David F. Huynh

Haystack: a platform for authoring end user semantic web applications

The Semantic Web promises to open innumerable opportunities for automation and information retrieval by standardizing the protocols for metadata exchange. However, just as the success of the World Wide Web can be attributed to the ease of use and ubiquity of Web browsers, we believe that the unfolding of the Semantic Web vision depends on users getting powerful but easy-to-use tools for managing their information. But unlike HTML, which can be easily edited in any text editor, RDF is more complicated to author and does not have an obvious presentation mechanism. Previous work has concentrated on the ideas of generic RDF graph visualization and RDF Schema-based form generation. In this paper, we present a comprehensive platform for constructing end user applications that create, manipulate, and visualize arbitrary RDF-encoded information, adding another layer to the abstraction cake. We discuss a programming environment specifically designed for manipulating RDF and introduce user interface concepts on top that allow the developer to quickly assemble applications that are based on RDF data models. Also, because user interface specifications and program logic are themselves describable in RDF, applications built upon our framework enjoy properties such as network updatability, extensibility, and end user customizability - all desirable characteristics in the spirit of the Semantic Web.

Exhibit: lightweight structured data publishing

The early Web was hailed for giving individuals the same publishing power as large content providers. But over time, large content providers learned to exploit the structure in their data, leveraging databases and server side technologies to provide rich browsing and visualization. Individual authors fall behind once more: neither old-fashioned static pages nor domain-specific publishing frameworks supporting limited customization can match custom database-backed web applications. In this paper, we propose Exhibit, a lightweight framework for publishing structured data on standard web servers that requires no installation, database administration, or programming. Exhibit lets authors with relatively limited skills-those same enthusiasts who could write HTML pages for the early Web-publish richly interactive pages that exploit the structure of their data for better browsing and visualization. Such structured publishing in turn makes that data more useful to all of its consumers: individual readers get more powerful interfaces, mashup creators can more easily repurpose the data, and Semantic Web enthusiasts can feed the data to the nascent Semantic Web.

Piggy bank: experience the semantic web inside your web browser

The Semantic Web Initiative envisions a Web wherein information is offered free of presentation, allowing more effective exchange and mixing across web sites and across web pages. But without substantial Semantic Web content, few tools will be written to consume it; without many such tools, there is little appeal to publish Semantic Web content. To break this chicken-and-egg problem, thus enabling more flexible informa-tion access, we have created a web browser extension called Piggy Bankthat lets users make use of Semantic Web content within Web content as users browse the Web. Wherever Semantic Web content is not available, Piggy Bank can invoke screenscrapers to re-structure information within web pages into Semantic Web format. Through the use of Semantic Web technologies, Piggy Bank provides direct, immediate benefits to users in their use of the existing Web. Thus, the ex-istence of even just a few Semantic Web-enabled sites or a few scrapers already benefits users. Piggy Bank thereby offers an easy, incremental upgrade path to users without requiring a wholesale adoption of the Semantic Webs vision. To further improve this Semantic Web experience, we have created Semantic Bank, a web server application that lets Piggy Bank users share the Semantic Web information they have collected, enabling collaborative efforts to build so-phisticated Semantic Web information repositories through simple, everydays use of Piggy Bank.

Piggy Bank: Experience the Semantic Web inside your web browser

The Semantic Web Initiative envisions a Web wherein information is offered free of presentation, allowing more effective exchange and mixing across web sites and across web pages. But without substantial Semantic Web content, few tools will be written to consume it; without many such tools, there is little appeal to publish Semantic Web content. To break this chicken-and-egg problem, thus enabling more flexible information access, we have created a web browser extension called Piggy Bank that lets users make use of Semantic Web content within Web content as users browse the Web. Wherever Semantic Web content is not available, Piggy Bank can invoke screenscrapers to re-structure information within web pages into Semantic Web format. Through the use of Semantic Web technologies, Piggy Bank provides direct, immediate benefits to users in their use of the existing Web. Thus, the existence of even just a few Semantic Web-enabled sites or a few scrapers already benefits users. Piggy Bank thereby offers an easy, incremental upgrade path to users without requiring a wholesale adoption of the Semantic Webs vision. To further improve this Semantic Web experience, we have created Semantic Bank, a web server application that lets Piggy Bank users share the Semantic Web information they have collected, enabling collaborative efforts to build sophisticated Semantic Web information repositories through simple, everydays use of Piggy Bank.

The role of context in question answering systems

Despite recent advances in natural language question an-swering technology, the problem of designing effective user interfaces has been largely unexplored. We conducted a user study to investigate the problem and discovered that overall, users prefer a paragraph-sized chunk of text over just an exact phrase as the answer to their questions. Fur-thermore, users generally prefer answers embedded in con-text, regardless of the perceived reliability of the source documents. When users research a topic, increasing the amount of text returned to users significantly decreases the number of queries that they pose to the system, suggesting that users utilize supporting text to answer related ques-tions. We believe that these results can serve to guide future developments in question answering user interfaces.

Potluck: data mash-up tool for casual users

As more and more reusable structured data appears on the Web, casual users will want to take into their own hands the task of mashing up data rather than wait for mash-up sites to be built that address exactly their individually unique needs. In this paper, we present Potluck, a Web user interface that lets casual users--those without programming skills and data modeling expertise--mash up data themselves. Potluck is novel in its use of drag and drop for merging fields, its integration and extension of the faceted browsing paradigm for focusing on subsets of data to align, and its application of simultaneous editing for cleaning up data syntactically. Potluck also lets the user construct rich visualizations of data in-place as the user aligns and cleans up the data. This iterative process of integrating the data while constructing useful visualizations is desirable when the user is unfamiliar with the data at the beginning--a common case--and wishes to get immediate value out of the data without having to spend the overhead of completely and perfectly integrating the data first. A user study on Potluck indicated that it was usable and learnable, and elicited excitement from programmers who, even with their programming skills, previously had great difficulties performing data integration.

Enabling web browsers to augment web sites' filtering and sorting functionalities

Existing augmentations of web pages are mostly small cosmetic changes (e.g., removing ads) and minor addition of third-party content (e.g., product prices from competing sites). None leverages the structured data presented in web pages. This paper describes Sifter, a web browser extension that can augment a well-structured web site with advanced filtering and sorting functionality. These added features work inside the sites own pages, preserving the sites presentational style and the users context. Sifter contains an algorithm that scrapes structured data out of well-structured web pages while usually requiring no user intervention. We tested Sifter on real web sites and real users and found that people could use Sifter to perform sophisticated queries and high-level analyses on sizable data collections on the Web. We propose that web sites can be similarly augmented with other sophisticated data-centric functionality, giving users new benefits over the existing Web.

Potluck: Data mash-up tool for casual users

As more and more reusable structured data appears on the Web, casual users will want to take into their own hands the task of mashing up data rather than wait for mash-up sites to be built that address exactly their individually unique needs. In this paper, we present Potluck, a Web user interface that lets casual users-those without programming skills and data modeling expertise-mash up data themselves. Potluck is novel in its use of drag and drop for merging fields, its integration and extension of the faceted browsing paradigm for focusing on subsets of data to align, and its application of simultaneous editing for cleaning up data syntactically. Potluck also lets the user construct rich visualizations of data in-place as the user aligns and cleans up the data. This iterative process of integrating the data while constructing useful visualizations is desirable when the user is unfamiliar with the data at the beginning-a common case-and wishes to get immediate value out of the data without having to spend the overhead of completely and perfectly integrating the data first. A user study on Potluck indicated that it was usable and learnable, and elicited excitement from programmers who, even with their programming skills, previously had great difficulties performing data integration.

User interface continuations

Dialog boxes that collect parameters for commands often create ephemeral, unnatural interruptions of a programs normal execution flow, encouraging the user to complete the dialog box as quickly as possible in order for the program to process that command. In this paper we examine the idea of turning the act of collecting parameters from a user into a first class object called a user interface continuation. Programs can create user interface continuations by specifying what information is to be collected from the user and supplying a callback (i.e., a continuation) to be notified with the collected information. A partially completed user interface continuation can be saved as a new command, much as currying and partially evaluating a function with a set of parameters produces a new function. Furthermore, user interface continuations, like other continuation-passing paradigms, can be used to allow program execution to continue uninterrupted while the user determines a commands parameters at his or her leisure.

Potluck: semi-ontology alignment for casual users

Potluck is a web user interface (Figure 1) that lets casual users-- those without programming skills and data modeling expertise--repurpose heterogeneous Semantic Web data. It lets users merge, navigate, visualize, and clean up data all at the same time, using direct visual manipulation. This iterative process of integrating the data while constructing useful visualizations is desirable when the user is unfamiliar with the data at the beginning--a common case--and wishes to get immediate value out of the data without having to spend the overhead of completely and perfectly integrating the data first.