Social Analytics Lab

Storing, managing and analysing sensitive data for research and teaching

The Social Analytics Lab (SAL) is a custom-built, secure research facility housed at Griffith University to store, manage and analyse sensitive administrative data for research and teaching. Underpinned by industry standard security protocols that enable the storage of individual level data, SAL offers a unique platform where cutting edge academic research can be applied to the complex real world problems of a rapidly evolving 21st-century society.

Who can use the Social Analytics Lab?

SAL has been purpose built to house large highly sensitive datasets. These datasets are protected by a range of industry standard security protocols and remain the property of the data providers. Consequently, access to these datasets is tightly controlled. SAL is open to researchers from any national or international academic institution however all users are required to undergo an induction process to gain entry into the lab.

Researchers using this facility are expected to be highly skilled in data manipulation and analysis. In addition, they will understand the importance of treating data ethically and with integrity. Finally, in line with SAL’s vision, all research supported by the lab should provide meaningful insight for those who provide the data.

How can I use the Social Analytics Lab?

If you would like to discuss how your research could benefit from housing data within the SAL, please contact socialanalyticslab@griffith.edu.au.

If you are interested in developing a research project using data currently held in SAL, you will need to complete an application and provide a brief project description, which will be considered by the SAL Management Committee. All access protocols are on a dataset–by-dataset basis, and depend on standing agreements between Griffith and data providers.

Please note, all data is held physically onsite within SAL.

WEBINAR: A discussion about Griffith University's Social Analytics Lab

26 May 2022 - Social Analytics Lab Webinar

SAL enables a new breed of impact-driven social science research, applying cutting edge analytics to large scale administrative data sets to solve complex real world problems. SAL has been purpose-built to house large, highly sensitive datasets. These data are protected by a range of industry standard security protocols and remain the property of the data providers. Researchers from any national or international academic institution are welcome to apply for access to SAL.

Presenters discuss what SAL is, who can access it and how, and its current data holdings. Researchers describe how they have used SAL data and the types of research it can be useful for.

Social Analytics Lab Data:

Queensland Police Service:

Over 10 years of individual level crime incident data occurring in Queensland from 2008 to 2021 The data includes details of an occurrence such as time and date, location, related offences, outcome, text description of the incident, details of stolen property, and drug, alcohol, and DV flags. As well as offender and victim information including age, gender and ATSI status.

Queensland Cross-sector Research Collaboration:

This is linked cohort data obtained from an ARC funded Queensland Cross-sector Research Collaboration (QCRC) project to examine the relationship between mental illness and offending over the life course. It includes records for 1983, 1984, and 1990 Queensland birth cohorts from various Queensland government departments such as police, courts, corrections, child safety, youth justice, births, deaths and marriages, and health. These records have been linked by the Office of the Government Statistician and Queensland Health and have a single person identification number across the databases.

Queensland Corrective Services:

QCS provides ABS National Prisoner Census data for prisoners in Queensland and QCS prisoner and community corrections data from July 2008 to June 2019, updated annually. Prisoner census data includes details such as a single person identifier, prison location, gender, date of birth, indigenous status, last known address, employment and education status. As well as sentencing details such as release date, breaches of parole or escape, principal offence, and security status.

The prisoner and community corrections includes data on risk-of-reoffending scores, movements to or from custody or community corrections, community supervision orders and offences, legal status history, custodial sentence calculation histories, custodial sentenced offences, risk/needs assessments, initial surveillance assessments, and incidents.

Current and Past Projects utilising Social Analytics Lab Data:

Offending and mental illness

Offending and mental illness: Understanding the experiences of Australian First Nations People across the life course

James Ogilvie

The project aims to address the gaps in knowledge regarding the relationship between mental illness and offending for Indigenous Australians. It is well established, both in Australia and internationally, that mental health problems are highly prevalent among people who encounter the criminal justice system. However, little is known about the impact of race on this relationship or about the sequencing and dynamic nature of the relationship across the life course.

In Australia, understanding the impact of race on the relationship between offending and mental illness will have significant implications for policy development, given the documented overrepresentation of Indigenous Australians at all levels of the criminal justice system. The project is based on an analysis of linked criminal justice and health data drawn from the Queensland Cross-sector Research Collaboration (QCRC) repository for individuals born in Queensland in 1983, 1984 and 1990. This data allows for examination of how offending and mental illness interact over time, including order, timing and sequence of onset; with the aim of identifying potential points of intervention during vulnerable time periods. Findings from the project will be crucial to assist in guiding policy and culturally informed and Indigenous-led efforts to reduce overrepresentation.

Intergenerational Continuity of Maltreatment: An Empirical Investigation

Emma McKenzie

This thesis examines the intergenerational (dis)continuity of child maltreatment. A maltreatment victimisation history is argued to be the most significant risk factor for becoming a maltreater, however, our understanding about who engages in maltreating behaviours, and why, is limited. The existing literature is generally plagued by significant methodological limitations. What we do know is that the majority of individuals with a victimisation history do not subsequently maltreat.

The research utilises linked prospective longitudinal population-based administrative data from the Queensland Cross-sector Research Collaboration (QCRC) data repository, which includes life course data reflecting all QLD system contacts of individuals born in 1983, 1984 and 1990. This data allows the examination of individuals’ contacts with the child protection system as a childhood victim and as a person responsible for harm, as well as other life course experiences (i.e., criminal offending, mental health, domestic violence). This research provides an opportunity to explore risk and protective factors and subsequent prevention/intervention opportunities.

Female Pathways to Offending: Investigating Precursors to Promote Prevention

Ayda Kuluk

Female offending is rapidly growing and is a key policy issue. However, there is limited longitudinal research on the different female offending trajectories and how these are influenced by risk and protective factors across the life-course. This thesis aims to contribute to a better understanding of the patterns and precursors of female offending as well as examining significant gender differences in the risk and protective factors associated with offending across the life-course. This thesis will use the Queensland population-based, longitudinal linked administrative dataset stored in the Social Analytics Lab (SAL) at Griffith University.

A range of databases stored in SAL will be explored, such as the Registry of Births, Deaths and Marriages, contacts with the child protection and criminal justice systems, domestic violence civil system, and health and mental health system. The results of this thesis will assist in informing effective gender-specific and gender-neutral prevention and intervention policies and practices.

Understanding the complexity of child maltreatment and domestic violence

Brigitte Gilbert

This project examined the contact domestic violence (DV) victims and DV perpetrators have with the systems that respond to child maltreatment and criminal offending. This was achieved by using population-based linked administrative data from the Queensland Cross-sector Research Collaboration. Utilising longitudinal data from individuals born in Queensland in 1983 and 1984, the results of this thesis revealed a significant overlap in the involvement of individuals with DV (perpetration and victimisation), child maltreatment (perpetration and victimisation), and criminal offending.

Further, the co-occurrence of DV, child maltreatment, and criminal offending was significantly impacted by gender, race (Indigenous status), and parental status. The findings demonstrate the need for holistic and collaborative responses by service systems for individuals involved with DV, child maltreatment, and criminal offending.

Other Projects: