Overview: Database and narrative
A database, as we have seen, is an effective way to manage, access, use, and query information. It can be used to store the metadata that describes files and materials in a repository, or it can be the primary document (many databases are stand-alone documents, they don’t necessarily link to or manage other files or materials).
What does it mean, however, to assert that databases are the new, current, and future form of knowledge and that they will replace narrative in the study of history, the creation of literature, or the development of artistic expression? The theorist Lev Manovich suggests that database and narrative are “natural enemies”—but why and on what grounds? A special issue of thePMLA, the Publication of the Modern Language Association generated much controversy when it took up these and other arguments.
Among the assertions was that databases were non-linear while narratives were linear, that processes of selection resulted in fixed narrative modes while processes of combination are at the heart of database “logic.” The theme that runs through such arguments has a strong technodeterminstic feel to it, suggesting that changes in ways of thinking are the direct result of changes in the technology we design and use. Counter-arguments suggested that combinatoric work and content models are integral elements of human expression and have been since the beginnings of the written record, which can be dated to five or six thousand years ago in Mesopotamia. The distinction between database structures and narrative forms is real, but are they in opposition to each other or merely useful for different purposes and circumstances? Why make such strong arguments on either side? At stake seems to be the definition of what constitutes discourse, human expression, and the rules and conventions according to which it can create the record of lived and imaginative experience. But also at stake is an investment in the ways we value and assess new media and their impact, understand digital media and its specificity but also its effects.
Discuss the points in this summary of some of the issues in these debates:
Lev Manovich, “Database as Symbolic form” (1999)
- Database and narrative as “natural enemies”—why?
- HTML as database? (modularity)
- Universal Media Machine – means what?
- Multiple interfaces to the same material
- Paradigm (selection) vs. syntagm (combination)
- What is meant by “database logic” in his text?
- Do his distinctions between database and narrative hold?
Ed Folsom, “Database as Genre: The epic transformation of the Archives” (2007)
- Cites Dimock (unordered/ordered = dbase/narrative)
- Network, circuits, rhizomes (Whitman’s own practice)
Jerome McGann, “Database, Interface, and Archival Fever” (2007)
- dbase and the “initial critical analysis of content”
- The concept of the “social text” and constant makings and remakings
Ursula Heise: Database and extinction
- How can you connect the statements here with our discussion?
- Look at the Red lists here
- Struggles over identity/description
- Distinctions between literal format and virtual form
- Continuities and ruptures: nothing new vs. totally new
- Technodeterminism, teleology, liberatory utopianism
Recap: Keep in mind that we are working towards understanding the “under the hood” aspects of Digital Humanities projects. We began with a very generalized sketch of what goes into a DH project: back end repository/database/structured data/metadata/files, a suite of services or functionalities that help do things with that repository, and various modes of display and/or modelling user experience. Digital Humanities concepts and vocabulary recap:
HTML, browsers, display, W3C and parsing depend on HTML’s function to display directly through browser has limited functionality, flexibility, use. HTML structures data for display, but not for content analysis.
Exercise: How is this NOT plain HTML? http://orbis.stanford.edu/#
Exercise: Can you map the elements in Omeka and in your projects to the basic features of digital humanities projects? What is still missing and/or unexplained in the creation of these projects?
- Metadata– records, descriptions, standards, Dublin Core, Getty AAt
- Classification/organization (into “classes” by characteristics)
- Ontologies (ontology=”being”) and Taxonomies (also classification systems)
- Database back-end (flat and relational databases: spread sheets, tables, relations)
- Display / Interface
Readings for 4B:
- * Calvin Schmid, Statistical Graphics, excerpt
- * Howard Wainer, Graphic Discovery, excerpt
- ManyEyes, read the information on uses for each type
- Visual Complexity website
- What is visualization and how does it work? How is Schmid’s very practical approach to graphics different from the work on the Visual Complexity website?
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