Facilitate Humanities Researchers in Sensemaking and Information Seeking Tasks Yan Qu School of Information firstname.lastname@example.org 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 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 Research Problem • How could a software system facilitate humanities researchers in their sensemaking and information seeking tasks 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 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 Dervin‟s Sensemaking Model • Dervin‟s sensemaking triangle show the close relationship between sensemaking and information seeking activities Situation Help Gap Russell et al‟s Sensemaking Model • Russell‟s sensemaking model posits the use of representations in service of accomplishing some tasks. Search for good representation Generation Loop Representational Representaaions Residue Shift Loop Instantiate Repersentations Data Coverage Loop Information Seeking Cycle • Information seeking is a rich heterogeneous and iterative process. [Bates 1989] [Pirolli and Card, 1995] Expressed Informtion Needs Formalize Search Information Needs Information World Understand and Use Search Search Results 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 Residue, Knowledge gap Expressed (Information Need) Information Needs Information Representational Representation World Shift Loop Search Results Representational Evolution 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 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.. 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. 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. 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. 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. 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 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 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 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. System Design - Interface Tree of Gathered Information Network/Outline representation Tree Node Summary System Design - Structure User Interface Network structure Text Processing Manipulation DB Users’ Representation Info Clustering and Tree Structure Classification Web Resources Manipulation Outline Editing Vivisimo Clustering Search Engine Web 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 System Function – Basic Tree Editing Tree Structure Editing Tree Node Editing (a) Interface of basic tree editing tools (b) Interface of keywords editor System Function – Basic Network Editing Network Structure Editing Pane Gathered data is organized in different groups Interface of basic network editing tools System Function – Clustering/Classification Clustering documents under the selected folder Classify documents under the selected folder (b) Example clustering result (c) Example classification result with the sample documents marked with different background (a) Interface of Clustering/Classification Tool Clustering/Classification Algorithms • Feature Selection – Document frequency thresholding (DF) – Information gain(IG) • Clustering algorithm - Single-linkage clustering algorithm • Classification algorithm - Semi- Supervised KNN 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. (a) Interface of tree structure comparison tool (b) An example of tree structure comparison: the distribution of economic news in China news System Function – Note Taking Interface of note editing tool System Function – Search Choices of how the query forms Choices of how the result is organized (a) Interface of the basic search tool (b) Search result organized in tree structure System Functions Under Development • Outline editing tools • Support transformation from network representation to outline • Export outline into XML format 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? Questions ?