Ebook: Information Modelling and Knowledge Bases XXVII
Information modeling has become an increasingly important topic for researchers, designers and users of information systems. In the course of the last three decades, information modeling and knowledge bases have become essential, not only with regard to information systems and computer science in an academic context, but also with the use of information technology for business purposes.
This book presents 29 papers selected and upgraded from those delivered at the 25th International Conference on Information Modelling and Knowledge Bases (EJC 2015), held in Maribor, Slovenia, in June 2015. The aim of the conference is to bring together experts from different areas of computer science and other disciplines, including philosophy and logic, cognitive science, knowledge management, linguistics, and management science, with a view to understanding and solving problems and applying research results to practice. Areas covered by the papers include: conceptual modeling; knowledge and information modeling and discovery; linguistic modeling; cross-cultural communication and social computing; environmental modeling and engineering; and multimedia data modeling and systems.
The book will be of interest to all those whose work involves the development or use of information modeling and knowledge bases.
In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied.
The series of International Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organized by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and recently also other countries. Because of that “European Japanese” in the title of the conference was replaced by “International” in 2014. Workshop characteristic – discussion, enough time for presentations and limited number of participants is typical for the conference.
The 25th International Conference on Information Modelling and Knowledge Bases (EJC 2015) constitute a world-wide research forum for the exchange of scientific results and experiences. In this way a platform has been established drawing together researches as well as practitioners dealing with information modelling and knowledge bases. The main topics of EJC conferences target a variety of themes. First theme is conceptual modelling including modelling and specification languages, domain-specific conceptual modelling, concepts, concept theories and ontologies, conceptual modelling of large and heterogeneous systems, conceptual modelling of spatial, temporal and biological data and methods for developing, validating and communicating conceptual models.
An important subject is also knowledge and information modelling and discovery covering knowledge discovery, knowledge representation and knowledge management, advanced data mining and analysis methods, conceptions of knowledge and information, modelling information requirements, intelligent information systems as well as information recognition and information modelling.
One of the main themes is linguistic modelling with models of HCI, information delivery to users intelligent informal querying, linguistic foundation of information and knowledge, fuzzy linguistic models and philosophical and linguistic foundations of conceptual models.
Much attention is also paid to cross-cultural communication and social computing including cross-cultural support systems, integration, evolution and migration of systems, collaborative societies, multicultural web-based software systems, intercultural collaboration and support systems, moreover, social computing, behavioral modeling and prediction.
One of the latest topics is environmental modelling and engineering covering environmental information systems (architecture), spatial, temporal and observational information systems, large-scale environmental systems, collaborative knowledge base systems, agent concepts and conceptualization along with hazard prediction, prevention and steering systems.
Current theme is also multimedia data modelling and systems with modelling multimedia information and knowledge, content-based multimedia data management, content-based multimedia retrieval, privacy and context enhancing technologies, semantics and pragmatics of multimedia data as well as metadata for multimedia information systems.
The chapters of this book feature twenty-eight selected upgraded contributions that are the result of the presentations, comments and discussion at the conference. Additional material covers one chapter based on the panel session. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organizing committee, and the program coordination team. The long and the short papers presented in the conference are revised after the conference before publishing in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference.
Dengue fever is the fastest spreading communicable disease in the world. Spreading of virus is driven by increasing number of human moving. In many dengue-endemic countries, problem in dengue spreading is predicting infected area and determine perfect strategy to prevent the disease. Predicting infected area spot relates with pattern of human moving, while strategy to prevent is depend on vulnerability of area. In this paper we proposed an adaptive spreading model of area-disease based on human movement. This method combines an area-based mathematical model with discrete life-cycle of virus. The proposed method includes (1) state-space model of routine movement cycle, (2) algorithm of spreading, (3) prediction of the next infection area by graph relation, and (4) vulnerability value of suspected area. There are two important features in this method: real-time prediction of infected area and flexibility to adapt in the different situation. To perform the simulation we utilize real data of infected people in Surabaya in January 2011.The result shows that this method is suitable for near future prediction and easy to compensate time-varying changing. However, the accuracy needs to be improved.
Semantic computing is an important and promising approach to semantic analysis for various environmental phenomena and changes in real world. This paper presents a new semantic computing method with multi-spectrum images for analyzing and interpreting environmental phenomena and changes occurring in the physical world.
We have already presented a concept of “Semantic Computing System” for realizing global environmental analysis. This paper presents a new semantic computing method to realize semantic associative search for the multiple-colours-spectrum images in the multi-dimensional semantic space, that is “multi-spectrum semantic-image space” with semantic projection functions. This space is created for dynamically computing semantic equivalence, similarity and difference between multi-spectrum images and environmental situations.
We apply this system to global environmental analysis as a new platform of environmental computing. We have already presented the 5D World Map System, as an international research environment with spatio-temporal and semantic analysers. We also present several new approaches to global environmental-analysis for multi-spectrum images in “multi-spectrum semantic-image space.”
This paper presents the analysis and visualization of river-water quality in 25 rivers in Thailand by using 5D World Map system. Water pollution is analyzed by using Water Quality Index (WQI) and Metal Index (MI) which focus on Ping, Nan and Chao Phraya River (the important rivers of Thai). The WQI indicator was used to evaluate water quality by conductivity, NO3-N, NO2-N, NH3-N, Cd, Cr, Mn, Ni, Pb, Zn and As. The MI indicator was used to estimate concentration of metal in the river. The results on 5D World Map System show that several actual values assigned to water-quality parameters are shown in snapshots. The results of Water Quality Index (WQI) show the WQI levels 32.697 at Chaophraya river (Bangkok, 2004) and 38.534 at Ping river (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively, and can be classified into categories of quality-levels for Irrigation and Aquatic life. The results of Metal Index (MI) show that the MI level reaches 92.902 at Ping River (Nakhonsawan, 2014) and 1803.303 at Ping River (Nakhonsawan, 2014) for Irrigation and Aquatic life respectively.
Last decades have introduced different improvements into software process modeling yet none has proven itself as a silver bullet; software development community has proposed various solutions from rigid prescriptive processes to agile methods, in the end, however, every good software process implementation require process modeling that can be used for different purposes like process auditing, analysis, and evaluation. This paper discusses application of explicit knowledge profiles based on process meta-model within software process modeling, alignment with visual process modeling, and further analysis with simulation and reverse engineering methods.
Algorithms of graph partitioning exploited in conceptual database design were reused to define a methodology of database concept preservation. An algorithm, the concept construction algorithm that relates concept theory to computer science was designed. This algorithm, however, is not suitable for implementation. In this paper, a relationship between conceptual graphs and concept generalization hierarchies is established at the boundary between concept theory and computer science. The algorithmic property of class/concept completeness is given and an algorithm designed to achieve this property is introduced. This algorithm, which has its own autonomy, can also be considered as a refinement step of the concept construction algorithm.
Since its release in 2004, Ruby on Rails has evolved into a widely used full stack model-view-controller (MVC) framework. But despite the fact, that Rails (short for Ruby on Rails) is also used for developing enterprise-scale applications like Github or scientific tools like QTREDS, there is no official support for graphical modelling. This paper introduces a proposal to fill this gap by suggesting a model driven approach using the free yEd diagram editor as well as a specifically developed transformation tool and ER dialect. The implementation is based on the Rails data abstraction layer ActiveRecord and its provided domain specific languages.
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.
Icons are small signs with fixed meanings. Icons are usually context specific. For example in the context of a hotel, the client can often find icons in hotel room books and safety guides. Scandic Hotel chain, for example, currently provides the manual for its safety system in 14 languages. There are at least two major shortcomings of this system: (1) in emergency or panic situations, it is very difficult to find your own language from the leaflet, and (2) there are no Asian languages. There is an obvious need for a global icon-based hotel safety language. In our paper, we introduce an icon-based model, language and mobile application for hotel safety.
News about hacking have become so common that most people do not follow them anymore and many do not even care, considering hacking an inevitable vice. But situation is rapidly deteriorating and many people (even in academy) are not aware or do not take seriously the emerging future, where Internet is a ‘free wild West’ where everyone can freely break everything and steel whatever seems to be valuable. Here is presented overview of current situation, analyzed reasons for this and presented some ideas about future and an overview of progress made in Estonia in secure use of e-tools.
This work continues investigation of a problem of ontology visualization focused on effective ontological knowledge transmission to an user. For achievement of this purpose the authors had offered to form on the basis of an ontology fragments special structures – cognitive frames (CFs) which allowed to represent concepts of ontology in a compact and complete visual image aimed at perception by user not familiar with ontological modeling. The general ways of OWL axioms interpretation as a sets of SKOS model elements for their adaptation for visualization by means of CFs are presented.
We discuss main formalisations of information and knowledge available in literature. Knowledge is considered as a meaning of data for an actor who can understand and use it. The actor can be a computer, a robot, a human being or even a virus. We make an assumption that the usage of knowledge depends on material data carrier only as much as the latter allows one to perform operations and restricts knowledge processing through capacity and time. This permits one to consider knowledge abstractly. Knowledge handling requires some tools that are called knowledge systems. These systems have different forms and they can be connected in various ways as it follows from the analysed publications. A metrics of knowledge is discussed that reflects the capability of solving problems.
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.
Cyber-Physical Social Systems (CPSS) are transforming how we live and interact with the physical world by semantically linking devices, data, and people. However, while tremendous progress have been made in modelling various CPSS physical components such as sensors and actuators, the involvement of humans in CPSS poses additional challenges for conceptual modelling experts and systems designers. Part of the problem is due to the fact that, even though humans sense, actuate, and process information like other CPSS component, they do these things differently. Furthermore, it is difficult to exactly know, in advance, how the human entity will interact with a CPSS. In this paper, we present a framework for modelling human's involvement in CPSS. Use cases, lessons learnt, and challenges we face in using the framework to develop a CPSS for research and development in the environmental sciences are also discussed.
Smart cities make use of ICT in an effective ways to manage their resources to achieve high satisfaction levels for their citizens. The smart city applications are ICT services, they immensely depend on the achievement of characteristics, factors, and indicators to measure the degree of ICT that contribute to provide services. Therefore, the degree of ICT permits the judgment of the level of smartness of a city. This research proposes an enhanced framework to evaluate the smartness of a city based on three functional layers comprising of three smartness measuring factors (SMF). The smart measuring factors include smart infrastructure, smart citizen, smart governance, smart mobility, smart economy, smart lifestyle, smart technology adaptation tendency, smart service integration level, smart response feedback model and ICT Maturity comprise of the umbrella activity. The proposed framework computes the level of efficiency in utilizing city's resources and thus fills the research gap presenting a way to the evaluation of the smart cities.
A multi-database environment is commonly important for creating new values by integrating heterogeneous data resources. We have designed a realtime association computing system for interactive information exchange among multi-databases. The metadatabase system organized to measure a relationship of interactive data and define a feedback control output to a system. In this paper, we present the applicability of this method to a multidatabase on railway information. We show several experimental results which have been obtained by associative computing for two different databases as a multidatabase environment. By those results, we clarify the effectiveness of the associative computing method in the actual multi-databases.
In this paper, the minutes of the monetary policy of the Bank of Japan, the central bank of Japan, for the year 1998 has been analyzed for the extraction of the topics concerning Asian financial crisis. The currency crisis started in Thailand in 1997 and spread toward many Asian countries. We analyzed the Monetary Policy Meeting minutes by text mining technologies. Especially we conducted topic extraction from the meeting minutes using Latent Dirichlet Allocation (LDA) model and the time series of the changes of extracted topic ratios are shown. From the analysis results, one topic which seems to be the Asian financial crisis related topic can be found. The topic ratio change curve clearly corresponds to the calm down of economic indices such as currency exchange ratios and market interest rates in the Asian countries.
In this paper we present an algorithm for finding an optimal configuration of the artificial neural network that is used for the classification in our use case based effort estimation tool. This approach is based on feed-forward artificial neural network and is trained using the back-propagation training algorithm. Our goal is to find the optimal number of hidden neurons and the optimal number of training iterations to be able to reach maximal accuracy of neural network during the estimations. We demonstrate the usage of the proposed algorithm and its result on the estimation example that contains training and testing datasets of UseCases obtained from real software project development.
Background: A general restrictions-free theory supporting a functional dependency between the data, the artificial classification algorithm's internal specifics and its performance (e.g. error) has not yet been devised. Thus, in the design phase of building a classification tree, an important choice of selecting an appropriate algorithm family must be made.
Objective: The objective of this paper is to compare the Support Vector Machines and of the Neural Network classification algorithm on real data sets in terms of accuracy, and in terms of a function that best describes the error rate.
Methods: A Weka-based multilayer perceptron (MLP) neural network and a Support Vector Machines classification algorithms were applied to a set of datasets (n=121) from publicly available repositories (UCI) in step wise k-fold cross-validation and an error rate was measured in each step. First, four different functions, i.e. power, linear, logarithmic, exponential, were fit to the measured error rates. Where the fit was statistically significant (n=54) for all functions for both algorithms, we measured the average mean squared error rate for each function and its rank. The Wilcoxon's signed rank test was used to test whether the differences between ranks are significant.
Results: In a total of 54 datasets, the SVM algorithm using the exponential function was performing better than NN (P=0,023). Average mean squared error using all datasets and the exponential function for description of learning statistically significantly differ from each other. The exponential function is thus best describing the learning process. The chosen neural network and support vector machines algorithms are not different from each other in the capacity of capturing the interrelations in the data. However, SVM gives better results when using the exponential function.
Conclusion: The exponential model can be used to forecast the future performance of both algorithms based on a small training sample. The selection process of the two algorithms shows that both algorithms are equal on capturing the data interrelations, but support vector machines is yielding lower error rates.
This paper presents real-time sensing, processing and actuating functions of a collaborative knowledge sharing system called 5D World Map System, and the applications in the field of multidisciplinary environmental research and education. The first objective is to integrate the analysis of sensing data into a knowledge sharing system with multimedia, based on the framework of Sensing-Processing-Actuation of Cyber-Physical Systems. The proposed real-time sensing, processing and actuating functions enable multiple remote-users to acquire real-time sensing data from multiple sites around the world, perform analytical visualizations of the acquired sensing data by the selected calculation methods on the system to discover the incidental phenomena, and provide the analysed results to related users' terminal equipment automatically. The second objective of the research is to realize a new multidimensional data analysis and knowledge sharing system for a collaborative environment by applying the concept of “differential computing” to the analysis of sensing data. Especially, in the processing function, the time-series difference of the value of each sensor, the differences between the values of multiple sensors in a selected area, and the time-series differences between the values of multiple sensors, are calculated, to detect an environmental incident and estimate the possibility of occurrence of the same kind of incident in the neighboring sites within the same area. By using 5D World Map System integrated with these functions, the users are able to perform a global analysis on the environmental sensing data along with the related multimedia data on a single view of time-series maps, based on the spatiotemporal and semantic correlation calculations.
Event-driven architecture and complex event processing have become important topics in achieving business reactivity and proactivity. Even though many technologies to support this have been developed, there is still a need for providing support for complex events based on different levels of required expressivity. On the other hand, semantic technologies and semantic-based systems have emerged and are becoming more and more used, whereas there is no recognized solution for event processing in information systems based on semantic technologies. In this paper, we address these issues. We present a framework for ontology-based support for complex events, which allows for semantically enriched event definitions and automatic recognition. In order to automatically recognize complex events, an appropriate event definition basis has to be defined. The paper represents a continuation of our previous work by enhancing this basis and developing a SPARQL-based framework to provide a richer mechanism for event definitions and more efficient event detection. As a proof-of-concept, we provide an implementation of this framework using the semantic integration platform - Information Workbench. The implementation is available as an app that runs on top of the Information Workbench platform.
In this paper we present a conceptual model of fishery based on Resource-Event-Agent (REA) framework. We identify the concepts and relationships among them existing in fishery. The knowledge structure of fishery is formally presented so that the conceptual model be a formal ontology. For this, we introduce a formal semantic structure and a logical language. The meaning of the fishery-specific concepts and relationships is described as logical axioms. Through this formal approach, we discuss the adequateness and compatibility of REA framework to model fishery.
The only way for efficient use of limited resources is exchanging them each other in mobile environment. In this paper, an application for hybrid learning of wave pattern detection is presented. The detection accuracy and speed will be improved by exchanging learning results mutually among integrated detection methods. By this model, flexible and elastic usability can be implemented on mobile devices in mobile computing environment. And hybrid learning of wave pattern detection enables us to elastic and intelligent learning among devices.
Humankind faces a most crucial mission; we must endeavour, on a global scale, to restore and improve our natural and social environments. In this environmental study, we will use context-dependent differential computation to analyse changes in various factors (temperatures, colours, level of CO2, habitats, sea levels, coral areas, etc.). In this paper, we will discuss a global environmental computing methodology for analysing the diversity of nature and animals, using a large amount of information on global environments.
Linguistic theory of verb-valency frames is applied to the analysis of event and process ontology from the point of view of agents' reasoning. Since logical analysis presupposes full linguistic competency, it is suitable to make use of the results of linguistic analysis, in particular of verb-valency frames. Each process can be specified by a verb (what is to be done), possibly with parameters like the agent/actor of the process (who), the object to be operated on, resources, etc. In verb-valency frames each verb is characterized by the participants of an action denoted by the verb. Using verb-valency frames we can thus obtain a fine-grained specification of a process/procedure. The novel contribution of this paper is a proposal of a process ontology based on the results of linguistic analyses and classifications. Particular types of participants are then assigned to processes as their requisites or typical properties. The specification tool is Transparent Intensional Logic (TIL) with its procedural as opposed to denotational semantics.