1 / 17

Using Conceptual Models to Organise Data Libraries

Using Conceptual Models to Organise Data Libraries. Bob Allen Visiting Professorial Fellow School of Information Management Victoria University of Wellington Bob.Allen@vuw.ac.nz. Roadmap. Trends in scientific communication

karli
Download Presentation

Using Conceptual Models to Organise Data Libraries

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Using Conceptual Models to Organise Data Libraries Bob Allen Visiting Professorial Fellow School of Information Management Victoria University of Wellington Bob.Allen@vuw.ac.nz

  2. Roadmap • Trends in scientific communication • Interface and library-level opportunities for open text research reports • Conceptual models for scientific research reports • Conceptual models for digital history

  3. Trends in Science Communications • Changes for scientific communication • Full text, open-access collections. • Include multimedia and simulations (“executable papers”).

  4. Changes in Documents and Digital Libraries • Documents (“works”) were considered the basic unit for libraries collections. • Increasingly (e.g., with XML), we are opening documents. • Digital libraries can be composed of smaller conceptual units. • The digital libraries might look more like Wikipedia. Wikipedia has been developing a a classification system.

  5. Structure of Scientific Reseacrh • Genre structure • Introduction, Methods, Results, Discussion (IMRD) (Swales) • Structured abstracts • Highlight key points in the abstract • Common in medical fields with standard procedures • Workflows • Laboratory procedures • Data analysis • Research designs

  6. Interacting with Structure in a PLoS Browser

  7. Opportunities for New Library Services • Authority files • Standard names • Summary/survey pages for • Theories • Methods • Instruments • Richer interactions with citation lists. • Knowledge structures for organizing entities such as taxonomies

  8. Discourse and Argumentation • Creating a Research Space (CARS) • Toulmin model • Widely used in science education • Annotation ontologies • Swan ontology • Beyond ontologies with narrative “fairy tails” • But, shouldn’t we also model the domain and events in that domain.

  9. Frozen Thawed Ocean water Normal Low Normal/Low High C02 absorption in ocean Atmospheric temperature Normal High C02 in atmosphere Conceptual/Causal Models • Many approaches to modelling causation • Structural equation models • Statechart and UML models of biological systems • System dynamics models for biological systems • Causal conceptual models for science education • Causal models as state changes applied to snowball earth. Allen, R.B., Wu, Y.J., and Jun, L., Interactive Causal Schematics for Qualitative Scientific Explanations, ICADL, 2005, 

  10. Toward Model-Oriented Research Reports (1) • Entities • States associated with attributes • Classes vs instances • Composites • Grouping • Models/Flows (combinations of entities which result in a state change) • Several variations for the causal template • State change, entity creation/destruction • Generic flows and instances • Chains • Both causal and non-causal flows • Generic flows (predicates) • Method and analysis flows • Conceptual models

  11. Toward Model-Oriented Research Reports (2) • Control framework • Article-level metadata • Specification of contradictions and gaps • From those identify Research Questions • Activity blocks: • Method implementation block • Exploration and confirmation blocks • Research question blocks • Research design • Comparing models (conditionals) • Specify and manage data sets • Presentation structure • Beyond the surface structure of the text

  12. Challenges for Implementation • Entities • Proliferation of Entities • Dealing with fully elaborated instances • e.g., entire organisms • States are ad hoc and need to be managed • Representing shapes and mechanisms • Blocks • Don’t follow the canonical patterns • The authors’ intention is ambiguous • Non-numeric data (e.g., image data) • Presentation • Interface • Some text may still be required • e.g., brief summaries are helpful • Future • Personalization

  13. Conceptual modeling for history?

  14. Newspaper as a Projection of a Community (Some) Events Reporter Community Editor Audience Given the large amount of data, could we develop a model of the culture? We may need to develop intermediate models.

  15. Identifying Important Events by Comparisons across Newspapers Oct – Dec 1906, Washington Times and Washington Herald Find distinctive words and then find days with overlaps of those words across the two newspapers Allen, R.B., Improving Access to Digitized Historical Newspapers with Text Mining, Coordinated Models, and Formative User Interface Design, IFLA International Newspaper Conference:  Digital Preservation and Access to News and Views, 2010.54-59. 

  16. Representation and Knowledge for History • Orthogonal entity categories • People • Place • Government • Rules, Norms, Regulations • Physical entities • Institutions • Knowledge & information • Predicates from FrameNet Project

  17. Bob.Allen@vuw.ac.nz

More Related