Opportunities for research students in HAIKU (Hypertext Augmenting Intelligent Knowledge Use)

For Masters and Undergraduate students

Mastery of programming to work with XML documents will be an advantage. Students will be expected to parse and create Ontology Web Language (OWL) and other files in RDF (Resource Description Format) and RDF Schema.

Touch Archive Taxonomies

recode the CIDOC-CRM to include other taxonomies
code existing artworks (objects, figures, etc.)
create taxonomies that describe visual patterns

Speed-up editing of CIDOC-CRM and other such ontologies

Use frequent subgraph mining and association graphs to find repeated patterns that can be replaced by either macros or semi-automated (see Philippe Fournier-Viger's An introduction to frequent subgraph mining for some details)

Engagement of visitors with artworks

games and quizzes
incorporation of visitor comments into interactive experience in art galleries

PhD (especially Interdisciplinary or InfoSci/SIM students)

Indigenous Ways of Knowing / Ontologies

students with experience of qualitative methods preferred but not essential
will be researching and conducting interviews to create ontologies that use Indigenous ways of knowing (not only in the Health field)

Tools and techniques for scholarly texts

Background

In HAIKU we are pursuing how to integrate mark making, navigation (place marking), note-taking, annotation, glossaries and to combine them with the ability to seamlessly transclude, version and share documents.

Transclusion is more than the simple inclusion of lexia from one source into another; with transclusion, although lexia are stored once and can be reused many times, every use is of the most recent version. When a new edition of a work is published, can notes made on an earlier edition be transcluded? What if the text in the new edition is different? In effect annotated copies become different editions, and the relevance and accuracy of the information in each can be questioned and the implications for learning and scholarship need to be resolved. As late as DocEng 2018, the question of how to transclude effectively has not been solved in general (although it has in Wikipedia).

It is not yet understood how digital interfaces change the ways people cognitively interact with text and what tools will best support and augment long-term knowledge acquisition. Learners rapidly switch between states of reading, making notes and marks, revising notes and their understanding of the text, reviewing, re-reading, reappraising, assessing the importance of ideas, being distracted, and sometimes considering their processes of use. People are not consistent, learners aims change in the process of cognitive restructuring and reading for a different purpose (repurposing).

It is not known what learners do when they revisit their notes: are the notes changed, erased, or even understood? This is especially important for learners who will assemble digital libraries for study over many years. The provenance of primary sources and of attribution of comments (for users to assess their merit) is important. When documents or notes are shared, how will authority control operate (e.g., a comment by an acknowledged expert is more important than one by an unknown source)? How can notes from multiple authors be meaningfully merged? These problems include, but go beyond, simple versioning.

Building on earlier research in HAIKU we are working towards a (semi-)automated system to help users discover information in text and in their existing notes. To create such a system we need to know how to recognize and attach meaning to the marks made by users. A simple example, where our research focus is: which categories, and which marks representing those categories, should be used so re-finding notes is most efficient. We seek to help users to refine their own process so it becomes knowledge-building instead of compiling marks, e.g. find all text that I've highlighted or circled and then filter for content.

Interested students should write with an outline of one or more specific research areas or questions. When we review applications to work in HAIKU we look for a well thought-out statement of research goals: an outline of one or more specific research areas or questions that demonstrates the student's preparation and seriousness. The statement of research should suggest that it could be completed in the time available for a thesis or project. There is much flexibility in choosing a final topic and approach — they do not have to be what you proposed in your statement as one or both may change over the course of our conversation.

Opportunities for student research in HAIKU

Current Projects