Social and Cultural Informatics (SCIP)

Overview

The Social and Cultural Informatics (SCIP) data team are here to support you in your research. They specialise in providing research consultancy services at the formative stages of a grant application or research project proposal. They provide digital expertise to research projects, helping you to grasp digital tools and methodologies.

Associate Professor Nick Thieberger
Associate Professor Nick Thieberger

Associate Professor Nick Thieberger

Nick Thieberger is an Associate Professor in Linguistics. He is particularly interested in developing methods for making better records of all of the world's many languages. This involves training new students in concepts of linguistic data management, the creation of new tools, and the use of existing records for new research.

He has worked with the Pacific and Regional Archive for Digital Sources in Endangered Cultures (PARADISEC) since its inception in 2003, it is an archive that holds 12,000 hours of audio records in 1229 languages. He built the Digital Daisy Bates pages using TEI XML to display 23,000 pages of manuscript material in Australian Indigenous languages. He wrote a grammar of Nafsan (central Vanuatu) and continues to work on a dictionary of that language.

Nick Thieberger academic profile

Greg D’Arcy

Research Data Analyst/Platform Administrator

Greg is a highly experienced digital professional having worked in roles such as digital project management, data analytics, website development, online communications and training within the research and education sectors. His current interests include data analysis, cloud computing, web publishing, text mining /APIs and current approaches to open science tools.


Amanda Belton

Data scientist

Amanda Belton is a data scientist working with education and arts researchers to visualise research information. Amanda works with playful approaches and empathetic design principles to communicate research data visually into the digital realm, with a keen interest in animation and mixed reality.


Dr Trent Ryan

Data scientist

Trent specialises in computational methods and analysis. His interests include data extraction and wrangling, social networks, text mining, machine learning, and statistical programming. He has worked on several projects examining the impact of social, cultural, and economic factors on cultural industries and aesthetic careers, and continues to be inspired by new and emerging methodologies designed to make sense of complex social phenomena. He is available for one-on-one research consultations on Thursdays and Fridays, and by appointment.