SUMMARY: GENRE HYBRIDITY IN DATABASES

Database design indeed inhabits the rhetorical, on multiple levels, ranging from the essential function of data in ontological and epistemological enter-prises in science to trans-scientific problems and the legal and policy-based questions that we might more comfortably call rhetorical. Databases are rhe-torical in that we decide what will be selected, segmented, represented, and stored. Effectively, we take these data as serving an argumentative function, and take that an argumentative function is a reality-building element. Thus, the way we identify data, structure databases, and decide what will be archived has significant implications for the ability to build high-quality and robust understandings about complex research problems and for the potentialities found in future research with our current data.

To understand the database and its related genre-ing activities is to acknowledge powerful rhetorical work involved in crafting a complex appa-ratus we use to construct knowledge. Design decisions are important, and we need a language in rhetorical studies of online science communications to talk about how disciplinary norms, discourse conventions, and argument shape the design features that are technically implemented. Indeed, the mat-ters of argument that shape a database design and its ongoing use are valu-able because the data that inhabit these organizational logics govern so much of how scientists explore and explain the world. Rhetorical study is relevant to these technologies and comes by way of rhetoric’s capacity to articulate emerging technologies and their communicative functions in relation to

more traditional forms (Geisler et al., 2001). Rhetorical genre studies have long been concerned with the study of written and oral expression, but the primary focus on these modes of expression should not be taken as wholly representative of genre studies. In addition to studies of delivery and perfor-mance, rhetorical studies have also considered the conceptual roots of our expressive modes, a variety of semiotic modalities not limited to auditory, aural, verbal, and visual expression, and indeed the media and technologies we employ for communicative functions. Ever-evolving expressive modes and associated media provide space to ask questions about rhetorical change: Are these new computational technologies and processes governed by rhetorical logics or something entirely different? Can we think of acts of composition and communication to create and use these technologies as rhetorical acts?

A researcher interested in providing open data will have a number of considerations to make, and many of these considerations exist outside the expected technical domain. Choices about audience, users, and the legality and ethics of sharing matter because databases are central to the mission of open science in that they allow sharing and redistribution of information that can advance research and scientific knowledge globally. However, because of the global and distributed nature of (open) science, and its mission to share information and knowledge broadly, attention to the rhetorical dimensions of databases is increasingly necessary. Because open data are designed to serve a larger stakeholder group, ensuring that those users’ needs are anticipated requires expanded rhetorical work. Needs include traditional design-based questions, including what kinds of data might be useful, how those data will be related to one another, and also how a wider range of users will be able to access and make sense of the data that they did not collect. It is the audi-ence that helps remind us that we are indeed engaging in rhetorical activities.

As we have seen in previous chapters, an essential difference between these genres and their traditional counterparts is not simply the form, but the com-plex audience composed of a range of experts, amateurs, citizen scientists, and other engaged stakeholders. In the case of databases, we see the audience changes qualitatively and quantitatively. In terms of quantitative change, we see more researchers and scientists accessing data that they did not collect on their own. This might be for verification of a study or perhaps even expansion of a study. Data must be organized and structured in a way that this audience can access and use them appropriately, in particular, making constraints and limitations of the data apparent. The qualitative change is a little more diffi-cult to account for, but when we open data to anyone who is interested, then the possibility for a more heterogeneous audience exists. This, again, can be

addressed by providing good, structured, and rhetorically thoughtful design to help guide users in understanding the context of data, data collection, and appropriate constraints.

Although Safecast offers what Bazerman (2016) might caution is an excit-ing, perhaps exemplary, but not common case, what we learn from their work can be applied to broader trends. Consider Figshare, a data repository that allows researchers to share various kinds of data (data sets, figures, presen-tations, and so on). Researchers can do more than share data: they are also provided with a DataCite DOI for their contributions. Recall, similarly, suc-cessful Experiment projects also receive a DOI. A DOI allows research to be searched for and cited in a manner acceptable to most scientific disciplines.

The purpose of sharing data through repositories such as Figshare extends beyond making one’s research findable and, crucially, citable—it is also to make the data useful to other researchers, as did Safecast’s efforts. With this framework, Figshare provides a platform for data sharing that is crucial for accessible data. The platform also frames itself as a place to host data spe-cifically associated with published articles, and indeed even as a service for publishers to use so that their own infrastructures are not impacted by the growing interest in associating data with research articles (Figshare, 2017).

Consider, for example, PLOS’s integration with Figshare. PLOS is a nonprofit, born-digital, open-access publisher that has done much since its founding in 2003.⁷ In 2013 PLOS and Figshare partnered to allow data to be hosted on Fig-share and associated with articles in PLOS journals (Hahnel, 2013). Further, its infrastructure allows for data to be visualized alongside the article. This partnership underscores the value of providing data in an accessible, findable place online. Figshare and PLOS lead us into a discussion of the dissemination of research, the subject of the next chapter.

7. Although the company was in fact founded in 2003, the idea predates the founding. But the story is worth noting as the site’s internal history reports a founding of 2001, when PLOS became a nonprofit, sprouting from its origins as a 2000 initiative by Harold Varmus, Patrick Brown, and Michael Eisen calling for scientists to make their articles freely available to every-one. In 2003, the organization began its publishing branch with its first journal, PLOS Biology (Public Library of Science, 2017b).

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