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In contrast to a traditional setting where users express queries against the database schema, we assert that the semantics of data can often be understood by viewing the data in the context of the user interface (UI) of the software tool used to enter the data. That is, we believe that users will understand the data in a database by seeing the labels, drop-down menus, tool tips, or other help text that are built into the user interface. Our goal is to allow domain experts with little technical skill to understand and query data. In this paper, we present our GUi As View (Guava) framework and describe how we use forms-based UIs to generate a conceptual model that represents the information in the user interface. We then describe how we generate a query interface from the conceptual model. We characterize the resulting query language using a subset of the relational algebra. Since most application developers want to craft a physical database to meet desired performance needs, we present here a transformation channel that can be configured by instantiating one or more of our transformation operators. The channel, once configured, automatically transforms queries from our query interface into queries that address the underlying physical database and delivers query results that conform to our query interface. In this paper, we define and formalize our database transformation operators. The contributions of this paper are that first, we demonstrate the feasibility of creating a query interface based directly on the user interface and second, we introduce a general purpose database transformation channel that will likely shorten the application development process and increase the quality of the software by automatically generating software artifacts that are often made manually and are prone to errors. [Copyright &y& Elsevier]

A faceted taxonomy is a set of taxonomies, each describing a given knowledge domain from a different aspect. The indexing of the domain objects is done using compound terms, i.e. conjunctive combinations of terms from the taxonomies. A faceted taxonomy has several advantages over a single taxonomy, including conceptual clarity, compactness, and scalability. A drawback, however, is the cost of identifying compound terms that are invalid, i.e. terms that do not apply to any object of the domain. This need arises both in indexing and retrieval, and involves considerable human effort for specifying the valid compound terms one by one. In this paper, we propose and present in detail an algebra which can be used to specify the set of valid compound terms in an efficient and flexible manner. It works on the basis of the original simple terms of the facets and a small set of positive and/or negative statements. In each algebraic operation, we adopt a closed-world assumption with respect to the declared positive or negative statements. In this paper we elaborate on the properties of the algebraic operators and we describe application and methodological issues. [Copyright &y& Elsevier]

Abstract: In this paper we study the ramification problem in the setting of temporal databases. Standard solutions from the literature on reasoning about action are inadequate because they rely on the assumption that fluents persist, and because actions have effects on the next situation only. In this paper we provide a solution to the ramification problem based on an extension of the situation calculus and the work of McCain and Turner. More specifically, we study the case where the effects of an action refer to the past, a particularly complex problem. [Copyright &y& Elsevier]

Abstract: Leveraging on the principle of data minimization, we propose tag suppression, a privacy-enhancing technique for the semantic Web. In our approach, users tag resources on the Web revealing their personal preferences. However, in order to prevent privacy attackers from profiling users based on their interests, they may wish to refrain from tagging certain resources. Consequently, tag suppression protects user privacy to a certain extent, but at the cost of semantic loss incurred by suppressing tags. In a nutshell, our technique poses a trade-off between privacy and suppression. In this paper, we investigate this trade-off in a mathematically systematic fashion and provide an extensive theoretical analysis. We measure user privacy as the entropy of the user''s tag distribution after the suppression of some tags. Equipped with a quantitative measure of both privacy and utility, we find a close-form solution to the problem of optimal tag suppression. Experimental results on a real-world tagging application show how our approach may contribute to privacy protection. [Copyright &y& Elsevier]

Abstract: XML stream applications bring the challenge of efficiently processing queries on sequentially accessible token-based data. For efficient processing of queries, we need to ensure that memory usage stays low. This in turn requires that we avoid holding data in the query buffer, by outputting it at the earliest possible time. In this paper, we propose a new class of stream algebra operators for efficient recursive XQuery stream processing. Our plan generator will analyze the query, and the schema when available to determine which join operators in the query need recursive join support and thus can plug in the more inexpensive just-in-time structural join whenever possible. In particular, we propose two strategies for implementing structural joins: (a) the just-in-time structural join strategy efficiently processes joins over non-recursive XML token streams; and (b) the recursive structural join strategy supports structural joins over recursive XML substreams, however, at an added cost of generating and comparing tuple-level ID. Both structural join strategies are complemented by an automata-driven invocation mechanism that triggers the execution of each join process at the first possible moment upon recognizing the end of the targeted input stream subelement. Further, we design this StructuralJoin operator itself to be context-aware. The operator is capable of at run-time switching from the efficient just-in-time join strategy for elements that are recognized to be non-recursive to the more powerful ID-based structural join strategy for elements that are identified to be recursive. We incorporate the proposed techniques into the Raindrop stream engine. We also report on experimental studies we conducted using the ToXgene benchmark that demonstrate that the performance improvements of the techniques. [Copyright &y& Elsevier]

Personalisation of web information systems (WISs) means customisation of the presented data content to the needs of users, restricting the available functionality to the goals and preferences of users, and tailoring the web presentation according to used devices and style options. This paper primarily concentrates on the customisation of functionality by making all those operations available to a user that are needed to achieve a specified goal, and by organising them in an action scheme called plot that is in accordance with the behavioural preferences of the user. Plots are formalised by algebraic expressions in Kleene algebras with tests (KATs). Then personalisation can be formalised as an optimisation problem with equational preference rules, for which a term rewriting approach is proposed. In a second step the approach is extended to conditional term rewriting thereby dispensing with the particular need to associate preference rules with user profiles. Finally, the approach is refined by taking content specifications via extended views and abstract programs on these views into account. This leads us to reformulating the personalisation problem in higher-order dynamic logic. [Copyright &y& Elsevier]

Abstract: This paper presents a mathematical analysis of different formal ontological theories of parthood (mereologies). We summarize variants of the theory of General Extensional Mereology (GEM) and compare them with their abstract mathematical counterpart, set theory. In particular, we prove by set theoretical means that there exists a model of GEM where arbitrary summation of entities is not possible. Further, we use Stone’s duality theory for Boolean algebras to classify models of the different mereologies. [Copyright &y& Elsevier]

Abstract: In this paper we propose an approach to defining logical database models, based on the instantiation of a general abstract model, and discuss its application to the management of mixed XML/relational data. Our abstract model is equipped with a parametric query algebra and relational-like algebraic equivalences, that do not have to be redefined when new models are generated. We present an instantiation of our model that unifies the main approaches to represent and manipulate relational and XML data, and in particular SQL, SQL/XML, XQuery, and Oracle’s XML Type. Additionally, our algebra can represent queries not expressible by other algebras taken from the literature. Among others, it can represent nested XQuery expressions with no constraints on nesting and on node constructors. [Copyright &y& Elsevier]

Abstract: Many kinds of news report provide information about events. For example, business news reports in the area of mergers and acquisitions, provide information about events such as “company X making a bid for company Y”, or “takeover of company Y by company X being rejected by the anti-trust authorities”. Furthermore, news reports do not normally exist in isolation. There is an underlying narrative which concerns a number of entities related in some way over a period of time. In many domains, stories will follow a stereotypical sequence. For example, a particular takeover may involve a bid being made, a rejection by the target board, a rise in the bid value by the potential buyer, a recommendation of acceptance by the target board, acceptance by the shareholders, and finally successful completion of the takeover. In order to merge heterogeneous news reports that describe events, we need to identify and reason about the events being described prior to merging them. In this paper, we investigate this problem with a focus on structured news reports. Each structured news report (SNR) is an XML document, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume SNRs do not require natural language processing. As each SNR is isomorphic to a term in logic, we use a logic-based approach to extract relevant information about the events being described in the reports to be merged. We then provide a new version of the event calculus to assimilate the information from the various reports, to obtain the most up-to-date and complete picture of the events being described. Finally, from this assimilated information, we generate an SNR as the output. [Copyright &y& Elsevier]

Abstract: XML is an ordered data model and XQuery expressions return results that have a well-defined order. However, little work on how order is supported in XML query processing has been done to date. In this paper we study the issues related to handling order in the XML context, namely challenges imposed by the XML data model, the variety of order requirements of the XQuery language, and the need to maintain order in the presence of updates to the XML data. We propose an efficient solution that addresses all these issues. Our solution is based on a key encoding for XML nodes that serves as node identity and at the same time encodes order. We design rules for encoding order of processed XML nodes based on the XML algebraic query execution model and the node key encoding. These rules do not require any actual sorting for intermediate results during execution. Our approach enables efficient order-sensitive incremental view maintenance as it makes most XML algebra operators distributive with respect to bag union. We prove the correctness of our order encoding approach. Our approach is implemented and integrated with Rainbow, an XML data management system developed at WPI. We have tested the efficiency of our approach using queries that have different order requirements. We have also measured the relative cost of different components related to our order solution in different types of queries. In general the overhead of maintaining order in our approach is very small relative to the query processing time. [Copyright &y& Elsevier]

Abstract: This paper presents the conceptual modelling parts of a methodology for the design of large-scale data-intensive web information systems (WISs) that is based on an abstract abstraction layer model (ALM). It concentrates on the two most important layers in this model: a business layer and a conceptual layer. The major activities on the business layer deal with user profiling and storyboarding, which addresses the design of an underlying application story. The core of such a story can be expressed by a directed multi-graph, in which the vertices represent scenes and the edges actions by the users including navigation. This leads to story algebras which can then be used to personalise the WIS to the needs of a user with a particular profile. The major activities on the conceptual layer address the support of scenes by modelling media types, which combine links to databases via extended views with the generation of navigation structures, operations supporting the activities in the storyboard, hierarchical presentations, and adaptivity to users, end-devices and channels. [Copyright &y& Elsevier]