Data is not meaningless. The intention of gathering data always has specific goals which can influence shaping social reality (Koenen, E. et al., 2021, p. 138). The primary drive behind the data collection, as mentioned by historians and anthropologists, is the demand for recording legislative measures and taxes from the ancient social structure (p. 139). For instance, the Master of Knaresborough Workhouse, one of the writers of the Daybook, used an obsequious speech of the working-class record of the daily routine of inmates. According to the record, the writers of the Daybook needed to address and please a committee of 'gentlemen' who supervised the financial situation and management of Workhouses. Considering the meaning and power interactions behind the data, the raw data in traditional media becomes a valuable asset for recording vivid history. There is excellent value in processing the original data with digital technology.
The significance of data processing and classification deserves to be stressed. Data does not exist on its own. Data work with other data, but also concerning processing systems and people (Dourish and Gómez, 2018, p. 1). In terms of visualisation, data must be classified (D'Ignazio and Klein, 2020, p. 103) to be valid. Classification systems are essential for any work (Bowker and Star, 1999). However, beneath the surface of classification systems lie binaries and hierarchies (p. 105). Take gender for example, the feminist logic can be explained by the example of 'colour representing gender', using the distinction between pink and blue as a binary form. In contrast, they avoid reinforcing stereotypes by breaking this cultural convention, using green and purple to make the distinction (p. 113).
In addition, the data animates, explains, provides and shares the story in a way that tells the story. (Gabrys et al., 2016; Sharon and Zandbergen, 2017) Papacharissi uses 'digital orality' to describe how data is embedded in narratives (2015). The most favourable narrative for data is that it requires no additional explanation. However, at the same time, the data is only meaningful if it has a framework for understanding it (Dourish and Gómez, 2018, p. 8). Veel (2018) points out that there is a reconstruction of both data and the narrative constituted in the narrative of data. Considering the object of collection, data collection addresses only narrow issues. Nevertheless, quantitative research is necessary because more data can make it more challenging to become aware of some established issues(D'Ignazio and Klein, p. 98).
Historicising data helps explore data (fication) in connection to the everchanging social status and the media environments (Koenen et al., 2021, p. 151). Moreover, we can see a more comprehensive prospect of datafication from its ability to seize details from digital sources and reveal patterns behind the vast data. For example, in logistics, without datafication, monitoring data flows to organise production and distribution across space and time within global commodity chains would be impossible (Cowen, 2015 cited in Mejias and Couldry, 2019). At the same time, the imbalance in the data collection process must be addressed. As D'lgnazio and Klein (2020) suggest, power inequalities exist ubiquitously when there is data collection and the classes within it. Due to these imbalances, the potential benefits and harms of whom will receive and the context of the collection needs to be considered when proceeding with data collection.
Media research must be mindful of the complexity of the interaction between new and old media. On what basis, for what purpose and with what consequences do people distinguish between old and new media when understanding media (Menke, M. and Schwarzenegger, C, 2019, p. 669). Old or new is always relative, as it depends on individual and generational temporalities of comparison, media ideologies, and the context of the moment (Menke and Schwarzenegger, 2019, p. 665). Media are often reintroduced or imitated by new technologies (Menke and Schwarzenegger, 2019，p. 659) and then provide new features and more ways of communication than in the past (Menke and Schwarzenegger, 2019, p.667). New media technologies are transforming communication and profoundly reshaping how people connect and interact. As a cultural tool, data reconstruct critical questions about what constitutes knowledge, the process of research, and how we should engage with information, as Boyd et al. suggests (2012, p. 665). In the past, the master was the only person to record things that happened in the workhouse. However, every "inmate" can record their life using new media tools. On the other hand, Simone Natale believes "there are no old media". As newness and oldness are constantly negotiated in media circuits of value, our perception and imagination of technological change might be more indicative of the oldness of media than the media themselves (2016, p. 586).
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