More about the session:

This session aims to bring together researchers to report on progress in diverse types of automata systems in social simulation. We encourage the submission of theoretical, experimental, methodological and application papers related to Cellular Automata (CA) and Agent‐Based Modelling (ABM). Papers may include, but are not limited to: 

• Artificial social systems.
• Agents and social networks.
• Modelling complexity in social simulations.
• Large scale social simulation.
• Social behaviour, social actions and interactions.
• Models of competition, cooperation and negotiation.
• Multi‐agent evolution: adaptation and learning.
• Hybrid automata models.
• Validation and verification of simulation results and simulation systems.
• Novel approaches to visualisation 

The GIScRG will provide one bursary for this session, sponsored by the GIScRG for a paper (co-)authored by a postgraduate student; priority will be given to postgraduate students also delivering the paper. The bursary will cover the reduced conference fee for the student for the duration of the conference. It is a requirement that the student is an RGS-IBG Postgraduate Fellow at the time the bursary is awarded [Annual membership costs from £27 (with no joining fee)].

Titles and abstracts (no longer than 250 words) should be emailed to Alison Heppenstall (a.j.heppenstall[AT]leeds.ac.uk), Mike Batty (m.batty[AT]ucl.ac.uk) and Mark Birkin (m.h.birkin[AT]leeds.ac.uk) by Friday 16th December 2011. Notification of acceptance will be given by mid-January 2012.

A wide number of public and private repositories of digital data are participating in the challenge.  Applicants will form international teams from at least two of the participating countries.  Winning teams will receive grants from two or more of the funding agencies and, two years later, will be invited to show off their work at a special conference sponsored by the eight funders.  Read more on the Digging into Data website,  http://www.diggingintodata.org/

The term “Open Data” refers to the philosophical and methodological approach to the democratization of data enabling citizens to access and create value through the reuse of public sector information. Today, Open Data is gathering momentum and forms part of a global movement linked to Open Access and comparable to other Open movements such as Open Source.

Today, the Open Data movement has created great excitement in the developer community with a seemingly endless stream of novel and innovative applications, tools and visualizations that repurposes and enriches public data.

However, while Open Data gives rise to many new opportunities it also poses many challenges. As Boyd (2010) states, access to public information to provide transparency represents only the first step to a more informed citizenry. The success of Open Data will depend in part upon addressing existing barriers to access which encompasses issues such as digital inclusion and information literacy. As such, there is much work still to do to make this promised future happen.

This special feature in the Journal of Spatial Information Science aims to bring together some of the key developers, academics and writers on Open Data to document its lineage, debate its philosophy and methods and to envision its future. Contributions are welcome from any source, and in any style appropriate to the arguments being made.

The deadline for the submission of full research articles is 30th June 2011.  Articles will be subject to the normal JOSIS peer review process. For more details of the submission process CLICK HERE.

Chair – Dr Seraphim Alvanides
Secretary – James Cheshire
Conference Coordinator – Dr Yi Gong
Prizes and Awards Coordinator – Dr Joana Barros
Postgraduate Representative – Tom Burgoine

The Transactions in GIS website can be found here:

http://www.wiley.com/bw/journal.asp?ref=1361-1682

The abstract of the dissertation appears below:

Marine ecosystems contribute significantly to global biodiversity, yet are under threat from both natural and human induced disturbances. Designing conservation strategies requires, as a first step, mapping these ecosystems. However, in situ mapping can be difficult due to the highly dynamic nature of the marine environment. Because wave exposure is known to play a major role in shaping marine ecosystems, it offers a potentially useful proxy variable for mapping them. However, in situ measurement of wave exposure is logistically difficult over large areas. Additionally, numerical wave models are limited to deep water, and are complex and time consuming to run. A Geographic Information System (GIS) based cartographic wave exposure model that measures the relative exposure of a site on the basis of its fetch length provides a simpler and faster alternative.

The academic literature describes a wide variety of cartographic exposure models, all designed for different purposes and study areas. Despite the fact that these models can be computationally intensive, their sensitivity to parameter setup has yet to be tested. Bringing these together within a common modelling framework where results can be standardised makes it possible to do such testing, and eventually to determine an appropriate model setup for a given study area and purpose. To that end, this study presents a generic modelling framework which integrates and extends existing relative wave exposure modelling tools within the ArcGIS programming environment (GREMO). It then uses this framework to assess the sensitivity of relative wave exposure models to key parameter settings, and outlines a conceptual framework for developing methods for parameter optimisation. The sensitivity analysis demonstrated that relative wave exposure model processing times and wave exposure estimates are influenced by how key model parameters are set in complex ways, and that this varies based on the spatial arrangement of waveblocking obstacles within a study area. This justifies further work to investigate sensitivity to unravel these complex interactions, and to develop tools to help determine optimal, or at least feasible, parameter settings for a given study area. Along with this, the conceptual framework for parameter optimisation outlined a range of tools which could be further developed to assist with this. For example, it may be that conditions across a given study area are not homogeneous, thus requiring division into sub-areas where different parameter settings can be applied. As a new integrated modelling environment for relative wave exposure, GREMO facilitates much needed sensitivity testings of these models as well as promoting the use of a mixed models / model comparison approach. Further development of GREMO that would make it even more useful include: (1) how to reduce its computational demand; (2) how to estimate settings for additional input parameters; (3) implementation of the conceptual framework for parameter optimisation; (4) further model verification, particularly of its spatial aspects; and (5) model validation.

We look forward to receiving your entries for next year!

Date: 28th Oct at 1700 GMT

Title: A dynamic social network model for disease transmission.

Speaker: Ling Bian (Buffalo)

Chair: Kirk Harland (Leeds)

The seminars are open to all. For details of how to join the e-seminar using the Marratech™ video conferencing environment, and further seminars in the same series, see: http://www.wun.ac.uk/ggisa/seminars.html

Dave Unwin (d.unwin@wun.ac.uk) WUN Global GISc Academy Coordinator
Steve Carver (s.j.carver@leeds.ac.uk) University of Leeds