Photo by Franki Chamaki on Unsplash


In early 2018, Google has launched a website titled “Me Too Rising”

[1] that visualises trends of web searches of across space and time at a global scale, noting cities where a markedly high proportion of total searches are for “MeToo”. Me Too is a movement founded in 2006 by African-American activist Tarana Burke to raise awareness of the pervasiveness sexual assault [2], which spread rapidly in 2017 as social media users adopted the hashtag #MeToo to share their experiences of sexual assault. Using a tool like this immediately highlights regions of significant search activity, as clear evidence of the power and potential of technology for facilitating, growing and furthering movements [3].


Over four months from November 2018 to February 2019, a project – funded by the Victorian government – developed by digital mapping company Crowdspot and Monash University’s Space Gender Communication (XYX) Lab, collected data to map experiences of gender inequity and equity in the Darebin and Milton council areas in the Melbourne region. The Gender Equality Map will allow urban planners to better understand “patterns of exclusion and inclusion” [4], providing an indication of the scale and extent of gender inequality based on contributions by people of all genders. This example of crowdsourced mapping is not the first of its kind: the Free to Be project has been a platform for women and girls to indicate places in Melbourne and Sydney where they have felt unsafe – including providing anonymous descriptions about particular incidents [5]. (It is important to consider here that the majority of sexual violence is perpetrated by someone that the victim/survivor knows, as opposed to a stranger [6]. Planning for safer public spaces is not alone enough to end violence against women, and forms part of a solution that ultimately addresses the underlying issues in society that lead to perpetrators’ acts.)


The value of collecting data is that it allows for the aggregation of experiences and incidences, to identify patterns and relationships across space and time. Correlations between certain events and experiences of violence can reveal factors relating to violence: the link between family violence and major sporting events and seasonal holidays is clear and well-known [7], so much that police and services anticipate and prepare for spikes in calls they receive for family violence-related matters [8,9]. The uneven distribution of violence due to the compounded experiences of marginalisation with gender-based violence faced by Aboriginal and Torres Strait Islander women, immigrant and refugee women, women with disabilities, LGBTIQ+ women, and young and elder women, is also highlighted and can be better understood and studied through demographic analysis of data. Data also reveals the sheer scale of violence against women: knowing, thanks to extensive data collection and analysis, that one in three women have experienced violence since the age of fifteen drives home the prevalence and severity of the problem [10], emphasising the urgency with which action must be taken. In theory, through analysing data relating to violence against women, support services can be planned for accordingly, and policies implemented to address the underlying patterns and issues that are identified.


However, there is a grim side to data’s relationship with violence against women. The power of data and technology can also be used by perpetrators to harass, intimidate and abuse. A recent case in Queensland where a police officer breached privacy and shared the details of a victim of domestic violence to an abusive former partner [11] is an example of this risk. The Australian Government’s online My Health Record [12] and myGov portal [13] have come under scrutiny for the possible ease of access perpetrators of violence have to a wide range of personal details and records, all through a single log-in. Moreover, surveillance in the name of national security is becoming increasingly prevalent [14], where people are unaware of what data or footage is being collected, for what purposes, and where it is stored. Personal information may be accessed and used by perpetrators of family violence. While there is sometimes the option to choose not to provide their information to online databases such as My Health Record, having an opt-out system, as compared to an opt-in one, may place victims/survivors who may not have access to and/or proficiency with technology (such as older people) in a position where they are unable to exercise their choice not to participate. A shift towards online databases and increasing dependence on the Internet may in fact place older people at greater risk of online abuse as well [15].


It is therefore all the more crucial that service providers and database managers ensure confidentiality of data and promote the use of security measures such as two-factor authentication [16] in order to maintain the safety of technology users. Moreover, any data collection taking place should involve transparency, and be accompanied by support on technological literacy to reduce the risk of online abuse.


Statistics on violence against women are only as good as the available data. People and groups of people who face barriers in reporting experiences of violence and/or seeking support are underrepresented in data collected by the police and/or service providers, and data available on violence against women is therefore likely to be an underestimation of the actual prevalence of such experiences. Incident-based reporting, employed by police, can fail to pick up on patterns of abuse, misrepresenting the ongoing and serious nature of control and coercion. Even statistical surveys such as those conducted by the Australian Bureau of Statistics have their limitations [17]. The benefits of data mentioned above, such as identifying patterns, can only be fully realised when barriers to reporting are broken down, allowing for a more holistic and comprehensive picture.

It is also important to consider that  data can be misconstrued or reported in a way that fits the agenda of whoever is presenting it; the very same data can be used to reach different (at time opposing) conclusions, depending on subtle phrasing differences [18]. We should be aware of these complexities in the way we read data that we may come across scrolling through social media or reading the news.


Data is neither essentially helpful nor inherently harmful to the goal of ending violence against women: rather, data’s value depends on how it is collected, used, and presented. Data, like many other things, can be used to perpetuate abuse and harmful attitudes that promote violence. At the same time, sound data is vital for understanding the issues and investigating possible responses. Individual and collective efforts to promote safety can be strengthened by understanding more about data, and by developing ethical, critical approaches to its use.


Sumithri Venketasubramanian

AWAVA Admin & Comms Assistant




[1] Google Trends, 2018. Me Too Rising. Google. Online. Accessed 30 October 2018. Available at:


[2] Brockes, E., 2018. Me Too founder Tarana Burke: ‘You have to use your privilege to serve other people’. The Guardian. 15 January. Online. Accessed 30 October 2018. Available at:


[3] Tripathi, R., 2018. #MeToo has arrived in India, and it’s changing how technology is used to fight injustice. The Conversation. 27 October. Online. Accessed 30 October 2018. Available at:


[4] Precel, N., 2018. Know somewhere that’s not gender equitable? Crown mapping aims to help. The Sydney Morning Herald. 28 October. Online. Accessed 30 October 2018. Available at:


[5] Kalms, N., 2018. To design safer parks for women, city planners must listen to their stories. The Conversation. 18 June. Online. Accessed 30 October 2018. Available at:


[6] Our Watch, n.d. Myths about violence. Our Watch. Online. Accessed 30 October 2018. Available at:


[7] Pescud, M., 2018. Whether teams win or lose, sporting events lead to spikes in violence against women and children. The Conversation. 13 July. Online. Accessed 30 October 2018. Available at:


[8] Noonan, A., 2018. AFL grand final night one of the busiest nights for family violence, Victoria Police chief says. ABC News. 27 September. Online. Accessed 30 October 2018. Available at:


[9] Wainwright, S., 2017. Domestic violence spikes over summer, authorities warn, with alcohol, festive stress blamed. ABC News. 28 December. Online. Accessed 11 December 2018. Available at:


[10] Our Watch, n.d. Facts and figures. Our Watch. Online. Accessed 30 October 2018. Available at:


[11] Smee, B., 2018. Queensland police constable told to give evidence in domestic violence privacy case. The Guardian. 7 November. Online. Accessed 9 November 2018. Available at:


[12] Moore, T., 2018. ‘Serious’ risks of domestic violence in new online health system. The Brisbane Times. 23 July. Online. Accessed 9 November 2018. Available at:


[13] Hendry, M., 2018. myGov portal can be used by abusive partners to track down victims, Government warns. ABC News. 18 October. Online. Accessed 9 November 2018. Available at:


[14] Lidberg, J., Muller, D., 2018. Book: In the name of security – secrecy, surveillance and journalism. The Conversation. 5 November. Online. Accessed 9 November 2018. Available at:


[15] Balg, M., 2013. Elder Abuse and Technology. Huffington Post. 18 July. Online. Accessed 18 January 2019. Available at:


[16] Australian Government, n.d. Two-factor authentication. Stay Smart Online. Online. Accessed 9 November 2018. Available at:


[17] Mitra-Kahn, T., Newbigin, C., Hardefeldt, S., 2016. Invisible women, invisible violence: Understanding and improving data on the experiences of domestic and family violence and sexual assault for diverse groups of women: State of knowledge paper. Sydney: ANROWS. Online. Accessed 11 December 2018. Available at:-


[18] McPhedran, S., 2018. FactCheck: is domestic violence the leading preventable cause of death and illness for women aged 18 to 44? The Conversation. 16 April. Online. Accessed 9 November 2018. Available at: