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Many hypermedia models have been proposed, including those specifically developed to model navigational aspects of web sites. But few hypermedia systems have been implemented based on metamodelling principles familiar to the database community. Often there is no clear separation between conceptual and technical issues in the models and their implementations are not based on an explicit representation of a metamodel. This results in a loss of generality and uniformity across systems. Based on principles of metamodel-driven system development, we have implemented a platform that can support various categories of hypermedia systems through the generality and extensibility of the metamodel. We present our metamodel and show how it generalises concepts present in a range of hypermedia and link server systems. [ABSTRACT FROM AUTHOR]

In designing software systems, security is typically only one design objective among many. It may compete with other objectives such as functionality, usability, and performance. Too often, security mechanisms such as firewalls, access control, or encryption are adopted without explicit recognition of competing design objectives and their origins in stakeholder interests. Recently, there is increasing acknowledgement that security is ultimately about trade-offs. One can only aim for "good enough" security, given the competing demands from many parties. In this paper, we examine how conceptual modeling can provide explicit and systematic support for analyzing security trade-offs. After considering the desirable criteria for conceptual modeling methods, we examine several existing approaches for dealing with security trade-offs. From analyzing the limitations of existing methods, we propose an extension to the i* framework for security trade-off analysis, taking advantage of its multi-agent and goal orientation. The method was applied to several case studies used to exemplify existing approaches. [ABSTRACT FROM AUTHOR]

Collections play an important part in everyday life. Therefore, conceptual data models should support collection types to make data modeling as natural as possible for its users. Based on the fundamental properties of endorsing order and multiplicity of its elements we introduce the collection types of rankings, lists, sets and bags into the framework of Entity-Relationship modeling. This provides users with easy-to-use constructors that naturally model different kinds of collections. Moreover, we propose a transformation of extended ER schemata into relational database schemata. The transformation is intuitive and invertable introducing surrogate attributes that preserve the semantics of the collection. Furthermore, it is a proper extension to previous transformations, and results in a relational database schema that is in Inclusion Dependency Normal Form. In addition, we introduce a uniqueness constraint that identifies collections uniquely and guarantees referential integrity at the same time. [ABSTRACT FROM AUTHOR]

In this paper we study the problem of schema exchange, a natural extension of the data exchange problem to an intensional level. To this end, we first introduce the notion of schema template, a tool for the representation of a class of schemas sharing the same structure. We then define the schema exchange notion as the problem of (i) taking a schema that matches a source template, and (ii) generating a new schema for a target template, on the basis of a set of dependencies defined over the two templates. This framework allows the definition, once for all, of generic transformations that work for several schemas. A method for the generation of a "correct" solution of the schema exchange problem is proposed and a number of general results are given. We also show how it is possible to generate automatically a data exchange setting from a schema exchange solution. This allows the definition of queries to migrate data from a source database into the one obtained as a result of a schema exchange. [ABSTRACT FROM AUTHOR]

It is increasingly recognised that user preferences should be addressed in many advanced database applications, such as adaptive searching in databases. However, the fundamental issue of how preferences impact the semantics and rankings in a relation is not resolved. In this paper, we model a user preference term involving one attribute as a hierarchy of its underlying data values and formalise the notion of Prioritized Preferences (PPs). We then consider multiple user preferences in ranking tuples in a relational table. We examine the impact of a given set of PPs on possible choices in ranking a database relation and develop a new notion of Choice Constraints (CCs) in a relation, r. Given two PPs, X and Y, a CC, X ≤ Y, is satisfied in r, if the choice of rankings according to Y is no less than that of X. Our main results are related to these two notions of PPs and CCs and their interesting interactions with the well-known Functional Dependencies (FDs). First, we exhibit a sound and complete set of three inference rules for PPs and further prove that for each closed set of PPs, there exists a ranking that precisely satisfies these preferences. Second, we establish a sound and complete set of five inference rules for CCs. Finally, we show the soundness and completeness of two mixed systems of FD-PPs and FD-CCs. All these results are novel and fundamental to incorporating user preferences in database design and modelling, since PPs, CCs and FDs together capture rich semantics of preferences in databases. [ABSTRACT FROM AUTHOR]

Since Chen's Entity-Relationship (ER) model, conceptual modelling has been playing a fundamental role in relational data design. In this paper we consider an extended ER model enriched with cardinality constraints, disjunction assertions, and is-a relations among both entities and relationships; we present a framework in which the data underlying an ER schema can be directly queried through the schema by using suitable predicates. In this setting, we consider the case of incomplete data, which is likely to happen, for instance, when data from different sources are integrated. We address the problem of providing correct answers to conjunctive queries by reasoning on the schema. Based on previous results about decidability of the problem, we provide a query answering algorithm based on rewriting the initial query into a recursive Datalog query, in which the information about the schema is encoded. We finally give some complexity results, and we show extensions to more general settings. [ABSTRACT FROM AUTHOR]

Vague information is common in many database applications due to internet-scale data dissemination, such as those data arising from sensor networks and mobile communications. We have formalized the notion of a vague relation in order to model vague data in our previous work. In this paper, we utilize Functional Dependencies (FDs), which are the most fundamental integrity constraints that arise in practice in relational databases, to maintain the consistency of a vague relation. The problem we tackle is, given a vague relation r over a schema R and a set of FDs F over R, what is the "best" approximation of r with respect to F when taking into account of the median membership (m) and the imprecision membership (i) thresholds. Using these two thresholds of a vague set, we define the notion of mi-overlap between vague sets and a merge operation on r. Satisfaction of an FD in r is defined in terms of values being mi-overlapping. We show that Lien's and Atzeni's axiom system is sound and complete for FDs being satisfied in vague relations. We study the chase procedure for a vague relation r over R, named VChase(r, F), as a means to maintain consistency of r with respect to F. Our main result is that the output of the procedure is the most object-precise approximation of r with respect to F. The complexity of VChase(r, F) is polynomial time in the sizes of r and F. [ABSTRACT FROM AUTHOR]

Classification is a key concept in conceptual modeling. However, the recognition that there might be different kinds of classes has received limited attention in conceptual modeling research. Most work has focused on the concept of role. However, confusion exists on the definition, properties, and representation of role. In this paper, we propose a metamodel of classifiers based on ontological foundations. We focus on the notion of role in the object-oriented and conceptual modeling literature. The metamodel conforms to the fundamental role features identified in the literature and handles several problems associated with role modeling. Furthermore, we contrast conceptual models created using our metamodel to those created using traditional ER or class modeling approaches, and highlight the database design implications of the differences. Using examples, we demonstrate that relational database schemata generated using our approach are more stable with respect to changing requirements. [ABSTRACT FROM AUTHOR]

An information system maintains a representation of the state of the domain in its Information Base (IB). The state of the IB changes due to the execution of the operations defined in the behavioral schema. There are two different approaches for specifying the effect of an operation: the imperative and the declarative approaches. In conceptual modeling, the declarative approach is preferable since it allows a more abstract and concise definition of the operation effect and conceals all implementation issues. Nevertheless, in order to execute the conceptual schema, declarative specifications must be transformed into equivalent imperative ones. Unfortunately, declarative specifications may be non-deterministic. This implies that there may be several equivalent imperative versions for the same declarative specification, which hampers the transformation process. The main goal of this paper is to provide a pattern-based translation method between both specification approaches. To facilitate the translation we propose some heuristics that improve the precision of declarative specifications and help avoid non-determinism in the translation process. [ABSTRACT FROM AUTHOR]

The goal of this article is to formalize Object Role Modeling (ORM) using the $\mathcal{DLR}$ description logic. This would enable automated reasoning on the formal properties of ORM diagrams, such as detecting constraint contradictions and implications. In addition, the expressive, methodological, and graphical capabilities of ORM make it a good candidate for use as a graphical notation for most description logic languages. In this way, industrial experts who are not IT savvy will still be able to build and view axiomatized theories (such as ontologies, business rules, etc.) without needing to know the logic or reasoning foundations underpinning them. Our formalization in this paper is structured as 29 formalization rules, that map all ORM primitives and constraints into $\mathcal{DLR}$, and 2 exceptions of complex cases. To this end, we illustrate the implementation of our formalization as an extension to DogmaModeler, which automatically maps ORM into DIG and uses Racer as a background reasoning engine to reason about ORM diagrams. [ABSTRACT FROM AUTHOR]

Variance in business process execution can be the result of several situations, such as disconnection between documented models and business operations, workarounds in spite of process execution engines, dynamic change and exception handling, flexible and ad-hoc approaches, and collaborative and/or knowledge intensive work. It is imperative that effective support for managing process variance be extended to organizations mature in their BPM (Business Process Management) uptake so that they can ensure organization wide consistency, promote reuse and capitalize on their BPM investments. Process variants are complex objects that contain features of different dimensions, such as variant design or variant execution data. This paper provides a technique for effective utilization of the adaptations manifested in process variants. In particular, we will present a facility for discovery of preferred variants through effective search and retrieval based on the notion of process similarity, where multiple aspects of the process variants are compared according to specific query requirements. The major advantage of this approach is the ability to provide a quantitative measure for the similarity between process variants, which further facilitates various BPM activities such as process reuse, analysis and discovery. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to derive views over a relational database by applying a sequence of appropriately defined operations to the global schema. Such tailoring and composition process aims at offering personalized views over the database schema, so as to improve its ability to support the new needs of customers, support evolutionary software development, and fix existing legacy database design problems. The process is driven by the designer's knowledge of the possible operational contexts, in terms of the various dimensions that contribute to determine which portions of the global schema are relevant with respect to the different actors and situations. We formally introduce some operators, defined on sets of relations, which tailor the schema and combine the intermediate views to derive different final views, suitable for the different envisioned situations. The application to a case study is also presented, to better clarify the proposed approach. [ABSTRACT FROM AUTHOR]

Schema mappings come in different flavors: simple correspondences are produced by schema matchers, intensional mappings are used for schema integration. However, the execution of mappings requires a formalization based on the extensional semantics of models. This problem is aggravated if multiple metamodels are involved. In this paper we present extensional mappings, that are based on second order tuple generating dependencies, between models in our Generic Role-based Metamodel GeRoMe. By using a generic metamodel, our mappings support data translation between heterogeneous metamodels. Our mapping representation provides grouping functionalities that allow for complete restructuring of data, which is necessary for handling nested data structures such as XML and object oriented models. Furthermore, we present an algorithm for mapping composition and optimization of the composition result. To verify the genericness, correctness, and composability of our approach we implemented a data translation tool and mapping export for several data manipulation languages. [ABSTRACT FROM AUTHOR]

This paper describes a rule-based algorithm to derive a relational schema from an extended entity-relationship model. Our work is based on an approach by Atzeni and Torlone in which the source EER model is imported into a universal metamodel, a series of transformations are performed to eliminate constructs not appearing in the relational metamodel, and the result is exported. Our algorithm includes novel features that are needed for practical object to relational mapping systems: First, it generates forward- and reverse-views that transform instances of the source model into instances of the target and back again. These views automate the object-to-relational (O/R) mapping. Second, it supports a flexible mapping of inheritance hierarchies to flat relations that subsumes and extends prior approaches. Third, it propagates incremental updates of the source model into incremental updates of the target. We prove the algorithm's correctness and demonstrate its practicality in an implementation. [ABSTRACT FROM AUTHOR]

The emerging area of business process intelligence attempts to enhance the analytical capabilities of business process management systems by employing data warehousing and mining technologies. This paper presents an approach to re-engineering the business process modeling in conformity with the multidimensional data model. Since the business process and the multidimensional model are driven by rather different objectives and assumptions, there is no straightforward solution to converging these models. Our case study is concerned with Surgical Process Modeling which is a new and promising subdomain of business process modeling. We formulate the requirements of an adequate multidimensional presentation of process data, introduce the necessary model extensions and propose the structure of the data cubes resulting from applying vertical decomposition into flow objects, such as events and activities, and from the dimensional decomposition according to the factual perspectives, such as function, organization, and operation. The feasibility of the presented approach is exemplified by demonstrating how the resulting multidimensional views of surgical workflows enable various perspectives on the data and build a basis for supporting a wide range of analytical queries of virtually arbitrary complexity. [ABSTRACT FROM AUTHOR]

The major purpose of the design of distributed databases is to improve system performance and to increase system reliability. Fragmentation and allocation play important roles in the development of a cost-efficient system. This paper addresses the problem of fragmentation in the context of complex value databases, which cover the common aspects of object-oriented databases, object-relational databases and XML. In this paper, we present a cost-based approach for horizontal and vertical fragmentation. Our approach is based on a cost model that takes the structure of complex value databases into account. [ABSTRACT FROM AUTHOR]

Service-oriented architecture (SOA) is rapidly becoming the dominant paradigm for next generation information systems. It has been recognized, however, that the full benefits of SOA would not be realized unless its capabilities are exploited at the business level. In the business arena, innovations in e-business have led to the identification and classification of business models and analysis of their properties. To ease the transition from business design to service-oriented system design, we propose a reference catalog approach. Recurring business designs are collected, pre-analyzed, and documented as a set of reference business models, following a standardized template. Each reference business model is realized through a set of service-oriented design patterns. The i* framework is the basis for modeling and analysis at both the business and service design level, taking advantage of its agent orientation for modeling service relationships, and its goal orientation to facilitate adaptation from generic patterns to specific needs. [ABSTRACT FROM AUTHOR]

Data warehouses integrate several operational sources to provide a multidimensional (MD) analysis of data. Therefore, the development of a data warehouse claims for an in-depth analysis of these data sources. Several approaches have been presented to obtain multidimensional structures from data sources in order to guide this development. However, these approaches assume that a wide documentation of the data sources is available and only provide informal guidelines to support the discovery of MD elements. Therefore, this task may become highly difficult for complex and large data sources (e.g. legacy systems). To overcome these problems, we consider the development of the data warehouse as a modernization scenario that addresses the analysis of the available data sources, thus discovering MD structures to either derive a data-driven conceptual MD model or reconcile a requirement-driven conceptual MD model with data sources. Specifically, we use concepts from Architecture Driven Modernization (ADM) in order to automatically perform the following tasks: (i) obtain a logical representation of data sources (ii) mark this logical representation with MD concepts, and (iii) derive a conceptual MD model from the marked model. Finally, we have provided a case study based on a real world project in order to exemplify the application of our approach. [ABSTRACT FROM AUTHOR]

In the traditional waterfall approach for building a software application, the phases of requirements analysis, design, implementation, testing, and maintenance follow one another. Aiming at the efficiency of a database application, we see that the outcome of the implementation phase decisively determines how much time the execution of queries and updates requires and how much space is needed to store the application data. But, these costs of the application result from decisions made not only in the implementation phase but also before that during the design phase. In this paper, we describe a tool to support the cost-based design of database applications. Based on earlier research where we designed a cost-model for an abstract object-oriented database machine, the tool shall provide its user with cost estimates during the design phase. We discuss which modifications and additions to our cost-model we use to build the tool. Specifically, we portray how we adapt the tool to a concrete DBMS. After picturing a design process that employs our tool, we conclude by assessing the achievements of the present work and how we benefited from our earlier underlying research. [ABSTRACT FROM AUTHOR]

In many online shopping applications, such as Amazon and eBay, traditional Association Rule (AR) mining has limitations as it only deals with the items that are sold but ignores the items that are almost sold (for example, those items that are put into the basket but not checked out). We say that those almost sold items carry hesitation information, since customers are hesitating to buy them. The hesitation information of items is valuable knowledge for the design of good selling strategies. However, there is no conceptual model that is able to capture different statuses of hesitation information. Herein, we apply and extend vague set theory in the context of AR mining. We define the concepts of attractiveness and hesitation of an item, which represent the overall information of a customer's intent on an item. Based on the two concepts, we propose the notion of Vague Association Rules (VARs). We devise an efficient algorithm to mine the VARs. Our experiments show that our algorithm is efficient and the VARs capture more specific and richer information than do the traditional ARs. [ABSTRACT FROM AUTHOR]

We propose a small set of parameterized abstract models for workflow patterns, starting from first principles for sequential and distributed control. Appropriate instantiations yield the 43 workflow patterns that have been listed recently by the Business Process Modeling Center. The resulting structural classification of those patterns into eight basic categories, four for sequential and four for parallel workflows, provides a semantical foundation for a rational evaluation of workflow patterns. [ABSTRACT FROM AUTHOR]

This paper gives an outline of my PhD thesis which describes the integration of managing uncertainty into ontology mapping. Ontology mapping is one of the most important tasks for ontology interoperability and its main aim is to find semantic relationships between entities (i.e. concept, attribute, and relation) of two ontologies, However, in the process of mapping, uncertainty and incompleteness of semantics in the syntactic representation and description of relations between entities in ontologies will lead to imprecise results. If we want to obtain better results, it becomes more significant for the ontology mapping to be able to deal with uncertainty. [ABSTRACT FROM AUTHOR]

Our research explores the possibilities for factoring culture into user models, working towards cultural adaptivity in the Semantic Web. The aim is to automate the localization process by acquiring details about an individual's cultural background. The paper shows how we have based our approach on research findings from related fields, outlining the connection between the cultural user and domain model ontologies, and a test environment. Furthermore, we describe a preliminary plan of how to validate our cultural user model by comparison to our previous experience in the manual adaptation of imbuto. [ABSTRACT FROM AUTHOR]

The use of tags to describe Web resources in a collaborative manner has experienced rising popularity among Web users in recent years. The product of such activity is given the name folksonomy, which can be considered as a scheme of organizing information in the users' own way. This research work attempts to analyze tripartite graphs - graphs involving users, tags and resources - of folksonomies and discuss how these elements acquire their semantics through their associations with other elements, a process we call mutual contextualization. By studying such process, we try to identify solutions to problems such as tag disambiguation, retrieving documents of similar topics and discovering communities of users. This paper describes the basis of the research work, mentions work done so far and outlines future plans. [ABSTRACT FROM AUTHOR]

Recent work in the field of middleware technology proposes semantic spaces as a tool for coping with the scalability, heterogeneity and dynamism issues of large scale distributed environments. Reflective middleware moreover offers answers to the needs for adaptivity and self-determination of systems. Based on experiences with traditional middleware we argue that ontology-driven management is a major advancement for semantic spaces and provides the fundamental means for reflection. In this research we look at ontology-based metadata to turn semantic spaces into reflective middleware. [ABSTRACT FROM AUTHOR]

This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to compute the exact scope of conditions over text sequences expressing the required actions. We present in this paper the rules developed for this task. We show that the system yields good performance when applied to the analysis of French practice guidelines. [ABSTRACT FROM AUTHOR]

Instance-based ontology mapping is a promising family of solutions to a class of ontology alignment problems. It crucially depends on measuring the similarity between sets of annotated instances. In this paper we study how the choice of co-occurrence measures affects the performance of instance-based mapping. To this end, we have implemented a number of different statistical co-occurrence measures. We have prepared an extensive test case using vocabularies of thousands of terms, millions of instances, and hundreds of thousands of co-annotated items. We have obtained a human Gold Standard judgement for part of the mapping-space. We then study how the different co-occurrence measures and a number of algorithmic variations perform on our benchmark dataset as compared against the Gold Standard. Our systematic study shows excellent results of instance-based matching in general, where the more simple measures often outperform more sophisticated statistical co-occurrence measures. [ABSTRACT FROM AUTHOR]

Unsatisfactory performance of ontology mapping methods on many tasks seems to indicate the need for employing some background knowledge. My PhD work focuses on exploiting pattern-like structures for this purpose. Design patterns are related to different styles of modelling ontology structure and/or naming of concepts. On the other hand, mapping patterns emerge as result of the mapping process. Preliminary results and schedule of future work are presented. [ABSTRACT FROM AUTHOR]

We propose a logic-based framework to model negotiations among agents in scenarios with fully incomplete information. In particular, we address multi-issue bilateral negotiations, with issues are expressed and related to each other via an OWL ontology. In particular we use OWL-DL sub-language and exploit its formal semantics, based on $\mathcal{SHOIN}(D)$. Agents goals are expressed through OWL-DL as (complex) concept expressions, and the worth of goals as weights over concepts. Noteworthily, we adopt a very general setting with incomplete information by letting agents keep both goals and worths of goals as private information. Moreover we propose a protocol for agents to negotiate on and reach an agreement, exploiting inference services. Agents, according to the protocol, can pursue different sets of strategies —depending on their type— and we illustrate and motivate two possible strategies. [ABSTRACT FROM AUTHOR]

Only few well-maintained domain ontologies can be found on the Web. The likely reasons for the lack of useful domain ontologies include that (1) informal means to convey intended meaning more efficiently are used for ontology specification only to a very limited extent, (2) many relevant domains of discourse show a substantial degree of conceptual dynamics, (3) ontology representation languages are hard to understand for the majority of (potential) ontology users and domain experts, and (4) the community does not have control over the ontology evolution. In this thesis, we propose to (1) ground a methodology for community-grounded ontology building on the culture and philosophy of wikis by giving users who have no or little expertise in ontology engineering the opportunity to contribute in all stages of the ontology lifecycle and (2) exploit the combination of human and computational intelligence to discover and resolve inconsistencies and align lightweight domain ontologies. The contribution of this thesis is a methodology and prototype for community-grounded building and evolution of lightweight domain ontologies. [ABSTRACT FROM AUTHOR]

The Semantic Web (SW) has been envisioned to enable software tools or Web Services, respectively, to process information provided on the Web automatically. For this purpose, languages for representing the semantics of data by means of ontologies have been proposed such as RDF(S) and OWL. While the semantics of RDF(S) requires a non-standard model-theory that goes beyond first order logics, OWL is intended to model subsets of first order logics. OWL consists of three variants that are layered on each other. The less expressive variants OWL-Light and OWL-DL correspond to the Description Logics $\mathcal{SHIF}$(D) and $\mathcal{SHOIN}$(D) [1], respectively, and thus to subsets of First Order Logics [2]. [ABSTRACT FROM AUTHOR]

Ontology mapping is to find semantic correspondences between similar elements of different ontologies. It is critical to achieve semantic interoperability in the WWW. This paper proposes a new generic and scalable ontology mapping approach based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information, measures the similarity of different elements of ontologies in a vector space model, and deals with constraints using the interactive activation network. The results of pilot study, the PRIOR, are promising and scalable. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Many enterprise systems face the same kind of information processing problems that exist on the web in general, and creating semantic solutions often involve constructing an enterprise ontology. Ontology engineering in turn needs to be semi-automatic in order to reduce the effort and need for expertise. By introducing knowledge reuse in ontology construction the construction effort can be further reduced and the quality of the ontology output increased. The proposed research focuses on a hybrid approach for ontology construction based on the methodology of case-based reasoning in combination with ontology patterns. [ABSTRACT FROM AUTHOR]

The move towards a semantic web has been in progress for many years and more recently there have been applications that make use of semantic web technology. One of the features that made the Web so easy to use is the ability to search web pages in a matter of seconds through the use of search engines. Now that the use of OWL and RDF as a knowledge representation format is increasing, the possibility appears to improve the quality of searching by using the semantic web to enhance the ‘ordinary' Web. This paper outlines an architecture for using distributed knowledge bases to assist and improve searching on the web. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The main objective of the CHIP project is to demonstrate how Semantic Web technologies can be deployed to provide personalized access to digital museum collections. We illustrate our approach with the digital database ARIA of the Rijksmuseum Amsterdam. For the semantic enrichment of the Rijksmuseum ARIA database we collaborated with the CATCH STITCH project to produce mappings to Iconclass, and with the MultimediaN E-culture project to produce the RDF/OWL of the ARIA and Adlib databases. The main focus of CHIP is on exploring the potential of applying adaptation techniques to provide personalized experience for the museum visitors both on the Web site and in the museum. [ABSTRACT FROM AUTHOR]

The ICT landscape is developing into a highly-interactive distributed environment in which people interact with multiple devices (e.g. portable devices such as mobile phones and home equipment such as TV's) and multiple applications (e.g. computer programs such as Web browsers and dedicated Web services) [1]. Globally, the industry is being driven by the shift away from old models - from physical space to digital space. New methods emerge for getting content such as TV programs via the Web. Almost half of the people want to watch TV content on their PC's; they want to make a bridge between a TV and a PC, perhaps even sitting in a home office [2]. The information overload is enormous and the content presented is hardly adapted to the prior knowledge, to the preferences and to the current situation of the user. [ABSTRACT FROM AUTHOR]

Revyu.com is a live, publicly accessible reviewing and rating Web site, designed to be usable by humans whilst transparently generating machine-readable RDF metadata for the Semantic Web, based on their input. The site uses Semantic Web specifications such as RDF and SPARQL, and the latest Linked Data best practices to create a major node in a potentially Web-wide ecosystem of reviews and related data. Throughout the implementation of Revyu design decisions have been made that aim to minimize the burden on users, by maximizing the reuse of external data sources, and allowing less structured human input (in the form of Web2.0-style tagging) from which stronger semantics can later be derived. Links to external sources such as DBpedia are exploited to create human-oriented mashups at the HTML level, whilst links are also made in RDF to ensure Revyu plays a first class role in the blossoming Web of Data. The site is available at . [ABSTRACT FROM AUTHOR]

Grouping is an attractive interaction metaphor for users to create reference collections of Web resources they are interested in. Each grouping activity has a certain semantics: things which were previously unrelated are now connected with others via the group. We present the GroupMe! application which allows users to group and arrange multimedia Web resources they are interested in. GroupMe! has an easy-to-use interface for gathering and grouping of resources, and allows users to tag everything they like. The semantics of any user interaction is captured, transformed and stored as adequate RDF descriptions. As an example application of this automatically derived RDF content, we show the enhancement of search for tagged Web resources, which evaluates the grouping information to deduce additional contextual information about the resources. GroupMe! is available via http://www.groupme.org. [ABSTRACT FROM AUTHOR]

Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution. [ABSTRACT FROM AUTHOR]

This paper describes a large case study that explores the applicability of ontology reasoning to problems in the medical domain. We investigate whether it is possible to use such reasoning to automate common clinical tasks that are currently labor intensive and error prone, and focus our case study on improving cohort selection for clinical trials. An obstacle to automating such clinical tasks is the need to bridge the semantic gulf between raw patient data, such as laboratory tests or specific medications, and the way a clinician interprets this data. Our key insight is that matching patients to clinical trials can be formulated as a problem of semantic retrieval. We describe the technical challenges to building a realistic case study, which include problems related to scalability, the integration of large ontologies, and dealing with noisy, inconsistent data. Our solution is based on the SNOMED CT® ontology, and scales to one year of patient records (approx. 240,000 patients). [ABSTRACT FROM AUTHOR]

Data warehouse is now widely used in business analysis and decision making processes. To adapt the rapidly changing business environment, we develop a tool to make data warehouses more business-friendly by using Semantic Web technologies. The main idea is to make business semantics explicit by uniformly representing the business metadata (i.e. conceptual enterprise data model and multidimensional model) with an extended OWL language. Then a mapping from the business metadata to the schema of the data warehouse is built. When an analysis request is raised, a customized data mart with data populated from the data warehouse can be automatically generated with the help of this built-in knowledge. This tool, called Enterprise Information Asset Workbench (EIAW), is deployed at the Taikang Life Insurance Company, one of the top five insurance companies of China. User feedback shows that OWL provides an excellent basis for the representation of business semantics in data warehouse, but many necessary extensions are also needed in the real application. The user also deemed this tool very helpful because of its flexibility and speeding up data mart deployment in face of business changes. [ABSTRACT FROM AUTHOR]

An ontology provides a precise specification of the vocabulary used by a community of interest (COI). Multiple communities of interest may describe the same concept using the same or different terms. When such communities interact, ontology alignment and translation is required. This is typically a time consuming process. This paper describes Snoggle, an open source tool designed to ease development of ontology translation rules, and discusses its application to geospatial ontologies. [ABSTRACT FROM AUTHOR]

This paper shows how semantic web techniques can be applied to solving problems of distributed content creation, discovery, linking, aggregation, and reuse in health information portals, both from end-users' and content publishers' viewpoints. As a case study, the national semantic health portal HealthFinland is presented. It provides citizens with intelligent searching and browsing services to reliable and up-to-date health information created by various health organizations in Finland. The system is based on a shared semantic metadata schema, ontologies, and ontology services. The content includes metadata about thousands of web documents such as web pages, articles, reports, campaign information, news, services, and other information related to health. [ABSTRACT FROM AUTHOR]

Semantic Web conferences such as ESWC and ISWC offer prime opportunities to test and showcase semantic technologies. Conference metadata about people, papers and talks is diverse in nature and neither too small to be uninteresting or too big to be unmanageable. Many metadata-related challenges that may arise in the Semantic Web at large are also present here. Metadata must be generated from sources which are often unstructured and hard to process, and may originate from many different players, therefore suitable workflows must be established. Moreover, the generated metadata must use appropriate formats and vocabularies, and be served in a way that is consistent with the principles of linked data. This paper reports on the metadata efforts from ESWC and ISWC, identifies specific issues and barriers encountered during the projects, and discusses how these were approached. Recommendations are made as to how these may be addressed in the future, and we discuss how these solutions may generalize to metadata production for the Semantic Web at large. [ABSTRACT FROM AUTHOR]

Ontologies proliferate with the growth of the Semantic Web. However, most of data on the Web are still stored in relational databases. Therefore, it is important to establish interoperability between relational databases and ontologies for creating a Web of data. An effective way to achieve interoperability is finding mappings between relational database schemas and ontologies. In this paper, we propose a new approach to discovering simple mappings between a relational database schema and an ontology. It exploits simple mappings based on virtual documents, and eliminates incorrect mappings via validating mapping consistency. Additionally, it also constructs a special type of semantic mappings, called contextual mappings, which is useful for practical applications. Experimental results demonstrate that our approach performs well on several data sets from real world domains. [ABSTRACT FROM AUTHOR]

As an increasing number of applications on the web contain some elements of spatial data, there is a need to efficiently integrate Semantic Web technologies and spatial data processing. This paper describes a prototype system for storing spatial data and Semantic Web data together in a SPatially-AUgmented Knowledgebase (SPAUK) without sacrificing query efficiency. The goals are motivated through use several use cases. The prototype's design and architecture are described, and resulting performance improvements are discussed. [ABSTRACT FROM AUTHOR]

This paper introduces a framework to add a semantic web layer to legacy organizational information, and describes its application to the use case provided by the Italian National Research Council (CNR) intraweb. Building on a traditional web-based view of information from different legacy databases, we have performed a semantic porting of data into a knowledge base, dependent on an OWL domain ontology. We have enriched the knowledge base by means of text mining techniques, in order to discover on-topic relations. Several reasoning techniques have been applied, in order to infer relevant implicit relationships. Finally, the ontology and the knowledge base have been deployed on a semantic wiki by means of the WikiFactory tool, which allows users to browse the ontology and the knowledge base, to introduce new relations, to revise wrong assertions in a collaborative way, and to perform semantic queries. In our experiments, we have been able to easily implement several functionalities, such as expert finding, by simply formulating ad-hoc queries from either an ontology editor or the semantic wiki interface. The result is an intelligent and collaborative front end, which allow users to add information, fill gaps, or revise existing information on a semantic basis, while keeping the knowledge base automatically updated. [ABSTRACT FROM AUTHOR]

We describe a novel approach by which software can assess the ability of a confederation of heterogeneous systems to interoperate to achieve a given purpose. The approach uses ontologies and knowledge bases (KBs) to capture the salient characteristics of systems, on the one hand, and of tasks for which these systems will be employed, on the other. Rules are used to represent the conditions under which the capabilities provided by systems can fulfill the capabilities needed to support the roles and interactions that make up each task. An Analyzer component employs these KBs and rules to determine if a given confederation will be adequate, to generate suitable confederations from a collection of available systems, to pre-diagnose potential interoperability problems that might arise, and to suggest system configuration options that will help to make interoperability possible. We have demonstrated the feasibility of this approach using a prototype Analyzer and KBs. [ABSTRACT FROM AUTHOR]