News

New paper “Juxtaposing thematic regions derived from spatial and platial user-generated content” has been accepted as a full paper in the COSIT 2017 proceedings. Link

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The GeoKEA research group (http://geokea.ac.nz) in the University of Canterbury department of geography is offering a fully-funded full-time 3 year PhD scholarship in the area of geographic data science. Particular topics of interest in our group include analytics on unstructured geospatial data (such as text and images), geographic information retrieval and exploratory search user interfaces (see e.g., http://frankenplace.com), artificial intelligence and deep learning for geographic knowledge discovery, spatial-temporal digital humanities, and cognitive modelling and geosemantics.

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Ben Adams will be co-organizing the SPHINx 2017 Workshop SPatial Humanities meets Spatial INformation Theory: Space, Place, and Time in Humanities Research, a pre-conference workshop at COSIT 2017.

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New paper “Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis” published in Future Generation Computer Systems. Link

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Selected Publications

This paper introduces Wāhi, the first gazetteer to map entities from the GeoNames database to multiple discrete global grid systems. A gazetteer service is presented that exposes the grid system and the associated gazetteer data as Linked Data. A set of use cases for the discrete global grid gazetteer is discussed.
International Journal of Digital Earth

The intrinsic connection between place, space, and time in narrative texts is the subject of chronotopic literary analysis. We take the notion of the chronotope and apply it to exploratory analysis of unstructured big data. Exploratory chronotopic data analysis provides a data-driven perspective on how place, space, and time are connected in large, crowdsourced text collections. In this study, we processed the English Wikipedia text to find all co-occurrences of named places and dates and discovered that times are linked to places in a large majority of cases. We analyzed these millions of connections between places and dates and discovered a number of interesting trends. Because of the scale of the data involved, we suggest that chronotopic data analysis will lead to the development of new data models and methods for geographic information science and related fields, such as digital humanities.
In GIScience 2016

In this paper we describe the architecture of an interactive thematic map search engine, Frankenplace, designed to facilitate document exploration at the intersection of theme and place. The map interface enables a user to zoom the geographic context of their query in and out, and quickly explore through thousands of search results in a meaningful way. And by combining topic models with geographically contextualized search results, users can discover related topics based on geographic context. Frankenplace utilizes a novel indexing method called geoboost for boosting terms associated with cells on a discrete global grid. The resulting index factors in the geographic scale of the place or feature mentioned in related text, the relative textual scope of the place reference, and the overall importance of the containing document in the document network. The system is currently indexed with over 5 million documents from the web, including the English Wikipedia and online travel blog entries. We demonstrate that Frankenplace can support four distinct types of exploratory search tasks while being adaptive to scale and location of interest.
In WWW 2015

We show in this paper that a reconceptualization of geographical information in terms of Peirce's Pragmatics (specifically firstness, secondness and thirdness) can provide the necessary modeling power for representing situations of data use and data production, and for recognizing that we do not all see and understand in the same way. This in turn provides additional dimensions by which intentions and purpose can be brought into the representation of geographical data. Formally, we propose a generative graphical model for geographic data production through pragmatic description spaces and a pragmatic data description relation. As a simple demonstration of viability, we also show how this model can be used to learn knowledge about the community, the tasks undertaken, and even domain categories, from text descriptions of data and use-cases that are currently available. We show that the knowledge we gain can be used to improve our ability to find fit-for-purpose data.
In GIScience 2014

Recent Publications

More Publications

  • Juxtaposing thematic regions derived from spatial and platial user-generated content

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  • Why good data analysts need to be critical synthesists. Determining the role of semantics in data analysis

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  • A data-synthesis-driven method for detecting and extracting vague cognitive regions

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  • Things and Strings: Improving Place Name Disambiguation from Short Texts by Combining Entity Co-Occurrence with Topic Modeling

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  • Wāhi, a discrete global grid gazetteer built using linked open data

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  • Exploratory Chronotopic Data Analysis

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  • Moon Landing or Safari? A Study of Systematic Errors and their Causes in Geographic Linked Data

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  • We Need to Rethink How We Describe and Organize Spatial Information. Instrumenting and Observing the Community of Users to Improve Data Description and Discovery

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  • Of Oxen and Birds: Is Yik Yak a useful new data source in the geosocial zoo or just another Twitter?

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  • Extracting Place Emotions from Travel Blogs

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Projects

DG3

Discrete global grid Linked Data gazetteer service

People

Ben AdamsBen Adams is a senior lecturer in the Department of Geography at the University of Canterbury. He received a PhD in Computer Science with an emphasis in Cognitive Science from the University of California, Santa Barbara. He has expertise at the intersection of geography, geographic information science, and computer science, including the application of machine learning, text mining, statistical methods on big data, and other high-performance computing tools for geographic analysis. Previously, he worked as a postdoctoral researcher at the National Center for Ecological Analysis and Synthesis in Santa Barbara, CA, USA and more recently as a research fellow at the Centre for eResearch at the University of Auckland.

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