Showing posts with label Mocnik. Show all posts
Showing posts with label Mocnik. Show all posts

Wednesday, November 13, 2024

Visualizing Places

Suggested by: Franz-Benjamin Mocnik



Keywords: places, cartography, user testing

Objective: Developing and comparing different cartographic means to display places on a map.

Short description: 

When talking about spatial (and sometimes also non-spatial) entities, we refer to places.  Enschede, the ITC, shopping areas, and our homes are examples of such places for which objective descriptions are often hard to find.  In these cases, the spatial boundaries are usually unclear, and people have different understandings of what constitutes these places.  Independent of this fact, we are able to successfully refer to places in our everyday language, and we use them to conceptualize our environment.  It is, however, still unclear how places can be represented by formal means and visually be conveyed.

The proposed thesis topic seeks to explore opportunities of visually conveying places.  Aalbers (2014) has discussed several examples of maps that were influenced by and have influenced existing geographies.  The maps named by him, however, make only use of simple cartographic means.  Mocnik and Fairbairn (2018) have explored further ways of how to adapt maps in order to convey more idiosynchratic content.  As part of the thesis project, characteristics of places need to be discussed, as well as corresponding visual properties.  This includes the spatial extent of places, emotional attachments, place types, the identity of places, and various types of relations between places.  When representing such a characteristics of a place on the map, particular attention shall be paid to correspondences between the places and their visual counterparts in terms of affordances, structural referencing, and further means to create analogies.  The different ways of representing places shall be compared by user testing, including eyetracking, interviews, and screen logging.

Literature references: 

  • MB Aalbers: Do Maps Make Geography? Part 1: Redlining, Planned Shrinkage, and the Places of Decline. ACME: An International E-Journal for Critical Geographies, 13(4), 2014, 525–556
  • FB Mocnik and D Fairbairn: Maps Telling Stories? The Cartographic Journal 55(1), 2018, 36–57

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Maps Telling Stories

Suggested by: Franz-Benjamin Mocnik



Keywords: storytelling, cartography, user testing

Objective: Implementing and testing modifications to existing cartographic means with respect to their ability to tell stories.

Short description:

Stories often convey emotions, and they convey a narrative that make us understand how it would be to be in the position of the protagonist.  By providing a description of an idiosynchratic experience, stories are more than a formal representation of shared conceptualizations of what happens.  This is in contrast to cartographic representations, which in many cases aim to provide an ‘objective’ view of our environment.  If a story shall be convey by a map, other media are usually included.  For instance, multimedia maps can convey stories by adding pictures, videos, and audio recordings.

Mocnik and Fairbairn (2018) have explored novel ways of how to adapt maps in order to make them more text-alike in their structure, thus hoping for being able to convey stories in more engaging and idosynchratic ways.  This thesis project aims at implementing and testing the proposed and similar cartographic means.  For implementing the cartographic means, either the rendering of maps would need to be adapted, or the depiction of prerendered map tiles would be extended by additional elements using Leaflet, D3.js, and similar technologies.  Then, a story would be chosen and visualized by utilizing the implemented cartographic means.  Finally, the produced visualization would be compared to a textual one.  By making use of suitable techniques, inlcuding eyetracking, interviews, and audio recordings, both the implemented visualization and the textual representation will be evaluated in terms of how well they are able to convey emotions and idiosynchratic views.

Literature references: 

  •  FB Mocnik and D Fairbairn: Maps Telling Stories? The Cartographic Journal 55(1), 2018, 36–57

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Dimension of Geographical Networks

Suggested by: Franz-Benjamin Mocnik


Keywords: spatial networks, dimension, street network, OpenStreetMap

Objective: Developing and implementing algorithms for detecting subnetworks the local network dimension of which is homogeneous.

Short description:

Networks occur virtually everywhere. The World-Wide Web, metabolic networks, and communciation networks are typical examples.  Also in Geography, such networks occur.  Mocnik (2018a) has examined the degree of influence space has on such networks.  He showed, for instance, that transport and road networks, as well as social networks to a lesser degree, are influenced by space.  Further more, the dimension of the space has a strong impact on the topological structure of such a network, which is why a dimension can be assigned to a network.  Besides exposing very similar qualities, street networks in cities are very similar with respect to their dimensionality (Mocnik 2018b).  In order to model such networks, Mocnik (2015a, 2015b) has proposed a spatial network model.

This thesis aims to develop strategies in order to identify subnetworks that expose a similar dimension in every neighbourhood.  That is, a network that is homogeneous and is thus similar to the spatial network model proposed.  Such networks naturally arise as has been discussed at the example of street networks in cities (Mocnik 2018b), and at the example of road networks as multi-layered networks (Mocnik 2018a).  The thesis will pay particular attention to the example of street networks, which can be extracted from the OpenStreetMap dataset, an open and freely available dataset.  As a result of this thesis, it will be tested whether such homogeneous subnetworks have a geographical relevance and can/should be considered to be geographical entities?  Would such an algorithm, for instance, be able to identify cities by their network dimension?



Literature references: 

  • FB Mocnik (2018a): The Polynomial Volume Law of Complex Networks in the Context of Local and Global Optimization. Scientific Reports 8(11274), 2018
  • FB Mocnik (2018b): Dimension as an Invariant of Street Networks. Proceedings of the 7th International Conference on Complex Networks and Their Applications, 2018, 455–457
  • FB Mocnik (2015a): A Scale-Invariant Spatial Graph Model. PhD Thesis. Vienna University of Technology, 2015
  • FB Mocnik, AU Frank (2015b): Modelling Spatial Structures. Proceedings of the 12th Conference on Spatial Information Theory (COSIT), 2015, 44–64

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Prerequisites / qualifications: This topic requires some previous knowledge in network science and a good understanding of algorithms.