Friday, October 23, 3:00 p.m.
Center for Social Complexity Suite
Research Hall, Third Floor

Utilizing Netlogo's GIS and CSV Extensions to Create Data-Driven Agent-Based Models

Melanie Swartz, PhD Student
Computational Social Science Program
Department of Computational and Data Sciences
George Mason University

ABSTRACT: Incorporating spatial data and detailed attribute data into agent-based models can help make a model less abstract and more realistic. Spatial data can support the application of a model to a specific geographic area or case study of interest. This hand-on seminar will provide you familiarity with the Netlogo GIS and CSV extensions available in the latest Netlogo version (5.2.1) and guide you through the process to incorporate spatial and tabular data into an agent-based model. This talk will cover the basics of how to get data into your model as well as more advanced topics on overcoming some of the challenges you may encounter when trying to work with spatial data in Netlogo. In addition, some of the pros and cons of using data in a model will be discussed. This will be an interactive, and fun opportunity to become more familiar with how to incorporate data into your Netlogo models. You will need the latest version of Netlogo in order to utilize the extensions. Although QGIS is not needed for this seminar, it is referenced during the tutorial and is useful for pre-processing GIS data to work with Netlogo.

Netlogo can be downloaded here:

You may also want to download and install QGIS.
QGIS can be downloaded here: