Led by Janelle Jenstad
University of Victoria
LINCS will shine light on the dark matter of history: the hidden and unexpected connections between people, places, events, and cultural works across time, space, and media.
Currently, the ability to ask large questions of digitized cultural datasets is hampered by the lack of good metadata that connects primary sources to contexts: when they were written, by whom, where, how, and why. LINCS will allow researchers to engage with digital archives’ content and context simultaneously. A deeply contextualized understanding is fundamental to answering big questions like how social discrimination persists despite formal equality, or what policies and practices fuel the creative economy.
A major aim of LINCS is to bring together overlapping datasets across multiple academic and linguistic fields. LINCS will bridge the two solitudes of linguistically divided cultural datasets as never before, partnering with the scholarly platform Érudit on French Canadian ontology development and on mobilizing Linked Open Data for scholarly ends.
Beyond academia, the interconnectivity LINCS creates will propel Canadian culture to greater prominence on the web, provide deep contextualization to search results, and give journalists, schoolchildren, and the public better access to quality knowledge sources.
Led by Stacy Allison-Cassin
University of Toronto
The ability to see patterns in large datasets and then zoom in to examine evidence is essential to humanities research, but it has been elusive in most contexts until now. LINCS will allow movement between granular data and distant views for those probing the complex interactions that contribute to cultural change.
We will mobilize a rich set of researchers’ musical data — entertainment records, early music scores, and ethnomusicological datasets covering Canadian Indigenous, East Indian, other folk music, and European traditions — to enable comparative investigation of influences, movements, and networks. Interlinking this data with that of our partners will enable an even broader analysis of the impacts of cultural policies and funding, such as the creation of the NPR in the US as compared to the CBC in Canada.
Such prosopographical datasets help trace how cultural identities circulate within avant-garde literary circles, or as applied to Indigenous and settler citizens in Canadian prison records. They offer glimpses of many who are otherwise lost to history, and have the potential to link to Canadians within inclusive projects such as the Digital Panopticon and other datasets of “ordinary” people.
The interplay of macro and micro is vitally important in work on material and textual culture. Editorial theorists and practitioners will use Linked Open Data to mobilize new kinds of editions and scholarly journal content. These probings of textual dynamics, using data that itself enacts networked textuality, will yield crucial insights in a world where textual conventions have been disrupted by digital tools. LINCS will therefore enable experiments in new forms of publication and application prototypes.
Led by Jon Bath
University of Saskatchewan
LINCS will change how researchers work on the web by combining the many advantages of highly structured data. For example, it will provide more explicit documentation of data organization than is available for most databases, with links back to sources in support of provenance, access, and analysis.
A major promise of Linked Open Data is that it can tell us what we don’t yet know through inferencing, the computational extrapolation of information not explicitly stated in, but emergent from, Linked Open Data. LINCS will transform knowledge discovery by extrapolating inferences from millions of data points. In this underdeveloped area of Semantic Web research, the interests of scientific team members inevitably overlap with some in the technical team.
Another promise is that new forms of serendipity will arise from the semantically meaningful data. Linking datasets provides exciting opportunities to locate sources in unexpected places, recreating the serendipitous discoveries that once awaited scholars in archives or libraries on a larger, more complex scale. Such advances will propel knowledge discovery rapidly and are relevant to the design of search engines like Google.
A real challenge of Linked Open Data for humanities research is incorporating nuance and epistemological differences, including the accommodation of boundary objects that have different meanings in different fields. LINCS will work to ensure that its ontologies can represent non-hegemonic epistemologies and push alternative knowledge representations into the Semantic Web. Linked data will also improve over time, increasingly capturing nuance and shedding more light on corners of darkness.
In its information architecture, LINCS will attend to difference and diversity, including the ways of knowing of marginalized groups. Above all, LINCS will provide a networked infrastructure of expertise and knowledge in linked data that will enable Canadian researchers to contribute to building a better information ecology. Canada has nothing approaching this kind of infrastructure for the study of human history and culture.