The meaning of a conceptual model is derived from the linguistic semantics of the modeling language used, the intension of the modeling concepts employed, and an explicit specification of these concepts that is understood within a community of practice. The triptych paradigm of conceptual modeling reflects these three dimensions of meaning as represented in the triptych wings of ‘Language Wing’, ‘Model Wing’, and ‘Meaning Wing’. In this paper, we investigate how the specification, that is, the ‘grounding’ of the modeling concepts, can be achieved based on these triptych wings. Our considerations should help the development of information systems to avoid costly future system changes that could occur due to the lack of a comprehensive understanding of an application and its inherent semantics during modeling. When developing a system, specifying the concepts used for modeling as precisely as possible increases the likelihood that the resulting information system will meet the application requirements.

Every discipline – and even more so a new one – needs a practical and expressive theory. With the science and practice of modelling, we are devoting ourselves to such a lore and teachings of MMM. Here MMM is an acronym that stands for the three components of a theory and practice of model-based science: M(odels)–(to )M(odel and use)–M(odelling). With the third component, we focus on the systematic, well-thought-out and well-founded way of working with models and model activities that can be understood as the Grand Theory of Models. MMM is combined with a corresponding scientific and practical discipline that we call modelology. Everything can potentially assimilate model-hood, but some things can only be models to a very limited extent, if at all. There are also non-models, pre-pre-models, pre-models, proto-models, or even un-models. Being a model can be characterised as a sophisticated judgement based on the capability and validity of models, the potency of models, the embedding in the background and the application, as well as the journey of a model over time for changing communities of practice. This reliability judgement leads to a conceptual model of model-hood itself.

Every object and every idea can be used as a model in an application scenario, if it becomes useful in the scenario as an instrument in a function. Through this use and function, an object or idea becomes a model, at least for a certain or long time for the respective model user in its context and environment. Models are works of art of thinking. They come in the most diverse forms: small ingenious, ever-present, medium-sized or even elaborate ones of imposing size and full of hidden secrets. Quiet ones, animated by a flash of inspiration. Groundbreaking and revolutionary. Methodically overwhelmingly sophisticated ones that stand on the shoulders of giants. Simple ones that are so well put together that everyone likes them and understands them and cannot refuse them. Modelology is a novel discipline that handles model development and usage in a systematic and well-founded way. We introduce the central kernels of this new science, art, and culture.

Computers were originally developed for executing complex calculations fast and effectively. The intelligence of computer was based on arithmetic capabilities. This has been the mainstream in the development of computers until now. In the middle of 1950s a new application area, Artificial Intelligence (AI), was introduced by researchers. They had interest to use computers to solve problems in the way intelligent beings do. The architecture, which supported calculations, were conquered to perform tasks associated with intelligence beings, to execute inference operations and to simulate human sense. Artificial intelligence has had several reincarnation cycles; it has reappeared in different manifestations since this research area became interesting for the researchers. All the time a lot of discussion about intelligence of these systems has been going on – are the AI based systems and robots intelligent, what is the difference of human and machine intelligence, etc. Abilities related to intelligence cover ability to acquire and apply knowledge and skills, as well as ability to learn. AI provides different manifestations to the term “intelligence”: the human intelligence is a wide variety of different types of intelligence, as well as the meaning of artificial intelligence has varied over time. In our paper we will look to this term, especially to provide means for comparing human and artificial intelligence and have a look to the learning capability related to it.

Models are used everywhere, in daily life, sciences, engineering, and thoughts. They represent, support, and enable our thinking, acting, reflecting, communication, and understanding. They are universal instruments. Reasoning through and by models is, however, different from those that we use in ‘exact’ sciences and is far less understood. The notion of model is becoming nowadays well-accepted. Reasoning through models is far less understood and a long lacuna. This keynote aims at closing this gap.

Data (conceptual, data, information, knowledge) modelling is still the work of an artisan, i.e. an art in the best case, made by humans, because of the need for human intelligence. Data modelling is an essential part of Information System (IS) design, specifying how data is implemented as part of an IS. The principles of data modelling follow the evolution of IS development paradigms, and these in turn follow the progress of technological changes in computing. Although technology has changed a lot during the decades of commercial use of computers – since the early 1950s to now, close to 70 years – data modelling is still based on the same basic principles as decades ago. Or is it really so? Finding the answer to this question was the main motivation to start writing this paper. Since the future is more interesting than the past, we set our research problem to be “What are the challenges for data modelling in the future?”. The reason for this is that we see some significant changes in the future in the data modelling sector which we wanted to examine. However, the future is a continuum of the past. The future cannot be fully understood without understanding the past. Humans also tend to forget the details of the past. Even the most remarkable innovations from the past have become part of the new normal. Consequently, at the beginning of our paper we look shortly at the progress of data modelling during the era of commercial computing. Our focus is on the recent past and we look at the technological changes that have been of key importance in data modelling in the role of triggers and enablers. To find the answer to our research question, we retrieved some recent studies handling the future of data modelling and analyse the challenges found in these sources. The paper is concluded by some future paradigms. In general, the big changes seem to be the growing importance of Artificial Intelligence (AI) and machine learning (ML) as its fuel. AI not only conducts algorithmic rule-based routines, it has learning capability, which makes it more intelligent and adaptable, and able to compete with human intelligence, even in data management tasks.

This paper deals with the comparison and management of (heterogeneous) temporal datings in pre- and protohistory. It will present a first draft of a conceptual model for the description of the most common types of scales used in this context. The aim is to enable a system to compare objects according to their dating, regardless of the used method and scale. Thus temporally relevant objects can be selected by a query and do not need to be selected manually by an expert. Especially for larger data sets, automated computations, integrity checks, temporal reasoning or pattern mining this is beneficial.

This paper presents a comparison of prediction methods for a water quality index (WQI) that is used for classification of water quality in rivers or canals. In this work, we consider the water quality index of two canals namely Phadung Krung Kasem Canal and Saen Saep Canal, Bangkok, Thailand as a case study. We compare results from M5P, M5Rules, REPTree with results from multilayer perceptron. The models employ five input variables including dissolved oxygen (DO), biological oxygen demand (BOD), ammonia nitrogen (NH3-N), Fecal Coliform bacteria (FCB) and Total Coliform bacteria (TCB) which were measured in the canals. The data in this research had been collected from Bangkok Metropolitan Authority, Thailand from 1 January 2007 to 31 November 2017. The total number of data is 2,000 records. The 10-fold cross validation method is used for evaluation of prediction models. It allows to determine the most effective method. Our experimental results show that the REPTree method yielded the highest accuracy to predict water quality index compared to other methods proposed in this paper.

Peer reviewed

Humankind faces a most crucial mission; we must endeavour, on a global scale, to restore and improve our natural and social environments. This is a big challenge for global information systems development and for their modelling. In this paper, we discuss on different aspects of conceptual modelling in global environmental context. The paper is the summary of the panel session “The Future of Conceptual Modelling” in the 29th International Conference on Information Modelling and Knowledge Bases.

When viewing the world each of us has a unique perception of his/her surrounding. The way and mode we use to notice important and interesting details is heavily influenced by things like our education, our academic discipline, or our personal interests. The cognitive patterns we prefer, our (working) habits, and in general our focus are often affected by our way to perceive the world. In contexts like multidisciplinary research projects, companies with various diverse departments, or so to say in contexts where many modes of perception and thus many different interest foci shall collaborate, this can be challenging. Different groups need different information to perform their working tasks. Different (data) structures, formats, and namespaces are requested. Even when examining the exact same object different experts will have different perspectives. In this paper we will approach this situation from a data managers point of view. In general these perspectives are no indicator for deficiencies. The different perspectives just mirror the differing tasks and purposes which are addressed. Mostly the existing structures and forms of information (re)presentation are reasonable and adapted to the needs of the people following the perspective. Nevertheless the amount of perspectives is possibly numerous, as potentially each task requires a slightly different way of structuring the available information. Thus it is in the general case infeasible to maintain all possible perspectives as physical data structures. We therefore suggest to systematically describe perspectives and use the information from these models to generate appropriate interfaces on demand.

Peer reviewed

Modelling is an essential part of information systems development. Models are used for communication between interest groups and inside development teams. Models are also used for transferring baseline artefacts between development phases. Models are mainly developed by humans, which represent certain cultures - national, enterprise, professional, team, project etc. Because of that we claim that models, as well as many other information systems related artefacts are culture dependent. The models are born in certain context and these must be also interpreted by taking the original context into account. In our earlier studies we have analysed the effect of culture in information systems development: culture related aspects in general level, in information search and interaction and in web information systems. We focus now on modelling. Because of that we shortly answer to the question “How cultures differ from each other”. This reviews and synthesis generally accepted frameworks for cultural analysis. In addition we shortly open the results of our earlier studies. Because modelling is a human activity, as well as information systems are used by humans, we integrate the use context into information systems development. The findings of culture analysis are transferred to modelling practices via our framework that defines model as an instrument transferring elements of its development context to the models – we discuss the roles of normal models, deep models and modelling matrix. Finally we will concentrate on the problems of cross-cultural modelling using selected national cultures as an example.

Collaboration is a crucial part of joint research. Especially in projects, where multiple academic domains and disciplines are involved, this is challenging. Different research foci and individual perspectives are often mismatching. Heterogeneous data, diverging working habits, and differing standards are common. Research itself is agile, dynamic, and evolving. Changes and revisions of data structures, requirements, and actual data values arise continuously. And so on…

The performance of modern information systems in the hydrosphere is based on the robustness of the wireless underwater communication between the cooperative subsystems. It is strongly intertwined with the coordination reliability for sharing resources and common purposes. Secure underwater coordination is a key functionality (C4I-STAR). The physical laws of the nature restrict the band-width and reliability of underwater communication links, the quality differs from deep to shallow water areas, with the hydro acoustical parameters, like the sound speed and sediment profile, with the weather conditions and day time. To over-come low data rates and non robust transmission links of submerged manned and unmanned platforms, error tolerant processes are needed to fulfill different hand-over maneuvers in the submerged teams. But, what are efficient process chains in this field? S-BPM has advantages to support users and scientists to handle this layer modeling for a standard network code of conduct.

Website design is often performed either by technology-biased people or by artisans and thus results either in a domination of technological solutions or fancy artistic solutions. Observing however which websites evolve successfully over a dozen of years we realise that these are those that properly match their layout and playout to the expectations and especially the cultures of their users. A website may be characterised by six dimensions: presentation, content, functionality, stories to be played, context and user intentions and needs. The last two dimensions heavily depend on the culture of the website customer. Culture studies developed models on passivity resp. multi-tasking or on general pattern of thinking or feeling or acting of users. In this paper we study the desiderata of low and high context of culture for website design and compare them to the Lewis and Hofstede model.

The importance of information in our daily life is increasing rapidly. Simultaneously the availability of information from different sources has grown exponentially. The progress in data oriented context has grown from traditional approach based on queries to databases to the beneficial use of wide variety of openly available, quite often also non-structured data sources. The complexity of data needs has also increased and solutions are based on combined multi-query results. The development has also taken us towards global context, in which data is used over geographical and cultural borders. Information search is a communication oriented task, in which the cultures of users and meet the culture related aspects of data repositories. A mismatch between the users' national culture based expectations to the behavior of global information services (information system and their user interfaces) is the source of a variety of problems. In our paper we analyse the characteristics of information search and the cultural aspects guiding the behavior of the users of information systems. These two approaches are merged in the form of query-answer profiles. The purpose of the paper is to find guidelines possible to generalize and apply by the developers and users for survival in global information system context.

Provenance tackles problems as: provides information to a user about his data that are given to him or passed by him; informs a user in which way a foreign user has used his data; allows rollback mechanisms on wrong data; observes the currentness of data for closed contracts and creates a history of data for a user. We show that with a sophisticated metadata support these problems can be solved.

Globalisation has a strong impact on information systems both from a development and usage point of view. Development is done by geographically distributed teams, with team members representing different cultures. In addition, the information systems are targeted at widening markets to get new clients and business - either as they are or as localized variations. In the case of traditional information systems, the needs related to globalisation are more or less manageable, because the clients are at least to some extent known, as well as their needs and preferences. Cloud technology and cloud-based solutions are replacing traditional information systems at an accelerating speed. In some cases, the question is only one change to an execution platform, but more often also opening up the information system usage to a “faceless” mass of users over the Internet – the information system (IS) becomes an SaaS-based WIS (Web Information System). In addition to SaaS-based solutions, the WIS category covers a wide variety of web services available in a more or less open manner; as a consequence the ability to react to the needs of a multi-cultural set of users causes new challenges to the developers and service implementation. Our paper initiates discussion on the challenges related to a WIS in a multi-cultural context. The complexity is structured by recognition of six concerns (viewpoints), which are handled in an interrelated manner. The foundation is built by analysis of cultural differences, which are used to clarify and explain the culture-based differences in information system structure and usage. Culture-related aspects of storyboards and database schemas are dealt with and evidence is derived from selected existing information systems.

Private data should often not distributed to other users than those that got an access on common consent and settled trust. Nobody and no company else should have an access to such data. Protection of privacy becomes more difficult in mobile environments and thus requires novel approaches to privacy enhancing technologies. The Privacy Wallet is a mobile application that supports exchange of data on consent and protects from unauthorised access and distribution. The owner of the data is the master of that data. The holder has only access on common consent.

Database research and practice has brought up a large body of knowledge and experience. This experience and knowledge is based on solutions for database structures that occur and reoccur in many applications in a similar form. We may distinguish two classes of such solutions: reference models that can be used as a blueprint for a fully fledged schema and stereotypes that are general solutions.

The paper develops an approach to information system adaptation supporting diversity and heterogeneity of users. The user perspective is handled from culture point of view. Cultures are layered and this structure can be used for starting with national cultures and deriving stereotypes. Culture is recognised as a multidimensional structure, in which national culture provides a basement for the behavioural variations of individuals in personal level. For information system development this layering covers three different perspectives: cultural stereotypes and user models, organisational models and technology models. We thus may develop a coherent information system perspective that supports adaptivity in multicultural information system applications.

Data quality becomes an important issue for scientific databases. It is currently managed insufficiently. General solutions for managing the quality data on the object level are represented insufficiently nowadays. These applications need, however, a management system that supports quality treatment over the entire lifespan. We develop an approach to quality management that can be integrated into a metadata management system. This approach is based on a separation of concern through database components, extended views and Information Containers.

Damage caused by natural hazards is increasing all over the world. All countries intensify their efforts to predict and prevent hazard events and to decrease disaster impact. Disaster management is one of the challenging, complex and critical application areas dealing with hyper dynamic situation changes, high velocity, voluminous data and organizational heterogeneity. Successful management of disaster response requires flexible and adaptable solution techniques including very accurate, fast and dynamic activity guidance for supporting of process coordination, decision making and information logistics in real-time.

Conceptual modelling has been changed over years. Nowadays conceptual modelling in the small has become state of the art for specialists and educated application engineers. Conceptualisations have been developed for almost any aspect of an information system (structuring, functionality, interactivity, distribution, architectural components), for most of the implementation decisions such as tuning or performance improvement, for many facets or viewpoints on the application domain etc. The area of conceptual modelling became a science for typical small-range applications with small schemata. Large schemata typically grow incrementally or are a result of migration or integration of schemata or are obtained after consolidation of applications. Typical industrial applications such as SAP R/3 use thousands or tens of thousands database types and have schemata that are not easy to handle, to maintain, to evolve or to map to logical or physical languages at the implementation level. Conceptualisation in the large is typically performed by many modelers and teams. It also includes architectural aspects within applications. At the same time quality, configuration and versioning of models developed so far become an issue.

Conceptional modelling is one of the central activities in Computer Science. Conceptual models are mainly used as intermediate artifact for system construction. The notion of the conceptual model is at present rather informal. Conceptional modelling is performed by a modeller who directs the process based on his/her experience, education, understanding, intention, and attitude.

Specification of collaboration has neglected over a long period although collaboration is one of main conceptions in computer science and computer engineering. We distinguish between collaborations among systems and socio-technical collaboration. Database research has succeeded in developing approaches for collaboration among database systems that incorporate conceptual specification and allow to reason on systems at a far higher abstraction level. Conceptual modelling of socio-technical collaborating systems is however an open research issue. With the advent of web information systems systems became naturally socio-technical and collaborating. Therefore, we need a techniques for conceptual description of collaboration. Collaboration modelling may be based on models for communication, models for coordination, and models for cooperation. In socio-technical systems users work within their local environment and collaborate within the global world. Therefore, users inject their culture and their specific behaviour into collaboration. Users use information, communication, cooperation and coordination services. These services must be highly flexible and adaptable to the needs of users, to the circumstances and contexts of these users, and to the technical infrastructures used.

Workflow management systems provide support for structured processes and help to follow the defined business process. Although their importance has been proved by various applications over the last decades they are not appropriate for all use cases. Such workflow management systems are only applicable for domains where the process is well structured and static. In various domains it is essential that the workflow is adapted to the current situation. In this case the traditional workflow systems are not applicable. A flexible approach is required.

Conceptual modeling is fundamental within information system engineering. However, it is still difficult to share models, to find reference models or to reuse suitable existing models. Motivated by the Open Model Initiative this paper presents a Meta Modeling Framework for the description of reference models in order to support both common use of existing models and development of new models. This work targeted to specify significant categories and attributes that allow representing knowledge about reference models with an appropriate abstraction level and granularity. The methodological approach and the framework are presented and design decisions are discussed. The usage of the framework is exemplarily sketched.

Database querying is still based on programming languages. The user must learn the database programming language and the corresponding database schemata before asking a data question to the system. Programming languages use either the classical textual style or some kind of visualisation for queries (e.g., query-by-example or VisualSQL). Conceptual queries are first to be specified at the conceptual level, using concepts and languages easily understood by the application domain experts who must be qualified to validate the query.

Exceptions are considered to be unusual states that can but must not be taken primarily into account. They form exclusions, represent cases to which a rule does not apply, form specific states that are not going to be handled at least by the current system, or might represent legal objections against the typical state. Exceptions are currently considered to be a sign of poor culture, wrong implementation, bugs in the code, bad understanding of the application domain area, wrong deployment of technology, or poor education of people. This understanding is completely different from the understanding and treatment of exceptions in real life.

This paper includes five contributions on the topic of multimedia information systems for social, cross-cultural and environmental computing. Approaches, models, and methods for Web Semantization, Cross-cultural Image Computing, Information Modelling and Data Mining, Mobile Information Systems for Ubiquitous Society, and Multimedia Systems for Cross-cultural and Environmental Computing are introduced and discussed. This paper is based on the contributions presented in the panel discussion of EJC 2012 Conference.

Data analysis based on spatial and temporal relationships leads to new knowledge discovery in multi-database environments. As various and almost infinite relationships are potentially existing among heterogeneous databases, it is important to realize an objective-based dynamic data analysis environment with appropriate data collection from selected databases.

Designing a tool for data extraction from semi-structured and unstructured text, we are confronted with a problem that has largely been neglected by scholars so far: What if we need to find matches for several different patterns in a document and there are no keywords to support the search? And if so, what if the same section matches several different patterns or if matches in part overlap? How can we decide which one to pick? We suggest that this is an important problem in data extraction and propose a solution based on a token classification system and weighted finite-state automata.

Knowledge management has been a hot research issues for decades and resulted in many proposals and some systems that have been supporting information exchange in companies or societies. They failed however to become knowledge systems. With the advent of the internet the knowledge web is going to replace knowledge management. It creates its own challenges but take advantage of all web, information systems and software technology.

Conceptual modelling is one of the central activities in Computer Science. Conceptual models are mainly used as intermediate artifact for system construction. They are schematic descriptions of a system, a theory, or a phenomenon of an origin thus forming a model. A conceptual model is a model enhanced by concepts. The process of conceptual modelling is ruled by the purpose of modelling and the models. It is based on a number of modelling acts, on a number of correctness conditions, on modelling principles and postulates, and on paradigms of the background or substance theories. Purposes determine the (surplus) value of a model. Conceptual modelling is performed by a modeller that directs the process based on his/her experience, education, understanding, intention and attitude.

Classical software development methodologies take architectural issues as granted or pre-determined. They thus neglect the impact decisions for architecture have within the development process. This omission is applicable as long as we are considering monolithic systems. It cannot however been kept whenever we move to distributed systems. Web information systems pay far more attention to users support and thus require sophisticated layout and playout systems. These systems go beyond what has been known for presentation systems.

NULL is a special marker used in SQL to indicate that a value for an attribute of an object does not exist in the database. Its aim is a representation of “missing information and inapplicable information”. Although NULL is called null ‘value’ is not at all a value. It is a marker. It is only an annotation of incomplete data. Since it is typically interpreted as a value, NULL has led to controversies and and debates because of its treatment by 3-valued logics, of its special requirements for its use in SQL joins, and the special handling required by aggregate functions and SQL grouping operators.

Fast databases are no longer nice-to-have – they are a necessity. Many modern applications are becoming performance critical. At the same time, the size of some databases has been increasing to levels that cannot be well supported by current technology. Performance engineering is now becoming a buzzword for database systems. At first physical and partially logical tuning methods have been used for support of high performance systems, but they are mainly based on large and not well understood performance and tuning parameters. Nowadays it becomes obvious that we need methods for systematic performance design.

The internet and web applications have changed business and human life. Nowadays everybody is used to obtain data through the internet. Most applications are still Web 1.0 applications. Web 2.0 community collaboration and annotated data on the basis of Web 3.0 technologies supports new businesses and applications. The quality dimension of the web is however one of the main challenges. Knowledge systems target at high-quality data on safe grounds, with a good reference to established science and technology and with data adaptation to user's needs and demands. Knowledge system can be build based on existing and novel technologies. This paper discusses the challenges, two solutions and the fundamentals of knowledge system environments.

Database modelling is classically defining the database dictionary, database structuring and functionality within one singleton paradigm. This approach has led to sophisticated financial services, to enterprise information systems and other database-backed practical solution which are easy to handle, relatively simple to change and to implement and which satisfied the needs of business in the 90ies. At the same time a number of applications have been developed that used the potential within the data for analysis, for exchange and collaboration of systems, e.g. OLTP-OLAP systems, decision support systems, scientific information systems, collaborative information systems and web information systems. These applications do not use a singleton language for data storage, data computation and data delivery. Their languages use different paradigms. We therefore need a way for specification of database applications that provide facilities for appropriate modelling depending on the needs.

In order to increase the expressiveness of XML query languages we define an XML object model that provides a rich description of XML data using the notions of class schema and class tuple. Based on this model we develop a novel query language, the XML Identity Query Language (XIQL) based on identifier generation and fixed-point computation. However, XIQL cannot deal with finite tree duplicates in an XML object graph. To solve this problem we extend XIQL by integrating termsdenoting hereditarily finite sets. With respect to determinate transformations the extended XIQL+is still incomplete, but becomes complete with respect to a modified completeness criterion for XML database transformations, which aims at capturing more non-determinism.

The current transition from Web 1.0 to Web 2.0 is not so much a change of the world wide web itself, but a change of usage. While Web 1.0 is mainly provider-driven, Web 2.0 is user-driven and content-centred. This also implies a fast change of content turning the web from a rather static medium into an active communication medium. Furthermore, the web is subject to even more changes emphasising content, commerce, community and context, personalization, and vertical search, which is branded as the next generation Web 3.0.In this situation the design of Web Information Systems (WISs) requires adaptations to the new developments, if not completely new methods. The tutorial wants to show that the co-design method for WISs did already support many of the features required in Web 2.0 applications. This is particularly stressed by the focus of user contributions to a community or service and the incorporation of collaboration. It will further outline, how the method has to be extended to be fully functional as a Web 2.0 applications development method.The tutorial comprises three parts, the first one dealing with the transition from Web 1.0 to Web 2.0 and beyond, the second one dealing with the co-design methodology with particular emphasis on service orientation, personalisation and contribution to communities, and the final one devoted to the composition of services and collaboration.Part I will give a brief description of three stages that websites have gone through and still will go through: author-driven Web 1.0, user-driven and content-centred Web 2.0, and Web 3.0, which is characterised by (4C+P+VS), where 4C means Content, Commerce, Community and Context, P means Personalization, and VS denotes Vertical Search. In particular, Enterprise 2.0, cloud computing, mashups and Web-Oriented architecture are discussed in detail in order to show the problems in WIS development and the need for WIS development methods. Part II presents the major blocks of our WIS development methodology dealing with strategic modelling of WISs, usage modelling of WISs by means of storyboarding, conceptual modelling of WISs by means of media types, and semantics and pragmatics of storyboarding. Particular attention is paid to services and contributions to communities. Part III focuses on service composition and collaboration showing how the WIS co-design techniques presented in Part II can be adopted to solutions to various Web 2.0 applications including E-Business, Enterprise 2.0, Mashups, thus picking up on the challenges that were highlighted in part I.

Data warehouses integrate and aggregate data from various sources to support decision making within an enterprise. Usually, it is assumed that data are extracted from operational databases used by the enterprise. Web warehousing relaxes this view permitting data sources to be located anywhere on the world-wide web. In this paper we even go one step further and propose that web warehousing should exploit data-intensive web services. For this we adopt the view of the recently introduced model of abstract state services (ASSs). An ASS combines a hidden database layer with an operation-equipped view layer, and can be anything from a simple function to a full-fledged Web Information System, thus provides an abstraction of web services that can be made available for use by other systems, e.g. via the web. We demonstrate how data warehouses and OLAP systems can be considered in a natural way as ASSs, i.e. selected data and functionality of a data warehouse may be made available in the form of a generalised web service, and consequently ASS composition can be used for web warehousing. In order to become workable the model of ASSs has to be extended in a way that allows services to be searched for. For this we propose federations of services together with an ontology that specifies their semantics.

Web information systems (WIS) augment classical information systems by modern Web technologies. They require at the same time a careful development and support for the interaction or story spaces beside the classical support for the working space of users. These dimensions complicate the system development process. This paper shows how classical advanced methodologies can be carefully enhanced. We evaluated the Co-Design approach to information systems development according to the ISO/IEC 15504 Framework for Process Assessment (SPICE) and derived the potential and deficiencies of this approach. This evaluation has been used for a managed Co-Design methodology. Since WIS constantly change and evolve the development process never ends. We develop as a solution an optimization procedure and a runtime environment for the Co-Design approach that allows to cope with such changes, with evolution and extension of WIS and that demonstrates the new system facilities whenever a change is mastered.

Content management is the process of handling information within an organization or community. Therefore, content management systems have to provide generic functionality for generation, extraction, storage, and exchange of digital assets. Because of the heterogeneity and complexity of content, a sufficient semantical and user-oriented annotation of content is crucial. Although semantical annotation by metadata and ontologies together with reasoning support has been extensively studied for a long time, commercially available content management systems provide only basic support for semantic modelling. Conceptual aspects of content users and support of user specific intensions are neglected. In this paper we will analyze the mismatch between the requirements of content management and semantical description and propose a data model for content which treats semantic information not only as describing metadata but incorporates the data itself, the intension behind the data, the usage of data and the origin of data on the same level.

Utilization of global information resources as a part of risk management is insufficient. The authorities are maintaining information systems mainly for their own purposes, without access to high quality public information sources in Internet and without interoperability between systems of different authorities. Beneficial use of all available information resources would provide an opportunity to create knowledge based on different pieces of information. However, powerful distributed knowledge management, mining of the information items, analysing the quality of them, is needed to create new information to be utilized. The distributed operations needs support of complex network architectures, models supporting mutual understanding over the cultures and language borders, and ability to recognize the context and adapt the results to the new context. This paper opens discussion from different viewpoints to the topic of global risk management. Architectural solutions supporting interoperability, quality of data in wide networks, ubiquity and mobility as well as time dimension of the information space are covered.

The tutorial will address the various aspects of web information systems (WISs) such as purpose, usage, content, functionality, context, presentation. Starting from the strategic characterisation of a WIS, i.e. the very general question what the WIS is about, we first explore the kind of content that is to be presented in the WIS, and the kind of functionality, with which this content can be accessed, customised to the needs of particular WIS users, and updated. We then explore the modelling of users (or actors) of the WIS, their goals, and the tasks that have to be performed to reach these goals, and general rules for the formation of the WIS presentation.

The exact validation of streaming XML documents can be realised by using visibly push-down automata (VPA) that are defined by Extended Document Type Definitions (EDTD). It is straightforward to represent such an automaton as an Abstract State Machine (ASM). However, creating a whole VPA is not an efficient validation approach. In this paper it is shown, how the VPA construction can be avoided by using a refined ASM that only requires knowledge of the EDTD. In a second step this approach is extended to approximate validation of streaming XML documents taking at most k updates to the document into consideration.

Aggregation functions are a class of generic functions which must be usable in any database application. We characterize the case where the aggregation functions can be correctly applied on macrodata (data cube) which are computed on the microdata.

One common usage of the WWW is to provide information services, e.g. for regional event calenders, university lecture management, travel information, etc. Their design requires a clear picture of the system's usage and the supported technical environment. The core of the problem is to provide flexible access units based on extended views on some underlying database. The extension consists of escort information, links, operational facilities and means for the generation of different presentations. We call such units media objects. In order to also allow a flexible presentation for them, we adapt the metaphor of a container. In this way it is possible to present the same information in various ways depending on the user profile and the possible technical restrictions of the display device.