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This paper proposes a cooperative approach for composite ontology mapping. We first present an extended classification of automated ontology matching and propose an automatic composite solution for the matching problem based on cooperation. In our proposal, agents apply individual mapping algorithms and cooperate in order to change their individual results. We assume that the approaches are complementary to each other and their combination produces better results than the individual ones. Next, we compare our model with three state of the art matching systems. The results are promising specially for what concerns precision and recall. Finally, we propose an argumentation formalism as an extension of our initial model. We compare our argumentation model with the matching systems, showing improvements on the results. [ABSTRACT FROM AUTHOR]

Information integration and retrieval are useful tasks in many information systems. In these systems, it is far from an easy task to directly integrate information from natural language (NL) sources, because precisely capturing NL semantics is not a trivial issue in the first place. In this paper, we choose the botanical domain to investigate this issue. While most existing systems in this domain support only keyword-based search, this paper introduces an ontology-based approach to process parallel colour descriptions from botanical documents. Based on a semantic model, it takes advantage of ontologies so as to represent the semantics of colour descriptions precisely, to integrate parallel descriptions according to their semantic distances, and to answer colour-related species identification queries. To evaluate this approach, we implement a colour reasoner based on the FaCT-DG Description Logic reasoner, and present some results of our experiments on integrating parallel descriptions and species identification queries. From this highly specialised domain, we learn a set of more general methodological rules. [ABSTRACT FROM AUTHOR]

Many organizations nowadays face the problem of accessing existing data sources by means of flexible mechanisms that are both powerful and efficient. Ontologies are widely considered as a suitable formal tool for sophisticated data access. The ontology expresses the domain of interest of the information system at a high level of abstraction, and the relationship between data at the sources and instances of concepts and roles in the ontology is expressed by means of mappings. In this paper we present a solution to the problem of designing effective systems for ontology-based data access. Our solution is based on three main ingredients. First, we present a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances. The second ingredient is a novel mapping language that is able to deal with the so-called impedance mismatch problem, i.e., the problem arising from the difference between the basic elements managed by the sources, namely data, and the elements managed by the ontology, namely objects. The third ingredient is the query answering method, that combines reasoning at the level of the ontology with specific mechanisms for both taking into account the mappings and efficiently accessing the data at the sources. [ABSTRACT FROM AUTHOR]

The goal of this paper is to identify various aspects of context-awareness needed to facilitate semantics integration of data, and to discuss how this knowledge may be represented within ontologies. We first present a taxonomy of ontologies and we show how various kinds of ontologies may cooperate. Then, we compare ontologies and conceptual models. We claim that their main difference is the consensual nature of ontologies when conceptual models are specifically designed for one particular target system. Reaching consensus, in turn, needs specific models of which context dependency has been represented and minimized. We identify five principles for making ontologies less contextual than models and suitable for data integration and we show, as an example, how these principles have been implemented in the PLIB ontology model developed for industrial data integration. Finally, we suggest a road map for switching from conventional databases to ontology-based databases without waiting until standard ontologies are available in every domains. [ABSTRACT FROM AUTHOR]

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires to the sharing scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since a few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government communityby analyzing motivations, requirements and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by showing how integration and interoperability emerge from this model through a cooperative and multi-viewpoint methodology. Finally, we illustrate added values and lessons learned by two compelling case studies: a change of circumstances notification system and a GIS-based emergency planning system, and describe key challenges which remain to be addressed. [ABSTRACT FROM AUTHOR]

The ability to deal with inconsistencies and to evaluate the impact of possible solutions for resolving inconsistencies are of the utmost importance in real world ontology applications. The common approaches either identify the minimally unsatisfiable sub-ontologies or the maximally satisfiable sub-ontologies. However there is little work which addresses the issue of rewriting the ontology; it is not clear which axioms or which parts of axioms should be repaired, nor how to repair those axioms. In this paper, we address these limitations by proposing an approach to resolving unsatisfiable ontologies which is fine-grained in the sense that it allows parts of axioms to be changed. We revise the axiom tracing technique first proposed by Baader and Hollunder, so as to track which parts of the problematic axioms cause the unsatisfiability. Moreover, we have developed a tool to support the ontology user in rewriting problematic axioms. In order to minimise the impact of changes and prevent unintended entailment loss, both harmful and helpful changes are identified and reported to the user. Finally we present an evaluation of our interactive debugging tool and demonstrate its applicability in practice. [ABSTRACT FROM AUTHOR]

We explore flexible querying of RDF data, with the aim of making it possible to return data satisfying query conditions with varying degrees of exactness, and also to rank the results of a query depending on how "closely" they satisfy the query conditions. We make queries more flexible by logical relaxation of their conditions based on RDFS entailment and RDFS ontologies. We develop a notion of ranking of query answers, and present a query processing algorithm for incrementally computing the relaxed answer of a query. Our approach has application in scenarios where there is a lack of understanding of the ontology underlying the data, or where the data objects have heterogeneous sets of properties or irregular structures. [ABSTRACT FROM AUTHOR]

In this paper we propose an asymmetric semantic similarity among instances within an ontology. We aim to define a measurement of semantic similarity that exploit as much as possible the knowledge stored in the ontology taking into account different hints hidden in the ontology definition. The proposed similarity measurement considers different existing similarities, which we have combined and extended. Moreover, the similarity assessment is explicitly parameterised according to the criteria induced by the context. The parameterisation aims to assist the user in the decision making pertaining to similarity evaluation, as the criteria can be refined according to user needs. Experiments and an evaluation of the similarity assessment are presented showing the efficiency of the method. [ABSTRACT FROM AUTHOR]

The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conversion, but would also be an aid in solving related problems such as information extraction and semi-structured data management. In this paper, we offer a conceptual modeling solution for the common special case in which so-called sibling pages are available. The sibling pages we consider are pages on the hidden web, commonly generated from underlying databases. We compare them to identify and connect nonvarying components (category labels) and varying components (data values). We tested our solution using more than 2,000 tables in source pages from three different domains—car advertisements, molecular biology, and geopolitical information. Experimental results show that the system can successfully identify sibling tables, generate structure patterns, interpret tables using the generated patterns, and automatically adjust the structure patterns, if necessary, as it processes a sequence of hidden-web pages. For these activities, the system was able to achieve an overall F-measure of 94.5%. [ABSTRACT FROM AUTHOR]

We deal with the problem of automated analysis of web service protocol compatibility and replaceability in presence of timing abstractions. We first present a timed protocol model for services and identify different levels of compatibility and replaceability that are useful to support service development and evolution. Next, we present operators that can perform such analysis. Finally, we present operators properties by showing that timed protocols form a new class of timed automata, and we briefly present our implementation. [ABSTRACT FROM AUTHOR]

As the Web continues to grow and evolve, more and more information is being placed in structurally rich documents, XML documents in particular, so as to improve the efficiency of similarity clustering, information retrieval and data management applications. Various algorithms for comparing hierarchically structured data, e.g., XML documents, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being modeled as ordered labeled trees. Nevertheless, a thorough investigation of current approaches led us to identify several structural similarity aspects, i.e. sub-tree related similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an improved comparison method to deal with fine-grained sub-trees and leaf node repetitions, without increasing overall complexity with respect to current XML comparison methods. Our approach consists of two main algorithms for discovering the structural commonality between sub-trees and computing tree-based edit operations costs. A prototype has been developed to evaluate the optimality and performance of our method. Experimental results, on both real and synthetic XML data, demonstrate better performance with respect to alternative XML comparison methods. [ABSTRACT FROM AUTHOR]

Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations. [ABSTRACT FROM AUTHOR]

Processing a twig pattern query in XML document includes structural search and content search. Most existing algorithms only focus on structural search. They treat content nodes the same as element nodes during query processing with structural joins. Due to the high variety of contents, to mix content search and structural search suffers from management problem of contents and low performance. Another disadvantage is to find the actual values asked by a query, they have to rely on the original document. In this paper, we propose a novel algorithm ValueExtractionwithRelationalTable (VERT) to overcome these limitations. The main technique of VERT is introducing relational tables to store document contents instead of treating them as nodes and labeling them. Tables in our algorithm are created based on semantic information of documents. As more semantics is captured, we can further optimize tables and queries to significantly enhance efficiency. Last, we show by experiments that besides solving different content problems, VERT also has superiority in performance of twig pattern query processing compared with existing algorithms. [ABSTRACT FROM AUTHOR]

One of the challenges of the Semantic Web is to integrate the huge amount of information already available on the standard Web, usually stored in relational databases. In this paper, we propose a formalization of a logic model of relational databases, and a transformation of that model into OWL, a Semantic Web language. This transformation is implemented in Cross, as an open-source prototype. We prove a relation between the notion of legal database state and the consistency of the corresponding OWL knowledge base. We then show how that transformation can prove useful to enhance databases, and integrate them in the Semantic Web. [ABSTRACT FROM AUTHOR]

Current graphical notations for XML Schema do not raise the level of abstraction for XML schemata in the same way traditional conceptual models raise the level of abstraction for data schemata. Traditional conceptual models, on the other hand, do not accommodate several XML Schema structures. Thus, there is a need to enrich traditional conceptual models with new XML Schema features. After establishing criteria for XML conceptual modeling, we propose an enrichment to represent the XML features missing in traditional models. We argue that our solution can be adapted generally for traditional conceptual models and show how it can be adapted for two popular conceptual models. [ABSTRACT FROM AUTHOR]

A continuous evolution of business process parameters, constraints and needs, hardly foreseeable initially, requires from the business process management systems a continuous design and a reliable process model. In this paper, we are interested in developing a reactive design through a process log analysis ensuring process re-engineering and execution reliability. We propose to analyse workflow logs to discover workflow transactional behavior and to improve and correct related recovery mechanisms subsequently. Our approach starts by collecting workflow logs. Then, we build, by statistical analysis techniques, an intermediate representation specifying elementary dependencies between activities. These dependencies are refined to mine the transactional workflow model. The analysis of the discrepancies between the discovered model and the initially designed model enables us to detect design gaps, concerning particularly the recovery mechanisms. Thus, based on this mining step, we apply a set of rules on the initially designed workflow to improve workflow reliability. [ABSTRACT FROM AUTHOR]

Neglecting traceability—i.e., the ability to describe and follow the life of a requirement—is known to entail misunderstanding and miscommunication, leading to the engineering of poor quality systems. Following the simple principles that (a) changes to UML model instances ought be justified to the stakeholders, (b) justification should proceed in a structured manner to ensure rigor in discussions, critique, and revisions of model instances, and (c) the concept of argument instantiated in a justification process ought to be well defined and understood, the present paper introduces the UML Traceability through Argumentation Method (UML-TAM) to enable the traceability of design rationale in UML while allowing the appropriateness of model changes to be checked by analysis of the structure of the arguments provided to justify such changes. [ABSTRACT FROM AUTHOR]

Enterprise integration refers to solutions that facilitate meaningful interactions among heterogeneous legacy applications. The scale, complexity and specificity of most enterprise integration efforts mean that design knowledge for enterprise integration has resisted codification. Important exceptions to this include: use of Business Process Models (BPM) to understand integration requirements; and Enterprise Integration Patterns (EIP), which present designers with abstract descriptions of recurring design tactics for integrating applications. The two, however, can be at odds. BPM encourages the control flow perspective; whereas EIP codifies an operational perspective. Mapping between the two to develop coherent solutions, therefore, tends to be problematic. To bridge the gap, we suggest an approach that builds on the theory of speech acts. We develop essential components of such an approach, including a re-representation of EIP as structures of speech acts, a characterization of tasks in BPM with action types, and a mapping between speech acts and action types. These components are accompanied by inference rules that produce a mapping between sets of tasks in a business process and structures of speech acts to allow reasoning on identification of appropriate EIPs for given set of tasks. We demonstrate usefulness of the proposed approach by application to industry cases. [ABSTRACT FROM AUTHOR]

Modeling is an important and time consuming part of the Business Process Management life-cycle. An analyst reviews existing documentation and queries relevant domain experts to construct both mental and concrete models of the domain. To aid this exercise, we propose the Rapid Business Process Discovery (R-BPD) framework and prototype tool that can query heterogeneous information resources (e.g. corporate documentation, web-content, code e.t.c.) and rapidly construct proto-models to be incrementally adjusted to correctness by an analyst. This constitutes a departure from building and constructing models toward just editing them. We believe this rapid mixed-initiative modeling will increase analyst productivity by significant orders of magnitude over traditional approaches. Furthermore, the possibility of using the approach in distributed and real-time settings seems appealing and may help in significantly improving the quality of the models being developed w.r.t. being consistent, complete, and concise. [ABSTRACT FROM AUTHOR]

This paper discusses extending the Unified Modelling Language by means of a profile for modelling knowledge-based system in the context of Model Driven Architecture (MDA) framework. The profile is implemented using the eXecutable Modelling Framework (XMF) Mosaic tool. A case study from the health care domain demonstrates the practical use of this profile; with the prototype implemented in Java Expert System Shell (Jess). The paper also discusses the possible mapping of the profile elements to the platform specific model (PSM) of Jess and provides some discussion on the Production Rule Representation (PRR) standardisation work. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for conceptual modeling which is based on a new modeling primitive, the niche, and associated constructs granularity and reconciliation. A niche is an environment where entities interact for a specific purpose, playing specific roles, and according to the norms and constraints of that environment. Granularity refers to the relative level of power or influence of an entity within a niche. Reconciliation is a relationship from N entities onto one reconciled entity, and represents explicitly a situation where two or more different perspectives of the same entity have been reconciled, by negotiation, into a single consensus view. The methodology we propose provides a systematic method of designing conceptual models along with a process for normalising inappropriate relationships. Normalising is a prescriptive process for identifying and remedying inconsistencies within a model based on granularities. Drawing on a number of case studies, we show how niches and granularity make complexity easier to manage, highlight inaccuracies in a model, identify opportunities for achieving project goals, and reduce semantic heterogeneity. [ABSTRACT FROM AUTHOR]

Engineering has a long tradition in analyzing the safety of mechanical, electrical and electronic systems. Important methods like HazOp and FMEA have also been adopted by the software engineering community. The misuse case method, on the other hand, has been developed by the software community as an alternative to FMEA and preliminary HazOp for software development. To compare the two methods misuse case and FMEA we have run a small experiment involving 42 third year software engineering students. In the experiment, the students should identify and analyze failure modes from one of the use cases for a commercial electronic patient journals system. The results of the experiment show that on the average, the group that used misuse cases identified and analyzed more user related failure modes than the persons using FMEA. In addition, the persons who used the misuse cases scored better on perceived ease of use and intention to use. [ABSTRACT FROM AUTHOR]

We investigate the computational complexity of reasoning over various fragments of the Extended Entity-Relationship (EER) language, which includes a number of constructs: isa between entities and relationships, disjointness and covering of entities and relationships, cardinality constraints for entities in relationships and their refinements as well as multiplicity constraints for attributes. We extend the known ExpTime-completeness result for UML class diagrams [5] and show that reasoning over EER diagrams with isa between relationships is ExpTime-complete even without relationship covering. Surprisingly, reasoning becomes NP-complete when we drop isa between relationships (while still allowing all types of constraints on entities). If we further omit disjointness and covering over entities, reasoning becomes polynomial. Our lower complexity bound results are proved by direct reductions, while the upper bounds follow from the correspondences with expressive variants of the description logic DL-Lite, which we establish in this paper. These correspondences also show the usefulness of DL-Lite as a language for reasoning over conceptual models and ontologies. [ABSTRACT FROM AUTHOR]

We consider the problem of adding both equality and order generating dependencies to Web ontology languages such as OWL DL that are based on description logics. Such dependencies underlie a number of problems that relate, for example, to web service composition, to document ordering, and to lower level algorithmic issues in service plan generation and evaluation. [ABSTRACT FROM AUTHOR]

Business modelling research is increasingly interested in exploring how domain ontologies can be used as reference models for business models. The Resource Event Agent (REA) ontology is a primary candidate for ontology-driven modelling of business processes because the REA point of view on business reality is close to the conceptual modelling perspective on business models. In this paper Ontology Engineering principles are employed to reengineer REA in order to make it more suitable for ontology-driven business modelling. The new conceptual representation of REA that we propose uses a single representation formalism, includes a more complete domain axiomatizat-ion (containing definitions of concepts, concept relations and ontological axioms), and is proposed as a generic model that can be instantiated to create valid business models. The effects of these proposed improvements on REA-driven business modelling are demonstrated using a business modelling example. [ABSTRACT FROM AUTHOR]

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]