Fluid Data

The last tool in the DALN Database Toolkit offers a chronological view of the database. As with other tools such as the Random View generator and the Google Earth map, users can click on a link in the tool and go directly to a narrative's entry in the DALN, thus providing a direct link between reading the database and close reading of individual narratives.

DALN Timeline allows users to visualize the time periods referred to by narrators whose stories are archived in the DALN—at least, by those who provided that information. It also strikingly reveals the chronological coverage of the archive in a manner that reading individual narratives cannot. For example, the timeline graphically highlights the urgency of recording literacy narratives by senior citizens if we wish to include their recollections in the DALN: the archive's holdings for a each decade shrink dramatically as one looks back in time. To explore the DALN Timeline, open the file DALN_SIMILE_Timeline_OverviewTop.html (inside the folder named DALNTimeline_KeepFilesTogether) in a Web browser and follow the directions at the top of the page.

The DALN Timeline tools raise another issue, however, that applies to all of the tools in the toolkit—the data represented in it are already outdated. The DALN is managed as an archive dedicated to preserving and providing access to cultural assets. Accordingly, the curators and systems administrators who watch over the collection exercise great care to protect the integrity of the data and metadata once they are deposited in the archive. As much as possible, the information content of the digital files is protected from loss or change, even if it must eventually be migrated to new physical media or file formats. These efforts at stability notwithstanding, the collection keeps growing, as does the usage data related to existing items in the collection, and the format of contributions will no doubt change as digital technology changes. Beyond the DALN, new tools for digital data analysis and visualization emerge continually. Reading the database, as we have explored it here, means not only analyzing the existing database in concert with close reading of individual narratives in order to discover networks of relationship in which meaning arises, but also tracking the evolving nature of the database, the data within it, and the capabilities and applications of tools for data analysis that can complement our reading of individual narratives.