Center for Documentary Studies

There is potential disconnect between a view of classification as historically and culturally contingent and the ethics of KO. For instance, Mai (2011) urges a shift away from the 'modernity' of received classification theory, towards a more pluralistic view that acknowledges the social, political, and historical contingency of classification as a practice. While this is a view shared by many, it is not evident how such an approach can support an ethics which prioritizes a commitment to truth, fairness, democracy, and the common good. A view of such values as merely contingent factors in classification activities would seem to undermine their use as ethical ideals, posing a choice between abandoning modernist tendencies and a workable ethics of KO. An ethics that is consonant with core methodological commitments is critical if we seek to preserve both disciplinary rigor and claim to serve the common good. Rorty's thought is presented as an ethics compatible with a view of classification as contingent. His suggestion of an ironic ethics is presented and distinguished from cynicism, which is a common misinterpretation of this aspect of his thought. Finally, his ethical principle of solidarity is shown to be broadly compatible with the traditional values of the field of LIS, while approaching it from a philosophical standpoint that doesn't demand or encourage the universalizing tendencies which Mai and others have exhorted us to abandon. In short, this paper attempts to preserve the baby of a workable ethics while discarding the bathwater of universalism in knowledge organization.

Aboutness ranks amongst our field's greatest bugbears. What is a work about? How can this be known? This mirrors debates within the philosophy of language, where the concept of representation has similarly evaded satisfactory definition. This paper proposes that we abandon the strong sense of the word aboutness, which seems to promise some inherent relationship between work and subject, or between word and world. Instead, we seek an etymological reset to the sense of aboutness of "in the vicinity, nearby; in some place or various places nearby; all over a surface." To distinguish this sense, we introduce the term episemantics. The authors have each independently applied this term in slightly different contexts and scales ​ (Hauser 2018a; J. T. Tennis 2016)​ , and this article presents a unified definition of the term and guidelines for applying it at the scale of both words and works. The resulting weak concept of aboutness is pragmatic, in Star's sense of a focus on consequences over antecedents, while reserving space for the critique and improvement of aboutness determinations within various contexts and research programs. The paper finishes with a discussion of the implication of the concept of episemantics and methodological possibilities it offers for knowledge organization research and practice. This paper discusses and synthesizes two conceptions of the term episematics developed independently by the authors in prior work. Both conceptions deny that meaning is an inherent property of language, but take distinct approaches in relating this idea to the field of KO, and information studies more broadly. Tennis ​(2016)​ proposes episemantics as a potential new field of study, analogous to epigenetics, just recently possible due to the advent of new technologies and research methods. Hauser ​ (2018a)​ asks what it might mean to remove aboutness as a core component of our understanding of information at all. After discussing both proposals, we present a synthesis of each that connects Tennis's methodological proposal with Hauser's theoretical approach via a shared pragmatism, in Star's sense of "consequences, not antecedents." The result is discussed in relation to classification theory, and particularly in light of Melvil Dewey's pragmatic approach to his first classification system.

Interest in data science, especially within the context of graduate education, is exploding. In this study we present initial results from an ongoing qualitative study of an interdisciplinary cyberinfrastructure-focused NSF-funded graduate data science education workshop hosted at an iSchool in the US. The complexity of the workshop curriculum, the participants' and instructors' disparate disciplinary backgrounds, and the technical tools employed are particularly suited to qualitative methods which can synthesize all of these aspects from rich observational, ethnographic, and trace data collected as part of the authors' role on the grant's qualitative evaluation team. The success of the workshop in equipping participants to do reproducible computational science was in part due to the successful acculturation process, whereby participants comprehended, altered, and enacted new norms amongst themselves. At the same time, we observed potential challenges for data science instruction resulting from the rhetorical framing of the technologies as inescapably new. This language, which mirrors that of a successful grant proposal, tends to obscure the deeply embedded and contingent history of the command-line technologies required to perform computational science , many of which are decades old. We conclude by describing our ongoing work, future theoretical sampling plans from this and future data, and the contributions that our findings can provide to graduate data science curriculum development and pedagogy.

The Longitudinal Social Impacts of HRI over Long-Term Deployments Workshop seeks to bring together researchers working on all aspects of thoroughly understanding such deployments. This includes researchers working in contributing areas, such as longitudinal studies of human-robot interaction, longterm autonomy, and real-world reployments. This workshop seeks to grow the study of how real-world, deployed robot systems impact the people who interact with them and the social structure of the places that they inhabit. Historically, research in this area has been high-impact. As the world sees robots begin to inhabit places designed for peopledelivery robots on city streets, and robots with jobs in airports, shopping malls, and in the home-we expect the importance of understanding these impacts to grow.

Aboutness ranks amongst our field’s greatest bugbears. What is a work about? How can this be known?
This mirrors debates within the philosophy of language, where the concept of representation has similarly
evaded satisfactory definition. This paper proposes that we abandon the strong sense of the word aboutness,
which seems to promise some inherent relationship between work and subject, or, in philosophical terms, between
word and world. Instead, we seek an etymological reset to the older sense of aboutness as “in the vicinity,
nearby; in some place or various places nearby; all over a surface.” To distinguish this sense in the context of
information studies, we introduce the term episemantics. The authors have each independently applied this term in slightly different contexts
and scales (Hauser 2018a; Tennis 2016), and this article presents a unified definition of the term and guidelines for applying it at the scale
of both words and works. The resulting weak concept of aboutness is pragmatic, in Star’s sense of a focus on consequences over antecedents,
while reserving space for the critique and improvement of aboutness determinations within various contexts and research programs.
The paper finishes with a discussion of the implication of the concept of episemantics and methodological possibilities it offers for
knowledge organization research and practice. We draw inspiration from Melvil Dewey’s use of physical aroundness in his first classification
system and ask how aroundness might be more effectively operationalized in digital environments.