Data divide

The data divide is the unequal relationship between those capable of collecting, storing, mining, and general management of immense volumes of data, and those whose data is collected. Using the framework of the digital divide, the data divide posits that the evolving nature of data and big data has created divisions and inequalities in data ownership, access, analysis, collection, and the manipulation of personal data generated by information and communications technologies (ICTs).

Theoretical Framework

Early research in the digital divide concentrated on the divisions of access to information and digital technologies, demonstrating a split between the “haves” and the “have-nots:” those able to access and use digital technologies versus those who do not. Divisions were found to occur along multiple lines of inequality, including education, economic income, race, and gender. The digital divide has several dimensions of access, including access to equipment or hardware, ownership, support networks, digital literacy, and skill to use/navigate user interfaces, and so on. The Ada Lovelace Institute notes that the digital divide has exacerbated a data divide. As a result, the dimensions of access present withing the digital divide are still present within the data divide. The data divide additionally puts in contrast the "haves" who have access to large-scale datasets and the "have-notes" who do not have access to large-scale datasets nor the capability to navigate them. For example, private companies, often social media companies, are the only ones who have access to extensive social data. boyd and Crawford suggest divisions are also emphasized through research and universities: well-funded universities can buy access to datasets and the students who attend would be more likely to be bridged into work within the same social media companies, while less prestigious institutions would be less likely to afford their students the same opportunities.

During the COVID-19 Pandemic

The COVID-19 pandemic resulted in governments worldwide issuing stay-at-home orders, lockdowns, quarantines, restrictions, and closures. Interruptions to schooling, work, business, and other public service operations caused a massive shift to moving otherwise in-person activities online. Operations like doctor’s visits, online schooling, shipping, and remote working require access to high-speed or broadband internet access and digital technologies. This mass adoption of data-driven digital technologies is what the Ada Lovelace Institute describes as a digital surge. In a report with the Health Foundation, the Ada Lovelace Institute found the four key elements that emerged through a public attitudes survey: a data divide based on access to data-driven technologies, a data divide based on awareness and skill, a data divide based on comfort with using health-related tracking apps, and a data divide based on choosing not to use health-tracking apps. In this, the Ada Lovelace Institute stressed the data divide in users not being able to access data that may benefit them and the dangers of not being represented to address health inequalities.

Aspects

Infrastructure

Smart city infrastructures are designed in ways that sensors facilitated by big data technologies can capture information to manage issues in urban city centers. Several technologies are enabled across municipalities which allow them to monitor systems, services, and other forms of infrastructure. However, many of these smart city systems do not share their processes with the public. In this sense, the data divide is represented by governments capturing real-time data on citizens, whose data enables these same systems. Smart cities claim to assist the public but has been critiqued for putting capital and government needs over citizens.

Skills and Digital Literacy

The data divide consists of the lack of knowledge on how to make use of large-scale datasets when enabled within new work environments or communities without proper knowledge sharing or training. For example, failures to adopt new technologies into key industries such as agriculture represents aspects in both the digital and data divide. Lack of data literacy can lead to data deluges – the burden of having and overwhelming amount of data without the capability to extract any meaningful information from datasets.

Data activists and information professionals do have the ability to help bridge the divide through social action including crowdsourcing, citizen science, data cooperatives, hackathons, and civic hacking. These events seek to disrupt and challenge the status quo by cooperating with citizens to better understand quality of access, raise awareness, and allow citizens to generate data for their own uses.

Implications

While the data divide may seem trivial in comparison to the digital divide, a lack of collected information can create disparities which can eventually lead to information poverty. Information poverty stems from a lack of data about a given concept, where the data poverty can have a cumulative effect. This can snowball from individuals to governments on a national scale. For example, a 2007 report from the World Health Organization shows that health information is one of the six fundamental building blocks of a well-functioning health system. Access to quality health data is essential to resolving outbreaks, sicknesses, or other disparities in health; however, many countries, particularly in the Global South, do not have access to the relevant data sources that would allow them to otherwise address health inequities.