Paulo Pinheiro da Silva

User interface declarative models and development environments: a survey

Model-Based User Interface Development Environments (MB-UIDEs) provide a context within which user interface declarative models can be constructed and related, as part of the user interface design process. This paper provides a review of MB-UIDE technologies. A framework for describing the elements of a MB-UIDE is presented. A representative collection of 14 MB-UIDEs are selected, described in terms of the framework, compared and analysed from the information available in the literature. The framework can be used as an introduction to the MB-UIDE technology since it relates and provides a description for the terms used inModel-Based User Interface Development Environments (MB-UIDEs) provide a context within which user interface declarative models can be constructed and related, as part of the user interface design process. This paper provides a review of MB-UIDE technologies. A framework for describing the elements of a MB-UIDE is presented. A representative collection of 14 MB-UIDEs are selected, described in terms of the framework, compared and analysed from the information available in the literature. The framework can be used as an introduction to the MB-UIDE technology since it relates and provides a description for the terms used in MB-UIDE papers.

A proof markup language for Semantic Web services

The Semantic Web is being designed to enable automated reasoners to be used as core components in a wide variety of Web applications and services. In order for a client to accept and trust a result produced by perhaps an unfamiliar Web service, the result needs to be accompanied by a justification that is understandable and usable by the client. In this paper, we describe the proof markup language (PML), an interlingua representation for justifications of results produced by Semantic Web services. We also introduce our Inference Web infrastructure that uses PML as the foundation for providing explanations of Web services to end users. We additionally show how PML is critical for and provides the foundation for hybrid reasoning where results are produced cooperatively by multiple reasoners. Our contributions in this paper focus on technological foundations for capturing formal representations of term meaning and justification descriptions thereby facilitating trust and reuse of answers from web agents.

Explaining answers from the Semantic Web: the Inference Web approach

The Semantic Web lacks support for explaining answers from web applications. When applications return answers, many users do not know what information sources were used, when they were updated, how reliable the source was, or what information was looked up versus derived. Many users also do not know how implicit answers were derived. The Inference Web (IW) aims to take opaque query answers and make the answers more transparent by providing infrastructure for presenting and managing explanations. The explanations include information concerning where answers came from (knowledge provenance) and how they were derived (or retrieved). In this article we describe an infrastructure for IW explanations. The infrastructure includes: IWBase - an extensible web-based registry containing details about information sources, reasoners, languages, and rewrite rules; PML - the Proof Markup Language specification and API used for encoding portable proofs; IW browser - a tool supporting navigation and presentations of proofs and their explanations; and a new explanation dialogue component. Source information in the IWBase is used to convey knowledge provenance. Representation and reasoning language axioms and rewrite rules in the IWBase are used to support proofs, proof combination, and Semantic Web agent interoperability. The Inference Web is in use by four Semantic Web agents, three of them using embedded reasoning engines fully registered in the IW. Inference Web also provides explanation infrastructure for a number of DARPA and ARDA projects.

Gradual trust and distrust in recommender systems

Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount of the recommendations. Since trust is often a gradual phenomenon, fuzzy relations are the pre-eminent tools for modeling such networks. However, as current trust-enhanced RSs do not work with the notion of distrust, they cannot differentiate unknown users from malicious users, nor represent inconsistency. These are serious drawbacks in large networks where many users are unknown to each other and might provide contradictory information. In this paper, we advocate the use of a trust model in which trust scores are (trust,distrust)-couples, drawn from a bilattice that preserves valuable trust provenance information including gradual trust, distrust, ignorance, and inconsistency. We pay particular attention to deriving trust information through a trusted third party, which becomes especially challenging when also distrust is involved.

Teallach: a model-based user interface development environment for object databases

Abstract Model-based user interface development environments show promise for improving the productivity of user interface developers, and possibly for improving the quality of developed interfaces. While model-based techniques have previously been applied to the area of database interfaces, they have not been specifically targeted at the important area of object database applications. Such applications make use of models that are semantically richer than their relational counterparts in terms of both data structures and application functionality. In general, model-based techniques have not addressed how the information referenced in such applications is manifested within the described models, and is utilised within the generated interface itself. This lack of experience with such systems has led to many model-based projects providing minimal support for certain features that are essential to such data intensive applications, and has prevented object database interface developers in particular from benefiting from model-based techniques. This paper presents the Teallach model-based user interface development environment for object databases, describing the models it supports, the relationships between these models, the tool used to construct interfaces using the models and the generation of Java programs from the declarative models. Distinctive features of Teallach include comprehensive facilities for linking models, a flexible development method, an open architecture, and the generation of running applications based on the models constructed by designers.

UMLi: the unified modeling language for interactive applications

User interfaces (UIs) are essential components of most software systems, and significantly affect the effectiveness of installed applications. In addition, UIs often represent a significant proportion of the code delivered by a development activity. However, despite this, there are no modelling languages and tools that support contract elaboration between UI developers and application developers. The Unified Modeling Language (UML) has been widely accepted by application developers, but not so much by UI designers. For this reason, this paper introduces the notation of the Unified Modelling Language for Interactive Applications (UMLi), that extends UML, to provide greater support for UI design. UI elements elicited in use cases and their scenarios can be used during the design of activities and UI presentations. A diagram notation for modelling user interface presentations is introduced. Activity diagram notation is extended to describe collaboration between interaction and domain objects. Further, a case study using UMLi notation and method is presented.

IWTrust: improving user trust in answers from the web

Question answering systems users may find answers without any supporting information insufficient for determining trust levels. Once those question answering systems begin to rely on source information that varies greatly in quality and depth, such as is typical in web settings, users may trust answers even less. We address this problem by augmenting answers with optional information about the sources that were used in the answer generation process. In addition, we introduce a trust infrastructure, IWTrust, which enables computations of trust values for answers from the Web. Users of IWTrust have access to sources used in answer computation along with trust values for those source, thus they are better able to judge answer trustworthiness.

Infrastructure for web explanations

The Semantic Web lacks support for explaining knowledge provenance. When web applications return answers, many users do not know what information sources were used, when they were updated, how reliable the source was, or what information was looked up versus derived. The Semantic Web also lacks support for explaining reasoning paths used to derive answers. The Inference Web (IW) aims to take opaque query answers and make the answers more transparent by providing explanations. The explanations include information concerning where answers came from and how they were derived (or retrieved). In this paper we describe an infrastructure for IW explanations. The infrastructure includes: an extensible web-based registry containing details on information sources, reasoners, languages, and rewrite rules; a portable proof specification; and a proof and explanation browser. Source information in the IW registry is used to convey knowledge provenance. Representation and reasoning language axioms and rewrite rules in the IW registry are used to support proofs, proof combination, and semantic web agent interoperability. The IW browser is used to support navigation and presentations of proofs and their explanations. The Inference Web is in use by two Semantic Web agents using an embedded reasoning engine fully registered in the IW. Additional reasoning engine registration is underway in order to help provide input for evaluation of the adequacy, breadth, and scalability of our approach.

Web explanations for semantic heterogeneity discovery

Managing semantic heterogeneity is a complex task. One solution involves matching like terms to each other. We view Match as an operator that takes two graph-like structures (e.g., concept hierarchies or ontologies) and returns a mapping between the nodes of the graphs that correspond semantically to each other. While some state of the art matching systems may produce effective mappings, these mappings may not be intuitively obvious to human users. In order for users to trust the mappings, and thus, use them, they need information about them (e.g., they need access to the sources that were used to determine semantic correspondences between terms). In this paper we describe how a matching system can explain its answers using the Inference Web (IW) infrastructure thus making the matching process transparent. The proposed solution is based on the assumption that mappings are computed by logical reasoning. There, S-Match, a semantic matching system, produces proofs and explanations for mappings it has discovered.

Generating user interface code in a model based user interface development environment

Declarative models play an important role in most software design activities, by allowing designs to be constructed that selectively abstract over complex implementation details. In the user interface setting, Model-Based User Interface Development Environments (MB-UIDEs) provide a context within which declarative models can be constructed and related, as part of the interface design process. However, such declarative models are not usually directly executable, and may be difficult to relate to existing software components. It is therefore important that MB-UIDEs both fit in well with existing software architectures and standards, and provide an effective route from declarative interface specification to running user interfaces. This paper describes how user interface software is generated from declarative descriptions in the Teallach MB-UIDE. Distinctive features of Teallach include its open architecture, which connects directly to existing applications and widget sets, and the generation of executable interface applications in Java. This paper focuses on how Java programs, organized using the model-view-controller pattern (MVC), are generated from the task, domain and presentation models of Teallach.