2.2.6 Hybrid network mapping
Design mapping supports the examination of the complex relational structures of urban landscapes. As a spatio-topological and spatio-temporal description method, maps open up special opportunities for accessing a multidimensional dynamic Raumgeschehen (spatial interaction) . . . Design mapping aims not only at describing and representing complex relational structures, but also at revealing these, at (re)interpreting, at (re)configuring and negotiating . . . Mapping can thus become a key navigational practice for (re)positioning within the ever-changing, complex conditions of urban landscapes.
Sigrun Langner, Mapping as a navigational strategy
(Langner, 2019, pp.66–67)
Figure 40. Examples of iconic network diagrams/maps that reflect systems thinking visually – interrelations of parts and whole.
(Left image) The Hebrew “Tree of life” (Kabbalah) diagram dates back to the 9th century BC. It consists of nodes (spheres) symbolising different archetypes and lines (paths) connecting the nodes. The diagram is believed to represent life – i.e. relationships between God and the human psyche (very broadly speaking). Image credit: AnonMoos (2014) from Wikimedia Commons.
(Right image) Charles Darwin’s “Tree of life” (1837) sketch could be argued as one of the most renowned forms of network mapping, understanding and representing interrelations in a visual format. The sketch of an evolutionary tree is from his notebook “Transmutation of Species”. Image credit: Darwin (1837) from Wikimedia Commons.
For my research, this type of network mapping was used in the initial research phase (i.e. Reflective moments – refer to Figure 33) to process the vast amounts of data that were collected within the transdisciplinary context (including issues regarding water, urban development, marine ecology, design decisions, etc.). Due to its size and complexity, this comprehensive body of data inevitably posed a challenge for the researcher to decipher, organise, analyse and curate in a cohesive way. Therefore, these entangled data sets[100] were initially arranged into broad categories in an online collaborative tool called Miro[101], as shown in Figure 41. This process was based on a methodological approach called “Giga Mapping[102]” by Birger Sevaldson (2011), an extensive mapping technique across many layers, sections and scales that seek to investigate relations between seemingly separate things, categories, and silos. According to Sevaldson (2011), Giga maps are process-oriented tools for visual thinking and understanding complex systems thinking in design. He uses Giga mapping in his teaching as an initial “data dump” by finding and mapping the data into key relations and categories, particularly at the beginning of a project. Using the method of Giga mapping with Miro, I did an extensive and gradual initial data dump of all the resources and findings related to integrating seaweed as part of the landscape-seascape approach to waterfront development in Vejle (as indicated in Figure 41).
Figure 41. Screenshot of the initial data dump of everything relevant about Vejle, seaweed, coastal protection/adaptation, nature-based solutions[103] etc., that are relevant in answering the research questions. The data include screenshots, hyperlinks to URLs and documents, and comments and arrows indicating their interconnections to others (organised in Miro, an online software).
The initial Miro mapping evolved into a more sophisticated, organised, spatial format that could be operable to work with territorial mappings (and other visual mediums), different timeframes and multiple scales. Therefore, another online mapping tool, “Kumu[104]”, was used to reflect the desired scaled systems thinking approach. The intention of using this tool was to go beyond the limitations of static 2D mapping addressed in section 2.2.2.
Interactive Network Mapping – Kumu
The research employs a network mapping tool Kumu as a methodological tool for curating, hosting, and making sense of various complex webs of information that the Vejle case study introduces. The Kumu tool was chosen as a data and geo visualisation (see definitions) tool because it allowed me to compose an interactive map capable of converting complex data sets into maps delineating the relationships between these. In other contexts, Kumu[105] has been used to map the complex structure of personal networks and reveal connections between key players (see Figure 42 for an example of stakeholder mapping). It can also be used to brainstorm complex ideas and relate individual concepts to the bigger picture (Kumu INC, 2011; Sage Ocean, 2022). These mapping tools allow the user to investigate and navigate the complexity using parameters such as categorisations and links. Depending on which parameters one wishes to emphasise, Kumu can reveal and hide connections and nodes[106] by calculating which nodes are the most popular or least popular, thereby reorganising the nodes into different groups. It is also an online tool that can be shared anywhere, anytime, with the capacity to embed various visual mediums such as images, texts, videos, websites, hyperlinks and other information. Finally, a Kumu map can also link to other Kumu maps.
Figure 42. An example of a complex Kumu map of all the stakeholders involved with the Aarhus School of Architecture. It is divided into several categories (i.e. Aarhus School of Architecture’s different research labs, teaching programs, personnel/staff, and collaborators such as universities, municipalities, practitioners, experts and NGOs). The map changes according to the variable you set, such as isolating only the University personnel and representing varying degrees of connections, as shown in the second and the third image above. It can also run analyses to find the nodes with the most connections and many other functions (which can be represented via node size, as shown in the last image). It can also be categorised and tagged into various groups to work through overwhelming and complex data sets. Image credit: Kevin Kuriakose. See this Kumu map: https://kumu.io/BASP-2020/basp#aaa-research-mapping (instructions on how to use the map: https://aarch.dk/en/interactive-map/).
[100] Such as, findings from the GIS data, interviews and Kanten/The Edge design competition entries, state-of-the-art projects around the world, literature reviews of articles, reports, photos, videos, drawings, websites, diagrams, maps, etc.
[101] Miro is a cloud-based collaboration tool for small to midsize organisations. The tool features a digital whiteboard that can be used for research, ideation, building customer journeys and user story maps, wireframing and a range of other collaborative activities. See www.miro.com for more details.
[102] However, Giga-maps are not designed for communication with outside of the designer/creator as it is used as process tools to map complex data (Sevaldson, 2011).
[103] Initial categories of sorting the various relevant information: 1. geography related (i.e. topographical and bathymetrical data for Vejle), 2. municipal documents (i.e. storm surge strategy for Vejle Municipality), 3. historical and cultural infrastructure, 4. other research dissertations that could be useful (i.e. master student works), 5. Urban development models – land reclamation, 6. Sea level rise, storm surge (climate change related), 7. marine life forms (such as seaweed, eelgrass, wetlands, salt marsh).
The initial Miro mapping evolved into a more sophisticated, organised, spatial format that could be operable to work with territorial mappings (and other visual mediums), different timeframes and multiple scales. Therefore, another online mapping tool, “Kumu[1]”, was used to reflect the desired scaled systems thinking approach. The intention of using this tool was to go beyond the limitations of static 2D mapping addressed in section 2.2.2.
[104] Kumu is a network mapping tool primarily used for social network mapping between people, systems or concepts with data analytical tools that help navigate a web of interests, influence and alignment of key players around important issues (Kumu INC, 2011). Go to https://kumu.io/ for more information.
[105] The main use cases for Kumu are: 1. Stakeholder mapping - Explore the complex web of loyalties, interests, influence, and alignment of key players around important issues. 2. Systems mapping - Understand and engage complex systems more effectively using systems maps and causal loop diagrams. 3. Social network mapping – Visualise and capture the structure of personal networks and reveal key players within an organization. 4. Community asset mapping - Keep track of the evolving relationships among community members and resources. 5. Concept mapping - Brainstorm complex ideas and relate individual concepts to the bigger picture (Kumu INC, 2011; Sage Ocean, 2022).
[106] A node is a point in a network or diagram at which lines or pathways intersect or branch. For Figure 42, the nodes are different coloured circles which are embedded with various information by clicking on them.
PREVIOUS
NEXT
By considering the opportunities and limitations of different forms of mapping mentioned throughout section 2.2, further development and refinement of mapping methods are needed in order to “remain capable of taking action in the face of the increasing complexity of design tasks and to be able to develop and negotiate ideas for shaping urban landscapes sustainably” (Seggern and Werner, 2008, p.46). Moreover, new forms of mapping are needed to engage with the immense complex spatial systems that are large-scale, unpredictable and non-linear from long-term horizons with multiple stakeholders with differing interests. It also needs to fill the current lack of established design traditions, approaches or valid design methods towards designing complex, large-scale urban landscape-seascape interventions in the Anthropocene (Seggern and Werner, 2008). Therefore, this research takes inspiration from network mapping to address the increasingly interrelated entanglements in addressing a wicked problem through mapping as a process of discovering all the entities connected to a network, outlined in Figure 40. One of the most notable form of a network map is a sketch from Charles Darwin called the “Tree of life” in the 19th century. His sketch underpins the importance of visualising the understanding of connection across multiple organisms and then portraying the strength of the interaction between species. Figure 40 also shows other influential examples of network maps used throughout human history that also visualise the world as an interconnected network.