Ebook: Information Modelling and Knowledge Bases XXV
Because of our ever increasing use of and reliance on technology and information systems, information modelling and knowledge bases continue to be important topics in those academic communities concerned with data handling and computer science. As the information itself becomes more complex, so do the levels of abstraction and the databases themselves.
This book is part of the series Information Modelling and Knowledge Bases, which concentrates on a variety of themes in the important domains of conceptual modeling, design and specification of information systems, multimedia information modeling, multimedia systems, ontology, software engineering, knowledge and process management, knowledge bases, cross-cultural communication and context modeling. Theoretical disciplines, including cognitive science, artificial intelligence, logic, linguistics and analytical philosophy, also receive attention.
The selected papers presented here cover many areas of information modeling and knowledge bases including: theory of concepts, semantic computing, data mining, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, software engineering, cross-cultural computing, environmental analysis, social networks, WWW information management, and many others. This new publication also contains papers initiated by the panels on: “Cross-cultural Communication with Icons and Images” and “Conceptual Modelling of Collaboration for Information Systems”. The book will be of interest to all those interested in advances in research and applications in the academic disciplines concerned.
Information modelling and knowledge bases have become important topics in academic communities related to information systems and computer science. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing.
The aim of this series of Information Modelling and Knowledge Bases is to make progress in research communities with scientific results and experiences achieved using innovative methods and systems in computer science and other disciplines, which have common interests in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. The research topics in this series are mainly concentrated on a variety of themes in the important domains: conceptual modelling, design and specification of information systems, multimedia information modelling, multimedia systems, ontology, software engineering, knowledge and process management, knowledge bases, cross-cultural communication and context modelling. Much attention is also paid to theoretical disciplines including cognitive science, artificial intelligence, logic, linguistics and analytical philosophy.
The selected papers cover many areas of information modeling and knowledge bases, namely theory of concepts, semantic computing, data mining, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, software engineering, cross-cultural computing, environmental analysis, social networks, WWW information management, and many others. This new issue also contains a paper initiated by panels “Cross-cultural communication with icons and images” and “Conceptual Modelling of Collaboration for Information Systems”.
We believe that this series of Information Modelling and Knowledge Bases will be productive, valuable and fruitful in the advance of research and applications of those academic areas.
The data deluge is defined by increasing amounts of large data with increasing degree of uncertainty. In a recent response, probabilistic databases are receiving a great deal of interest from research and industry. One popular approach to probabilistic databases is to extend traditional relational database technology to handle uncertainty. In this approach probabilistic databases are probability distributions over a collection of possible worlds of relational databases. On the one hand, research has seen various efforts to extend query evaluation from relational to probabilistic databases. On the other hand, updates have not received much attention at all. In this paper we show that well-known syntactic normal form conditions capture probabilistic databases with desirable update behavior. Such behavior includes the absence of data redundancy, insertion, deletion, and modification anomalies. We further show that standard normalization procedures can be applied to standard representations of probabilistic databases to obtain database schemata that satisfy the normal form condition, and can thus be updated efficiently.
We reconsider the nature and formal properties of the class inclusion relation, IS-A, from the point of view of information modeling and engineering of formal ontologies. In particular we review approaches to the elusive notion of intensionality. We then conduct an analysis adopting a metalogic setup where classes and properties are reified. This approach affords choices along the extensionality/intensionality spectrum. Our analysis concludes that the distinction between epistemic modes for distinguishing definitions, norms, hypotheses, and observational evidence is more important the extensionality/intensionality dichotomy in ontological engineering.
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.
Conceptual modelling in the large has been mainly developed within companies that handle large and complex applications. It covers a large variety of aspects such as models of structures, of business processes, of interaction among applications and with users, of components of systems, and of abstractions or of derived models such as data warehouses and OLAP applications. We develop new architectural techniques to conceptual modelling in the large.
In the last decades we got used to software applications (or computers, if you like) being everywhere and working for us. Yet sometimes they fail to work as desired. The current situation is often characterized as the second software crisis. There are many alleged causes of this state. They include, inter alia, web net overload, loss of data, inconsistency of data, intrusions by hackers, etc. etc. Yet in our opinion, the main problem is an old one. It consists in an insufficient specification of the procedures to be executed. We have been dealing with this problem since the beginning of computer era. Though there are many specification methods and languages, the problem remains very much a live issue and so far no satisfactory solution has been found. Our stance is that a declarative logical specification is needed. A serious candidate for such a high-quality declarative specification is a higher-order logic equipped with a procedural semantics. The goal of our contribution is to describe a specification method using Transparent Intensional Logic (TIL). TIL is a hyperintensional, typed, partial lambda-calculus. Hyperintensional, because the meaning of TIL-terms are not the functions/mappings themselves; rather, they are procedures producing functions as their products. Proper typing makes it possible to define inputs and outputs of a procedure. Finally, we must take into account partiality and the possibility of a failure to produce a product. A procedure may fail to produce a correct product for one of two reasons. Either the mapping the procedure produces is undefined at the argument(s) serving as point(s) of evaluation, or the procedure is ill- or under-specified, in which case the empirical execution process has undesirable results. This paper investigates, in a logically rigorous manner, how a detailed specification can prevent these problems.
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.
Refinement of specifications is inherently connected to the development of information systems. Throughout the development process models are refined towards the implementation. Especially the coherence of the models developed throughout this process is important. Concepts for adaptation has been developed in the area of functions. The application of this methodology in combination with the abstraction of workflows based on the concept of word fields allows to solve the adaptation problem for workflow applications.
This concept of generic workflows addresses the required adaptation and provides mechanisms to describe generic workflows and refine them during runtime to specific workflows adapted to the current situation. The chosen conservative approach is based on proven methods and provides a robust approach for workflow adaptation. And so it allows us to handle the highly dynamic characteristics of disaster management.
In the natural environment research field, computer systems are widely utilized. The majority of computer systems are used to store observed data. Super computers are used to simulate environment changes, for example, the global climate change. Prior research has shown that computer systems make it possible to store and access huge amount of observed data based on database manage systems. The simulation accuracy of nature environment changes is also improved accompanied by the progress of computer technology. In this work, we propose a new method to discover what are happening in the nature of our planet utilizing differential computing in our Multi-dimensional World Map. We have various (almost infinite) aspects and contexts in environmental changes in our planet, and it is essential to realize a new analyzer for computing differences in those situations for discovering actual aspects and contexts existing in the nature of our planet. By using Differential Computing, important factors that change natural environment are highlighted. Furthermore, the highlighted factors are visualized by using our Multi-dimensional World Map, which makes it possible to view the nature environment changes in the view of history, geographic, etc.
With the rapid increase in popularity of mobile devices, a huge number of mobile applications are published with rich functionalities. However, the available functionalities still do not satisfy the variety of users' needs. Some common tasks cannot be accomplished by using an individual application, but require the interoperability of multiple applications. Unfortunately, most of the applications are not ready to be integrated due to the lack of formal descriptions of its offered functionalities. Accordingly, it becomes essential to describe the shared functionalities of mobile applications in a structured way. We address this problem by proposing an XML-based modeling language, called LIMA (Language for Interoperability of Mobile Applications), that allows developers to describe the shared functionalities of mobile applications. In order to enhance the interoperability, LIMA is designed to abstract the functionalities of mobile applications from the concrete details on how to invoke those functions. We demonstrate our modeling language by implementing a parser tool that generates proxy classes to leverage the mobile application development process. Moreover, we apply our modeling language with a mobile mashup approach to demonstrate automatic mobile application integration.
Twitter is one of the largest social media platforms in the world. Although Twitter can be used as a tool for getting valuable information related to a topic of interest, it is a hard task for us to find users to follow for this purpose. In this paper, we present a method for Twitter user recommendation based on user relations and taxonomical analysis. This method first finds some users to follow related to the topic of interest by giving keywords representing the topic, then picks up users who continuously provide related tweets from the user list. In the first phase we rank users based on user relations obtained from tweet behaviour of each user such as retweet and mention (reply), and we create topic taxonomies of each user from tweets posted during different time periods in the second phase. Experimental results show that our method is very effective in recommending users who post tweets related to the topic of interest all the time rather than users who post related tweets just temporarily.
This paper considers the difficulties faced by the stakeholders in general requirements engineering (RE). These difficulties range from the complexity of requirements gathering to requirements presentation. Affordable visualization techniques have been widely implemented to support the requirements engineering community. However, no universal characteristics that could be associated with requirements completion have been identified so far. The research focus of this paper is driven by the above considerations to introduce the icon-based language comprising a set of icon notations, syntactic and semantics. Icon-based language would support the requirements engineering tasks that normally executed by stakeholders and provide a visual modelling language to unify the requirement activities. Research approach is recapitulate, firstly, by identifying the requirements engineering artefact, secondly by refining the icon artefact, and thirdly, by integrating those two artefacts by means of requirements engineering process. The result aimed at to make communications more interactive and manageable by facilitating the exchange of information and to promote global understanding in any requirements development context across cultural and national boundaries.
This paper describes a method for discovering URLs with contextually relevant deep-topics, and then propagating such information to collaborating users lacking such information. When a user is knowledgeable about a subject, their reasons for frequently browsing a URL extend beyond the fact that it is merely related to said subject. This paper's method includes an algorithm for discovering the surface-topic of a URL, and the underlying deep-topic that a user is truly interested in with respect to a given URL. The deep-topic extraction process works by using URLs linked together through a user's behavioral browsing patterns in order to discover the surface or group-topic of surrounding URLs, and then subtracting those topics to discover hidden deeper topics. This paper describes the three parts of the method: Information Extraction, Propagation, and Verification & Integration, which together form a method with high levels of parallelism due to its distributed and independent nature. This paper also discusses concrete usage-scenarios for the included method, and data structures which would support the implementation of this paper's method.
Numerous stock market analysis methods have been proposed from simple moving average to the use of artificial intelligence such as neural networks and Bayesian networks. In this paper, we introduce a new concept and a methodology that enable predictability of asset price movement in the market by way of inference from the past data. We use schema to describe an economic instance, and a set of schema in time series to describe the flow of economic instances in the past. Within the schema, we introduce a concept of velocity and momentum to effectively characterize the dynamic nature of the market. We compare the current and the past instances to identify resemblance and take inference as a predictive capability of future asset price movement.
The geometrically enhanced ER model (GERM) addresses conceptual geometric modelling on two levels. On the surface level GERM is an extended ER model, in which attributes are associated with types with sets of values as domains. On the internal level some of the types, the geometric types, are further associated with geometric domains, which define point sets by means of algebraic curves. For query handling the operations on geometric types give rise to operations on point sets, which can be realized by a small set of operations on algebraic curves. The core problem is then to obtain a surface representation as the result. We show that symbolic computation is essential for solving this problem.
The trend of globalization has been seen for several decades. Wider markets, the vicinity of the client, cheaper working force and wider IT-professional pools are driving software organizations to offshore software product development. As the result, the software engineering (SE) teams are distributed and multicultural. Differences in cultural backgrounds cause various issues which often stay unrecognized and unsolved for years in global organizations. The operation of software developing organizations is divided into SE processes, described in international standards such as ISO/IEC 15504. SE processes are impacted by cultural factors in global environment because software development relies heavily on the communication with the client and among the team members. The aim of this paper is to propose a tool for cultural sensitivity assessment in SE processes. Cultural sensitivity assessment model (CSAM) helps to identify cultural factors that impact the outcomes of the SE processes. The results of the cultural sensitivity identification in SE processes can be further benefited in cultural training, strategy planning or even software process improvement (SPI).
This paper proposes a time series topic extraction method to investigate the transitions of people's needs after the East Japan Great Earthquake using latent semantic analysis. Our target data is a blog about afflicted people's needs provided by a non-profit organization in Tohoku, Japan. The method crawls blog messages, extracts terms, and forms document-term matrix over time. Then, the method adopts the latent semantic analysis and extract hidden topics (people's needs) over time. In our previous work, we already proposed the graph-based topic extraction method using the modularity measure. Our previous method could visualize topic structure transition, but could not extract clear topics. In this paper, to show the effectiveness of our proposed method, we provide the experimental results, and compare them with our previous method's results.
Requirements on software products are becoming more and more complicated and software systems of today are characterized by increasing complexity and size. Therefore, software systems can no longer be developed feasibly without the processes supported by appropriate methods. We propose a method for configuration and modification of software processes in companies based on gathered knowledge and our approach allows to support and optimize the processes with formal methods of modeling.
Combilog is a compositional relational programming language that allows writing relational logic programs by functionally composing relational predicates. Higraphs, a diagram formalism is consulted to simplify some of the textual complexity of compositional relational programming to achieve a visual system that can represent these declarative meta-programs, with the final intention to design an intuitive and visually assisted complete development practice. As a proof of concept, an implementation of a two-way parser/visualizer is presented.
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.
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.
This paper develops a definition of the model and the conceptual model that encompasses model notions used in Computer Science, Mathematics, Natural and Social Sciences, and Humanities. Models are artifacts which have a background, a basis, and a context. They are products that are used by community of practice such as programmers, learners, business users, and evaluators. Models must be adequate for the representation of origins, faithful for their signification, functional; thus providing the necessary capability and be able to provide effective deployment.
The paper discusses on context-based schema - the sensing, processing and actuating (SPA) architecture - for situation specific communication. In this paper, we apply the schema to bear communication research. The main idea of our research is to identify groups of voice sequences which are typical for certain situations such as waking up from hibernation, cubs coming out for the first time from the den, a female bear teaching her cubs, cubs playing, mating and defense of territory. The communication schema of a brown bear seems to be very goal-oriented and situation specific. Once we can identify context-dependent communication schemas, we will be able to better interpret bear vocalization. The bear communication ABC can be used by scientists, authorities, teachers, students, hikers and especially citizens living in bear-rich areas. For environmental conservation initiatives and programs, it is also important to interpret, early enough, weak signals coming from the bears' natural environments.
The resource exchanging is the key function in mobile computing environment. We have the limitation of the capacity for every single mobile device. The only way for efficient use of limited resources is exchanging them each other in mobile environment. In this paper, a mutual resource exchanging model in mobile computing is proposed. Furthermore, two applications of the model are shown. The first one is a universal battery. It enables us to exchange resources of electricity from one to another mobile device. The second application is bandwidth resource sharing among mobile devices. It provides the mobility of bandwidth from devices with surplus network connectivity to other devices that requires more network bandwidth. By this model, flexible and elastic usability can be implemented on mobile devices in mobile computing environment.
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.
Visual information such as pictorial symbols, icons and images capture our imagination. In our paper, we discuss icons and images in the context of cross-cultural communication. The authors present their own viewpoints to the subject. We discuss about communication in the multi-cultural world and analyze icons in cross-cultural context. Two professional application domains for icons will be presented. A Kansei-based cross-cultural multimedia computing system and a cross-cultural image communication system are described. Icons are a good means for communication within a certain application domain and in a certain context.