to Terms with knowledge brokering and translation: Background paper. Knowledge Ecologies Workshop, 28 November 2012, Institute for Culture and Society, University of Western Sydney, Parramatta. Online:

Biography: Zoë Sofoulis is an Adjunct Fellow at the Institute for Culture and Society, Western Sydney University. Her long term fascination with the irrational and mythic dimensions of high technology in western culture has converged with concerns about integration and implementation in relation to research on the social and cultural aspects of urban water management.

12 thoughts on “From integration to interaction: A knowledge ecology framework”

  1. The idea of an “ecology” is helpful as it emphasises that each collaboration, and those interacting within a collaboration, operate within a unique context that is ever-changing and impacting upon how the collaboration and its actors perceive things and go about their relationships and work. I like this imaginative metaphor.

  2. Nowhere can I see the amalgamation of STEM and HASS more on display than in the entertainment industry. I have several associates who consult with Hollywood production studios and the conversations usually go something like this:
    Technical consultant: “You can’t do that, it doesn’t work that way, it has to be like this”
    Moviemaker: “We can’t do it that way, the movie wouldn’t work, it has to be like this”

    Each being confident and sure of his or her own knowledge.

    Zoe, you have given me loads to think upon and I don’t feel as if I can comment further until I do. That is high praise and I thank you for putting this out.

  3. Thanks Zoe – interesting and timely 🙂

    just on Joseph’s mega-fauna consuming debate…. the whole issue of organisational autopoiesis comes in I think. The defining characteristic of any living system (and therefore any part of an ecosystem) is that it can consume resources and change those into itself, it can self-recreate itself. Can we see that happening in what we might choose to call a knowledge ecosystem? and is it at the expense of other entities in the system? I think the answer is yes and I also think the charasmatic mega-fauna tag is quite appropriate.

    Just one example is “big data” as a charismatic mega-fauna, I know knowledge environments where big data as the knowledge paradigm IS squeezing out other forms of knowledge and knowledge generation, So practically it IS kiling them, both at the level of people who do other stuff losing their jobs, and at the level of resource consumption and at the level of what counts as valid and valuable knowledge. This in spite of the fact that it really hasn’t delivered much (or, in most cases I’m thinking of, anything at all) in terms of results, in other words it has won by virtue of charisma not performance.

  4. I can see Zoe and Joseph’s angle – but the knowledge ecology framework could be seen as a useful model – and as George Box said: ” all models are wrong, but some are useful.” The framework could definitely rattle the cage enough for someone to see a system with new eyes – the “predatory” metaphors being provocative and perhaps Kafkaesque enough to wake us up – but it’s probably not Intended as a final resting place.

  5. I much like this Zoe. I have been playing in the trans-discplinary space for a while and might have a bit to share.

    A couple of quick contributions (I can’t see how to post a diagram here):

    On Information and knowledge sharing

    Knowledge Cultures in western systems have ‘issues’… Val Brown states that, rather than sharing knowledge for common good…

    “Each knowledge culture has developed effective boundary-riding techniques through allocating ignorance…Individual knowledge is consistently rejected as prejudiced; local knowledge as gossip; specialised knowledge as jargon; strategic knowledge as corrupt and holistic knowledge as impractical.

    Familiar accusations from their fellow knowledge’s are that specialist knowledge is too abstract to be useful; community knowledge is irrelevant since it can only refer to one case; strategic knowledge of organisations is distorted, since it seeks to influence reality, not merely to observe it.”

    Source: Val Brown, in The Australian Natural Resource Management Knowledge System, Andrew Campbell (Land & Water Australia, 2006)

    And this one from David Holmzer, who says:

    “… those of us within the broad and diverse community of leadership, are finding ourselves in the unique position of helping to steward the concurrent processes of decay and rebirth.

    …helping shift between the old and the new is one of the key purposes on our new map of leadership. And …all that lies ahead will be bound by the seemingly paradoxical notions of unity and difference. … there exists a great need for scholars and practitioners who are able to bridge ideological and epistemological boundaries… to help …emergence of new forms of thinking about organizations and leadership.”

    Source: David Holmzer, 2012, The 13th Annual International Leadership Association Global Conference, October 2011, January 2012 / Notes from the Field

  6. Great frame work Zoe. I love the concept of ‘Charismatic mega-fauna’! I had a big LOL over that. I cannot wait for an opportunity to use that identifier. I’ll be sure to reference you as the creator.

    I think these sort of analogies will go far to help engage bench scientists. As team science become more and more the norm, STEAM (A=Art) teams will only perform as well as they learn to value the social sciences to help them learn how to ‘play nice’ and maximally collaborate.

    • Hi Suzanne, I agree that identifying the ‘charismatic mega-fauna’ in a knowledge ecosystem is a hoot to do and say! Hope you are right that analogies like this might help people on team/STEAM projects play more respectfully.

  7. That’s good, Timothy. Sounds like just the kind of thing where the knowledge ecology framework would be helpful. Do let us know how it goes!

  8. I find knowledge ecology a risky metaphor. The idea of a knower/knowledge predator consuming an other would seem to imply that the prey knower/knowledge is taken by force, is consumed, and no longer exists afterwards. While opinions have obviously been violently suppressed, I would argue that this is (fortunately) the exception rather than the rule, and when this occurs, the knowledge is not productively consumed. Positivists appropriating other knowledges do not extinguish those other knowers (let alone all knowers associated with that knowledge, in an epistemicide) even if they do refuse to respect the other knowers on their own terms. Additionally, it seems the way it has been presented here risks being equally epistemicidal – it does not seem to tolerate some knowers holding their own knowledge above others. That would seem to be problematic, e.g. with regard to climate change sceptics. My preference is to replace the idea of (natural) ecology with an actor-network, the behaviour of which can be analysed from a knowledge governance perspective. For a form of integration that allows both positivist and post-positivist to co-exist, I like Jackson’s critical systems practice meta-methodology which allows for switching between perspectives, which he refers to as “functionalist”, “interpretive”, “emancipatory” and “postmodern”.

    • Thanks for your thoughtful response, Joseph. I really like your more nuanced account of the relations between the ‘predator’ positivists and other knowledges. After all: we are what we eat! Also I agree I suffer from epistemicidal tendencies (towards positivism) that my co-author Dena Fam usually helps me keep a lid on. 🙂
      Your point about actor-network as a better perspective is well made and taken. However one problem with that approach is that beginners don’t know where to start with a tangled socio-technical network. The knowledge ecology framework simplifies the initial task by allowing a range of different actors and interactions to be identified, in a sense constituting a proto-actor-network model. Then a more detailed ANT study of dynamics might follow.

      • Sounds good to me! I agree that as long as one doesn’t take the metaphor too far, knowledge ecology is a nice way in.

  9. It is a very helpful analogy and frame to appreciate the natural interactions that ‘want’ to occur between species. I will use these concepts to describe governance frameworks for the ecosystems that emerge within the landscape sustainability projects.


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