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Facilitate Humanities Researchers in Sensemaking and Information Seeking Tasks

Facilitate Humanities Researchers in Sensemaking and Information Seeking Tasks. Yan Qu School of Information yqu@umich.edu. Project Overview. What’s the research problem? How could a software system facilitate humanities researchers in their sensemaking and information seeking tasks?

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Facilitate Humanities Researchers in Sensemaking and Information Seeking Tasks

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  1. Facilitate Humanities Researchers in Sensemaking and Information Seeking Tasks Yan Qu School of Information yqu@umich.edu

  2. Project Overview • What’s the research problem? • How could a software system facilitate humanities researchers in their sensemaking and information seeking tasks? • Why it’s important? • Sensemaking and information seeking activities are ubiquitous in our research activities. The better support for these activities could result in efficient and high quality research work. • What has been done? • Various sensemaking and information-seeking related theories • Existing systems • What is my approach? • Study of sensemaking and infomration seeking behavior • System design and implementation • System evaluation

  3. Presentation Outline • Introduction to the research problem • Study of sensemaking and information seeking behaviors with the emphasis on sensemaking tasks conducted by humanities researchers. • How such study informs the system design • Related systems • System design • System framework • Functions support sensemaking and information gathering • System evaluation

  4. Research Problem • How could a software system facilitate humanities researchers in their sensemaking and information seeking tasks

  5. Research Methodology • Study of sensemaking and information seeking behaviors with the emphasis on sensemaking tasks conducted by humanities researchers. • Review general theory about sensemaking and information seeking • Investigate how humanities researchers conduct sensemaking and information seeking activities • Review theory about academic reading and writing • How such study informs the design of software systems that support sensemaking and information seeking activities • System design and implementation • System evaluation

  6. Theories of Sensemaking and Information Seeking • Dervin’s sensemaking model • Russell et al’s sensemaking model • Information seeking model • Integrated model of sensemaking and information seeking

  7. Dervin’s Sensemaking Model • Dervin’s sensemaking triangle show the close relationship between sensemaking and information seeking activities

  8. Russell et al’s Sensemaking Model • Russell’s sensemaking model posits the use of representations in service of accomplishing some tasks.

  9. Information Seeking Cycle • Information seeking is a rich heterogeneous and iterative process. [Bates 1989] [Pirolli and Card, 1995]

  10. Combined Model of Sensemaking and Information Seeking • Sensemaking and information seeking are always happened together and interweave with each other • Representation plays a central role in this model

  11. Design Implication (Part 1) • Support Sensemaking • Support storage and editing of multiple representations • Give suggestions on organizing the collected Information • Show different facets of the information • View representation at different granularities • Support Information Gathering • Help express the information needs • Organize search results

  12. How Humanities Researchers Conduct Their Sensemaking and Information Seeking Tasks (1) • The study of “The Night before Christmas” -- Stephen Nissenbaum • Study of the role the poem played in historical social change. • Moore’s poem was about the privatization of Christmas. And the poem itself seems to have played an important role in bringing about that change. • What we see in this sample of humanities research • The representation of knowledge is gradually evolved. • Search in wide range of information resources. • Various activities are involved: information selection, categorization, connection, reasoning, comparison, etc..

  13. How Humanities Researchers Conduct Their Sensemaking and Information Seeking Tasks (2) • Research methodology • Qualitative “data”/observation, qualitative reasoning, non-experimental • Research Process/Activities • Gathering data (mostly qualitative, primary and secondary sources) • Process/understand data: organize, interpret, qualitatively reasoning, etc. • Writing and publishing • Features: • Wide variety of data resources • Intensive information related activities: organization, connection, aggregation, comparison, reasoning, and interpretation.

  14. Design Decision • Mainly focus on support of sensemaking activities • Support organizing collected information • Support reading and writing • Scenario that resembles typical sensemaking and information seeking actives in humanities research: a researcher constructs a paper outline.

  15. Reading as a Sensemaking Activity • “Readers do not ‘receive’ information. They approach reading in the context of the entire world of their experience, and they turn away with that world confirmed, modified, extended, or challenged” [Gerald, 1994] • “Reading is thinking stimulated by print” [Vaughn 1984], it includes various of activities: categorization; comparing, connecting and organizing ideas; clarifying, generating questions; analyzing, synthesizing… [Gerald, 1994] • People’s writing are representations of their knowledge. Reading is a process transferring other knowledge representation to our own.

  16. Writing as Construction [Bolter, 2001] • A writer begin with a jumble of verbal ideas and only a vague sense of how these ideas will fit together. • He may start by laying out topics in an arrangement less formal than an outline: he may organize by association rather that strict subordination. • Then the writer trims his network by removing connections and establishing subordination until there is a strict hierarchy.

  17. Design Implication (Part 2) • Facilitate reading comprehension • Help note taking • Give suggestions on organizing the collected Information (same as part 1) • Show different facets of the information (same as part 1) • Support outline generation • Support brainstorming and idea formation • Help representation shift from network to tree representation

  18. Design Implication (Repeat) • Support storage and editing of multiple representations • Give suggestions on organizing the collected Information • Show different facets of the information • Help note taking • View representation at different granularity • Support brain storming and idea formation • Help representation shift from network to tree representation • Help express the information needs • Organize search results • Support the iterative information seeking process

  19. Related systems • Research systems: • NoteCrads [Halasz, Moran, and Trigg, 1987] • gIBIS [Conklin and Begeman, 1998] • SenseMaker [Bell, 1997] • SenseMaker [Baldonado and Winograd, 1997] • PowerBookmarks [Li, et al, 1999] • Brainstorming software: • MindManager • ThoughtPath • Bookmark manager: • Check&Get • Private Bookmarks

  20. My Approach Differs in: • A software system is designed to facilitate humanities researchers in their sensemaking and information seeking tasks. • I take as central to my approach the representation search and shift in sensemaking; • Machine learning techniques are intensively used to provide automatic features in information organization and presentation structure manipulation.

  21. System Design - Interface

  22. System Design - Structure

  23. Features to Support Sensemaking • Support Sensemaking • Support storage and editing of network and tree representations • Give suggestions on organizing the collected Information • Show different facets of the information • Note taking functionalities • Help generate the outline

  24. System Function – Basic Tree Editing

  25. System Function – Basic Network Editing

  26. System Function – Clustering/Classification

  27. Clustering/Classification Algorithms • Feature Selection • Document frequency thresholding (DF) • Information gain(IG) • Clustering algorithm - Single-linkage clustering algorithm • Classification algorithm - Semi-Supervised KNN

  28. System Function – Tree Structure Comparison • Two sub-trees from different category schemes are selected, and a node from one sub-tree is colored if it is also appears in another sub-tree.

  29. System Function – Note Taking

  30. System Function – Search

  31. System Functions Under Development • Outline editing tools • Support transformation from network representation to outline • Export outline into XML format

  32. System Evaluation • Qualitative test • Study how doctoral student in humanities using this system in their research. • Observation + Interview • Find out if the system is helpful in those student’s research • Find out the advantage and disadvantage of using this system, comparing to how the students do the tasks before. • Quantitative test • Study whether users who use this system come with better sensemaking results than users who don’t use this system. • How to define “better performance” in sensemaking tasks?

  33. Questions ?

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