Knowledge Organization and Data Modeling in the Humanities: An ongoing conversation

Featured

In March 2012, a three-day workshop was held at Brown University on data modeling in the humanities, sponsored by the NEH and the DFG, and co-organized by Fotis Jannidis and Julia Flanders. Attended by approximate 40 experts with diverse disciplinary backgrounds, the event included theoretical presentations, case studies, panels, and wide-ranging open discussion. What we present here is a record of the event, with links to slides, video footage, and transcriptions of all presentations and discussion. In order to open up the conversation to a broader audience, the transcriptions have been extensively annotated to elucidate informal references, and to provide links and glosses on the many projects, tools, standards, people, and specialized terms that were referenced in discussion.

March 14

Keynote presentation: Wendell Piez, “Data Modeling for the Humanities: Three Questions and One Experiment” (paper, slides, video, transcription)

Panel discussion: Data models in humanities theory and practice (video, transcription)

Stephen Ramsay, Laurent Romary, Kari Kraus, Maximilian Schich, Desmond Schmidt, Andrew Ashton; Julia Flanders and Fotis Jannidis (moderators)

Theoretical perspectives I

Case studies: Critical editions

March 15

Open discussion: Key themes (video, transcription)

Case studies: Research ontologies

  • Daniel Pitti, “EAC-CPF” (video, transcription)
  • Stefan Gradmann, “Objects, Process, Context in Time and Space – and how we model all this in the Europeana Data Model” (slides, video, transcription)
  • Trevor Muñoz, “Discovering our models: aiming at metaleptic markup applications through TEI customization” (slides, video, transcripition)

Panel discussion: Data modeling and humanities pedagogy (video, transcription)

Elisabeth Burr, Elizabeth Swanstrom, Susan Schreibman, Elena Pierazzo; Julia Flanders, moderator

Theoretical perspectives II

Discussion

March 16

Open discussion: Key themes (video, transcription)

Case studies: Historical archives

Theoretical perspectives III

Closing keynote presentation: C. M. Sperberg-McQueen (video, transcription)

Continuing the discussion

We know there will be continued interest in the topic of data modeling in the (digital) humanities. For a record of this event, including video footage of all the sessions and links to slides and presentation notes, please visit the workshop site at the Women Writers Project.

Thanks to all who participated in Knowledge Organization and Data Modeling!

Featured Abstract: March 14

Check in frequently this week to view featured abstracts, leading up to the symposium! We welcome your comments.

Featured Abstract: “A theoretically-rich approach to teaching to model”

Elena Pierazzo, King’s College

Modelling is at the heart of most of my teaching: when teaching XML, XSLT, TEI within an MA in Digital Humanities you need to provide the students with intellectual challenges as well as technical skills. In fact, modelling can be seen as the intellectual activity which lies at the base of any computational effort, namely the methods and the languages we invent to communicate our understanding of a particular cultural object (such as a text, a statue, a piece of music) to the computer and, via the computer, to the users. Effective modelling depends on a deep analysis and understanding of the object to be modelled, so it is also essential to encourage and train students’ analytical skills as part of introducing them to modelling; the provision of theoretical frameworks within which to conduct the analysis and subsequent modelling has proven to be a highly successful approach with MA and PhD students. The case study to be presented here will be the modelling of texts of manuscripts and of the transmission of texts through centuries, materials and people. Transmission of texts can be seen as an act of communication, and so communication and linguistic theories (particularly those of Shannon-Weaver 1948/63, Berlo 1960, Saussure 1961 and Jakobson 1960 ) can cast some new light over the way we analyse, model and understand the texts contained in manuscripts as well as their relationship with the author’s intentions and the reader’s experience. The use of such a complex theoretical framework has proven to help students move conceptually from the empirical to the abstract, a process that is fundamental for modelling. My talk will present some considerations and examples of analytical and modelling activities applied to text transmission and which have been used in the classroom at King’s College London.

Featured Abstract: March 14

Check in frequently this week to view featured abstracts, leading up to the symposium! We welcome your comments.

Featured Abstract: “Taking Modeling Seriously”

Allen Renear, University of Illinois, Urbana-Champaign

There are many kinds of modeling. I am concerned here with the sort of
modeling that emphasizes theoretical or epistemic objectives, modeling,
that this, that purports to provide an account of how things are in a
domain of interest.   The demands of this sort of modeling are exacting –
and not to everyone’s taste. But the rewards in insight and understanding
are worth the effort. This sort of modeling may sound like straightforward
philosophical ontology development, and of the usual naïve and realistic
sort. Perhaps in a sense it is. However my focus throughout will not be on
self-declared ontologies or ontology design, but rather on examples that
have more practical objectives (such as systems design) and are typically
carried out in familiar graphic conceptual modeling languages, such as
entity relationship diagrams and UML class diagrams. It is these ordinary
modeling efforts I will be taking seriously, and in doing that I will be
thereby doing some serious modeling of my own. In my experience the
stresses and paradoxes latent in familiar unpretentious conceptual
modeling give us a natural manageable start in thinking through some of
the hardest problems in developing a formal understanding of cultural
objects and relationships. In the end however I will argue, as you
probably suspect, that taking modeling seriously requires specific
logic-based formal methods. Serious modeling takes modeling more seriously
than it takes itself.

Featured Abstract: March 13

Check in frequently this week to view featured abstracts, leading up to the symposium! We welcome your comments.

Featured Abstract: “Modeling: Perspectives, Objectives, and Context”
Daniel Pitti, Institute for Advanced Technology in the Humanities, University of Virginia

Humanists, scholars and cultural heritage professionals (archivists, librarians, museum curators, and keepers of sites and monuments) share a common focus on artifacts, objects created by humans that provide the historical evidence for our understanding of what it means to be human. Cultural heritage professionals focus on preserving and facilitating access to selected artifacts, and scholars study the artifacts, from a variety of perspectives, and attempt to analyze and understand them.

Humanists have turned to (and become increasingly comfortable with) information technologies for practical reasons: the technologies allow them to achieve particular professional or scholarly objectives. Broadly speaking, those are preservation and access for the cultural heritage professionals, and analysis and understanding for the scholars. To facilitate achieving their objectives, the scholars and professionals seek to represent an artifact or class of artifacts, descriptive representation (for example, a catalog record) or content representation (for example, a TEI-encoded text). The ways in which any given artifact or class of artifacts can be represented is unlimited, but the mission of the cultural heritage professional and the disciplinary perspective of the scholar narrow the possible representations.

Modeling or representing artifacts digitally involves philosophical issues—metaphysical, epistemological, and even ethical issues—as well as quite practical issues. A particular technology’s capacity to represent artifacts will limit or direct its application, making it a better or worse servant to our objectives. Economy and efficiency must be a factor, both in the processing efficiency of a chosen technology, and the financial and administrative economy of creating and maintaining the representation data. Social context and objectives also have an impact on the modeling design and process. Representations that are created and maintained by a lone scholar, a small group of two or three working together closely, or a large distributed community, have their own specific design challenges. Finally, for both scholars and cultural heritage professionals, the desired audience must be an important social factor to be considered in the modeling process.

Featured Abstract: March 13

Check in frequently this week to view featured abstracts, leading up to the symposium! We welcome your comments.

Featured Abstract: “Analyzing linguistic variation: From corpus query towards feature discovery”

Elke Teich, Universität des Saarlandes, Saarbrücken, Germany

In the study of linguistic variation (dialect, sociolect, register), we can distinguish two types of analytical situations: the feature-centric and the variable-centric. In a feature-centric perspective, we start from a given feature (or set of features) and want to derive the variables (e.g., place, social group, user group) associated with the given feature/features. This is a typical situation in dialect studies, where we are interested in the geographical distribution of a particular phonetic realization (e.g., +/- rhoticity and British dialect areas). In a variable-centric perspective, we start from a given variable (e.g., a register) and want to determine the features that are typically associated with that variable. In the feature-centric perspective, we obtain the necessary information (typically a frequency distribution of a feature) employing a corpus query approach, by means of which we extract the instances of a given feature from an appropriate set of language data. In a variable- centric perspective, we are faced with the problem that we may not know a priori what the relevant features are; instead, we have to find ways of discovering linguistic features potentially suitable for analysis.

In my presentation, I will illustrate these two perspectives with examples from the study of register variation in the scientific domain, looking at selected lexico-grammatical features and the variables of discourse field (scientific discipline) and time (diachronic evolution of registers) (cf. Teich & Fankhauser, 2010; Degaetano et al., 2011; Degaetano & Teich, 2011).

Featured Abstract: March 13

Check in frequently this week to view featured abstracts, leading up to the symposium! We welcome your comments.

Featured Abstract: “Modelling as a centre of Practice and Pedagogy”
Susan Schreibman, Trinity College Dublin

Last year I designed a MPhil in Digital Humanities and Culture for Trinity College Dublin. We are now in the second semester of the first year. Unlike teaching a single DH course that centres on a specific area (from introductory courses to more specific text encoding, digital scholarly editing, web technologies, etc) the longer timescale of a full year allows for significant cross-fertilisation in understanding how disparate technologies, methodologies, and theories interrelate to comprise the salient core of this new and somewhat abstract discipline of humanities computing.

Many of us have been in this field long enough to know that the technologies we teach our students today will be surpassed and replaced by the yet-to-be invented.  What is more lasting, however, is the understanding how to model the objects of our contemplation: from the narrative arc of a thematic research collection, to a TEI-encoded document, to a relational database. Models serve as an abstraction of an analogue object, its relationship to other objects, as well as a representation of what we think is important about them. By teaching our students how to model, we give them the tools to represent and re-present the yet-to-be-encountered.

The question then remains: how do we teach this interrelatedness of things and their properties. Should there be a knowledge representation course which covers modelling more abstractly, or should it be covered within context, when teaching subjects such as relational databases, TEI encoding, or virtual world construction. Should knowledge representation be the theme that binds the disparate strands of DH together, or a theme. If knowledge representation, as Willard McCarty suggests, is the coherent or cohesible practice that binds all of DH together, then it follows, that KR must be at the centre of our pedagogy.