Martin Tomko

Experiential Hierarchies of Streets

Mental representations of spatial knowledge are organized hierarchically. Among people familiar with an urban environment, common spatial knowledge from these spatial mental representations enables successful communication of place and route descriptions, consisting of hierarchically-ordered references to prominent spatial feature s, such as streets. The more prominent a street is, the more likely it is to be known by the wayfinder rec eiving the directions. The automated construction of such descriptions therefore re quires hierarchical data models ranking streets in street networks. This paper explores the re asons of overlaps in the content and hierarchical organization of common spatial knowledge among locals. We introduce a novel measure allowing to rank streets in a street network. This ranking allows to construct experiential hierarchies reflecting the shared exper ience of the streets in a city. The measure is derived from network connectivity measures, and takes into account the structure of the street network as well as the higher-order partition of the urban space into suburbs.

Landmark hierarchies in context

We are interested in the generation of distinguishing place or route descriptions for urban environments. Such descriptions require a hierarchical model of the discourse, the elements of the city. We postulate that cognitive hierarchies, as used in human communication, can be sufficiently reflected in machine-generated hierarchies. In this paper we (a) propose a computational model for the generation of a hierarchy of one of these elements of the city—landmarks—and (b) demonstrate that a set of filter rules applied on this hierarchy derives distinguishing route descriptions from spatial context.

Pragmatic Construction of Destination Descriptions for Urban Environments

Abstract Destination descriptions are route descriptions focusing on the “where” of the destination instead of the “how” to reach it. They provide first a coarse reference to the destination, and then increasingly more detailed ones as the description proceeds. We introduce a definition of destination descriptions, along with an analysis of the construction and interpretation of destination descriptions grounded in pragmatic communication theory. We present a formal model enabling the selection of references for destination descriptions from models of experiential hierarchies of urban environments. This model generates route directions for people with some knowledge of the environment. Destination descriptions are usually shorter and we conjecture that the cognitive workload required during their use is lower than for equivalent turn-based directions.

A Dialog-Driven Process of Generating Route Directions

Humans adapt the instructions provided in route directions to the assumed spatial knowledge of the receivers; the majority of route directions is provided to wayfinders with at least partial spatial knowledge of the environment. However, today’s navigation systems assume no a-priori knowledge. Most of current research addresses this by exploring means to personalize assistance through the capture of knowledge about individual users. Accordingly, such systems require an extended learning phase. In this paper, an approach to adaptive route directions based on a combination of turn-by-turn directions and destination descriptions is presented. This approach does not rely on information on a wayfinder’s previous knowledge. Instead, a wayfinder can adjust the type and detail of the presented information via dialog. The paper focuses on the problem formalization and its algorithmic realization; the approach is generic with respect to the modality of the actual dialog (e.g., verbal or key-press based computer interfaces). The paper provides a contribution towards non-static, adaptive route direction services.

Recursive construction of granular route directions

People give route directions to persons who are familiar with the environment typically by referring to elements of the city of varying granularity—what we call granular route directions. This is in contrast to current navigation services, which produce directions of constant granularity. In granular route directions the detail of the description is adapted to some relations between the start and target of the route. The references to elements of the city are aggregated to a referring expression respecting the conversation maxims formulated by Grice. We demonstrate how granular route directions can be automatically constructed by selecting appropriate elements of the city from a hierarchical city structure, and we further demonstrate that the process is based on a recursive application of a small set of topological rules.

From Descriptions to Depictions: A Conceptual Framework

People use verbal descriptions and graphical depictions to communicate spatial information, thus externalizing their spatial mental representations. In many situations, such as in emergency response, the ability to translate the content of verbal descriptions into a sketch map could greatly assist with the interpretation of the message. In this paper, we present an outline of a semi-automatic framework enabling seamless transition between verbal descriptions and graphical sketches of precinct-scale urban environments. The proposed framework relies on a three-step approach: NL parsing, with spatial named entity and spatial relation recognition in natural language text; the construction of a spatial Property Graph capturing the spatial relationships between pairs of entities; and the sketch drawing step where the identified entities are dynamically placed on a canvas in a manner that minimizes conflicts between the verbalized spatial relationships, thus providing a plausible representation of the described environment. The approach is manually demonstrated on a natural language description of a university campus, and the opportunities and challenges of the suggested framework are discussed. The paper concludes by highlighting the contributions of the framework and by providing insights for its actual implementation.

The Australia urban research gateway

The

The Online What if? Planning Support System

20m Australian Urban Research Infrastructure Network (AURIN) project (www.aurin.org.au) began in July 2010. AURIN has been tasked with developing a secure, Web‐based virtual environment (e‐Infrastructure) offering seamless, secure access to diverse, distributed and extremely heterogeneous data sets from numerous agencies with an extensive portfolio of targeted analytical and visualization tools. This is being provisioned for Australia‐wide urban and built environment researchers – itself a highly heterogeneous collection of research communities with diverse demands, through a unified urban research gateway. This paper describes these demands and how the e‐Infrastructure and gateway is being designed and implemented to accommodate this diversity of requirements, both from the user/researcher perspective and from the data provider perspective. The scaling of the infrastructure is presented and the way in which it copes with the spectrum of big data challenges (volume, veracity, variability and velocity) and associated big data analytics. The utility of the e‐Infrastructure is also demonstrated through a range of scenarios illustrating and reflecting the interdisciplinary urban research now possible. Copyright

Towards an e-Infrastructure for Urban Research across Australia

The chapter introduces the Online What if? (OWI) GIS-based planning support system, which is being made available through the Australian Urban Research Infrastructure Network (AURIN). AURIN has been established to provide an advanced information infrastructure to support discipline-specific and multi-disciplinary research and promote sustainable urban development in Australia. OWI is an open source online version of the widely used desktop What if? planning support system developed by Klosterman (1999). OWI enables a range of end users to create and explore what if? land use change scenarios. This chapter discusses OWI in the context of a demonstrator case study in Hervey Bay, Queensland, and introduces future applications of this collaborative planning tool to support the sustainable planning of cities in Australia.

Decentralized orchestration of data-centric workflows in Cloud environments

Many challenges facing urban and built environment researchers stem from the complexity and diversity of the urban data landscape. This landscape is typified by multiple independent organizations each holding a variety of heterogeneous data sets of relevance to the urban community. Furthermore, urban research itself is diverse and multi-faceted covering areas as disparate as health, population demographics, logistics, energy and water usage, through to socio-economic indicators associated with communities. The Australian Urban Research Infrastructure Network (AURIN) project (www.aurin.org.au) is tasked with developing an e-Infrastructure through which a range of urban and built environment research areas will be supported. This will be achieved through development and support of a common (underpinning) e-Infrastructure. This paper outlines the requirements and design principles of the e-Infrastructure and how it aims to provide seamless, secure access to diverse, distributed data sets and tools of relevance to the urban research community. We also describe the initial case studies and their implementation that are currently shaping this e-Infrastructure.