. gov Toward Digital Government: The Case of Government Statistics Gary Marchionini University of North Carolina at Chapel Hill NSF Grants EIA and EIA Principal Investigators: Gary Marchionini, Stephanie Haas, Ben Shneiderman, Catherine Plaisant, and Carol Hert

. gov Digital Government: Leveraging IT Government information dissemination –Websites –Other publications (no mass ings yet) Transactions –Registrations –Census, regulatory filings –Taxes Policy making –E-voting –E-rules Our work focuses on statistical information and agencies as many important decisions by policy makers and citizens depend on statistics

. gov Preliminary Work Human needs –Interviews (agencies, public) –Transaction log analysis – content analysis System development and testing –Novel interfaces –Information architecture –Usability studies

. gov Focus on Tables Table browser –Java applet –DTD for tables (DC and DDI influence) –XML protocol –Mapping metadata elements to interface control mechanisms –Piping data from large databases to applet –User studies Metadata to aid understanding

. gov Statistical Knowledge Network Create SKN prototype with agency partners Integration –Horizontal integration across federal agencies (BLS, EIA, NCHS, Census, SSA, NASS) –Vertical integration from local/state Focus on non-specialists –Help crucial –Metadata drives help User interfaces are the intermediaries to link people and data Find what you need, understand what you find

. gov Data Flow agency data with integrated metadata agency with multiple metadata repositories agency backend data and metadata Distributed Public Intermediary: variable/concept level, XML-based incorporating ISO and DDI providing java-based statistical literacy tools to user interfaces Statistical Ontology firewall Domain Experts End User Communities Domain Ontologies I n t e r f a c e s U s e r end user end users: interact with data from information/concept perspective, not agency perspective membrane end user end user end user end user

. gov Statistical Knowledge Network Architecture Agencies SKN Registry Actions Contribute Find Display Annotate Understand Manipulate Collaborate ….. …………. Objects Actions Private Work Space Objects Actions Private Work Space Objects Actions Private Work Space OntologyRules & Constraints SKN Consortium …... gov Objects Reports metadata Tables metadata People metadata Glossary Annotations

. gov Interface Prototypes: Find, Display, Understand; Leverage Metadata, Glossary, Ontology Relation Browser Mulitlayered help: treemaps, video help Animated Glossary Contextualizer PairTrees Spatial audio for maps Missing Data

. gov Use Case Scenarios to Guide Design Based on discussions with agency partners 20 scenarios 4 detailed with in depth resources located Used to ground ongoing work

. gov Relation Browser++ displaying all webpages EIA

. gov RB++ with Cursor Over Residential Sector

. gov RB++ showing ‘hous’ typed in title field

. gov Multi-layered interfaces 1 level 3 levels of growing complexity map+table +filters map+table +filters +scatterplot map+table +filters +scatterplot

. gov Animated Demonstration Features

. gov Script Guidelines Base the script on a live demonstration (never on a written description) –Focus on tasks (not tours of widgets or conceptual overviews) –Act out the interaction (with minimum description) then describe results in context of task –Start with a tour of main screen components (orient and introduce vocabulary) 5-10 sec. max –Plan a linear sequences made of very short autonomous chunks (15-60 sec.) Map the chunks to existing online documentation Show text title at beginning of each chunk Carefully synchronize voice and visual (hard when alone) Provide duration and file size for individual chunk

. gov Interactive Glossary Development Tools Provide foundation for content development Separate content development from presentation development Reduce overall development time Maximize reuse of existing elements Create multiple presentations from a single content development effort

. gov Animation Template

. gov Content Foundation Template (SIG) Question initial motivation Answer overview, definition Process explanation, equation Example Result statistic, answer Review summary, interpretation

. gov Animation Template Consistent display and interaction for all animations Presents animation and explanatory text simultaneously Navigate (forward and back) through animation segments Complete review of text at any time

. gov Animation Template Three pieces: text, animations, template Text is tagged with content section tags in a separate text file Animation consists of segments in individual animation files Text and animation segments coordinated by placement in template

. gov ontology Semantic level Classes Relationships Constraint rules DTD/XML Schema Structural level Elements Attributes Datatypes SKN Ontology DTD / XML Schema Interface Tools Statistical Interactive Glossary (SIG) Ontology Applications  Knowledge organization  Content and terminology control  Data integration  Query support  Automatic classification support  Reasoning mechanism  Others modeling implementation

. gov unit aged unit aged unit married couples living together, with husband or wife aged 65 or older age SSA household Domain knowledge Operational knowledge estimate poverty estimate poverty benefit Census Bureau FIFARS earning salary wage income family distribution

. gov Project DTD Investigate DDI and ISO Leverage DDI and data cubes Markup a set of objects –Tables –Reports/press releases Use markup to build added value search (find what you need) and help (understand what you find) support into interfaces

. gov The Basic Structure entDscr_1: description of an entity within the marked up document docDscr : description of the markup-what is being marked-up, who marked it up, etc. entDscr_2: description of an entity within the marked up document varDscr_1: description of each variable within an entity, study group or document stdygrpDscr: describes the “group” to which an entity or document belongs such as a survey program nCubeDscr: used when entity is an aggregated table fileDscr: descripes physical file structures for nCubes varDscr_2: description of each variable within an entity, study group or document

. gov One Example of How the DTD Helps The DTD can help bring the “expert knowledge” to the less expert user and bring relevant information together by enabling searching via variables as well as subjects/keywords

. gov Median income, by age, 2001 age persons Age or older

. gov Discovering Metadata Hybrid machine learning approach –Crawl website –Create term document matrices –Use k-means clustering with small K to fit on screen in RB++ –Revise Use structure in the existing sites to train a classifier For small n of concepts, classify site

. gov Combining Machine Learning and Dynamic Interfaces What should these topics be, and how do we know if we’ve found the right names for them?

. gov Combining Machine Learning and Dynamic Interfaces How do we assign thousands of documents to their respective topics?

. gov Initial, Unstructured Approach doc

. gov Initial, Unstructured Approach doc

. gov Initial, Unstructured Approach doc This approach yielded intuitively coherent clusters. But the clusters fall at too fine a level of granularity, while also wasting large portions of the data. Clustering Based on Word Distributions

. gov New Approach, Semi-Supervised

. gov New Approach, Semi-Supervised doc

. gov New Approach, Semi-Supervised doc This approach capitalizes on the agencies’ efforts and expertise, and so far seems to yield superior results. However, the amount of training data is very sparse, and the observed categories have high correlation in some cases. Our current work addresses these tuning issues.

. gov State Statistical Office USDA / NASS State Cooperative Agency (Dept. of Agriculture,etc.) Farmers & Producers Statistical Consumers Supply data to agencies Obtain data from agencies Collection agents Vertical Integration: Agriculture

. gov Multiple Research Threads for the SKN Interfaces Metadata and Ontology Multi-leveled help Automatic slicing and dicing User needs and user testing Cross agency cooperation See