Fuzzy ontology for knowledge mobilisation and decision support

A growing concern for organisations is how they should deal with increasing amounts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advantage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available information systems are not capable of handling imprecise data, even though it can offer various advantages. Expert knowledge stored as linguistic expressions is a good example of imprecise but valuable data, i.e. data that is hard to exactly pinpoint to a definitive value. There is an obvious concern among organisations on how this problem should be handled; finding new methods for processing and storing imprecise data are therefore a key issue. Additionally, it is equally important to show that tacit knowledge and imprecise data can be used with success, which encourages organisations to analyse their imprecise data. The objective of the research conducted was therefore to explore how fuzzy ontologies could facilitate the exploitation and mobilisation of tacit knowledge and imprecise data in organisational and operational decision making processes. The thesis introduces both practical and theoretical advances on how fuzzy logic, ontologies (fuzzy ontologies) and OWA operators can be utilized for different decision making problems. It is demonstrated how a fuzzy ontology can model tacit knowledge which was collected from wine connoisseurs. The approach can be generalised and applied also to other practically important problems, such as intrusion detection. Additionally, a fuzzy ontology is applied in a novel consensus model for group decision making. By combining the fuzzy ontology with Semantic Web affiliated techniques novel applications have been designed. These applications show how the mobilisation of knowledge can successfully utilize also imprecise data. An important part of decision making processes is undeniably aggregation, which in combination with a fuzzy ontology provides a promising basis for demonstrating the benefits that one can retrieve from handling imprecise data. The new aggregation operators defined in the thesis often provide new possibilities to handle imprecision and expert opinions. This is demonstrated through both theoretical examples and practical implementations. This thesis shows the benefits of utilizing all the available data one possess, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web movement, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision.

Design and validation of stateful composite RESTful web services

A web service is a software system that provides a machine-processable interface to the other machines over the network using different Internet protocols. They are being increasingly used in the industry in order to automate different tasks and offer services to a wider audience. The REST architectural style aims at producing scalable and extensible web services using technologies that play well with the existing tools and infrastructure of the web. It provides a uniform set of operation that can be used to invoke a CRUD interface (create, retrieve, update and delete) of a web service. The stateless behavior of the service interface requires that every request to a resource is independent of the previous ones facilitating scalability. Automated systems, e.g., hotel reservation systems, provide advanced scenarios for stateful services that require a certain sequence of requests that must be followed in order to fulfill the service goals. Designing and developing such services for advanced scenarios with REST constraints require rigorous approaches that are capable of creating web services that can be trusted for their behavior. Systems that can be trusted for their behavior can be termed as dependable systems. This thesis presents an integrated design, analysis and validation approach that facilitates the service developer to create dependable and stateful REST web services. The main contribution of this thesis is that we provide a novel model-driven methodology to design behavioral REST web service interfaces and their compositions. The behavioral interfaces provide information on what methods can be invoked on a service and the pre- and post-conditions of these methods. The methodology uses Unified Modeling Language (UML), as the modeling language, which has a wide user base and has mature tools that are continuously evolving. We have used UML class diagram and UML state machine diagram with additional design constraints to provide resource and behavioral models, respectively, for designing REST web service interfaces. These service design models serve as a specification document and the information presented in them have manifold applications. The service design models also contain information about the time and domain requirements of the service that can help in requirement traceability which is an important part of our approach. Requirement traceability helps in capturing faults in the design models and other elements of software development environment by tracing back and forth the unfulfilled requirements of the service. The information about service actors is also included in the design models which is required for authenticating the service requests by authorized actors since not all types of users have access to all the resources. In addition, following our design approach, the service developer can ensure that the designed web service interfaces will be REST compliant. The second contribution of this thesis is consistency analysis of the behavioral REST interfaces. To overcome the inconsistency problem and design errors in our service models, we have used semantic technologies. The REST interfaces are represented in web ontology language, OWL2, that can be part of the semantic web. These interfaces are used with OWL 2 reasoners to check unsatisfiable concepts which result in implementations that fail. This work is fully automated thanks to the implemented translation tool and the existing OWL 2 reasoners. The third contribution of this thesis is the verification and validation of REST web services. We have used model checking techniques with UPPAAL model checker for this purpose. The timed automata of UML based service design models are generated with our transformation tool that are verified for their basic characteristics like deadlock freedom, liveness, reachability and safety. The implementation of a web service is tested using a black-box testing approach. Test cases are generated from the UPPAAL timed automata and using the online testing tool, UPPAAL TRON, the service implementation is validated at runtime against its specifications. Requirement traceability is also addressed in our validation approach with which we can see what service goals are met and trace back the unfulfilled service goals to detect the faults in the design models. A final contribution of the thesis is an implementation of behavioral REST interfaces and service monitors from the service design models. The partial code generation tool creates code skeletons of REST web services with method pre and post-conditions. The preconditions of methods constrain the user to invoke the stateful REST service under the right conditions and the post condition constraint the service developer to implement the right functionality. The details of the methods can be manually inserted by the developer as required. We do not target complete automation because we focus only on the interface aspects of the web service. The applicability of the approach is demonstrated with a pedagogical example of a hotel room booking service and a relatively complex worked example of holiday booking service taken from the industrial context. The former example presents a simple explanation of the approach and the later worked example shows how stateful and timed web services offering complex scenarios and involving other web services can be constructed using our approach.

Fedora Commons as core repository of the EU legislation

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

It’s a workflow engine. It’s working with linked data. It’s repository! – Supporting electronic thesis related processes in University of Helsinki library

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

E-thesis repository – processes and data

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Integrating open articles with open data in the life sciences with Europe PubMed Central.

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Invenio as a Blog Archiving platform

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Integration of JINR Information Resources

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Implementing Widely-used Vocabularies to Produce Linked Open Data in the Context of Open Repositories

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Biomedical Event Extraction with Machine Learning

Biomedical natural language processing (BioNLP) is a subfield of natural language processing, an area of computational linguistics concerned with developing programs that work with natural language: written texts and speech. Biomedical relation extraction concerns the detection of semantic relations such as protein-protein interactions (PPI) from scientific texts. The aim is to enhance information retrieval by detecting relations between concepts, not just individual concepts as with a keyword search. In recent years, events have been proposed as a more detailed alternative for simple pairwise PPI relations. Events provide a systematic, structural representation for annotating the content of natural language texts. Events are characterized by annotated trigger words, directed and typed arguments and the ability to nest other events. For example, the sentence “Protein A causes protein B to bind protein C” can be annotated with the nested event structure CAUSE(A, BIND(B, C)). Converted to such formal representations, the information of natural language texts can be used by computational applications. Biomedical event annotations were introduced by the BioInfer and GENIA corpora, and event extraction was popularized by the BioNLP'09 Shared Task on Event Extraction. In this thesis we present a method for automated event extraction, implemented as the Turku Event Extraction System (TEES). A unified graph format is defined for representing event annotations and the problem of extracting complex event structures is decomposed into a number of independent classification tasks. These classification tasks are solved using SVM and RLS classifiers, utilizing rich feature representations built from full dependency parsing. Building on earlier work on pairwise relation extraction and using a generalized graph representation, the resulting TEES system is capable of detecting binary relations as well as complex event structures. We show that this event extraction system has good performance, reaching the first place in the BioNLP'09 Shared Task on Event Extraction. Subsequently, TEES has achieved several first ranks in the BioNLP'11 and BioNLP'13 Shared Tasks, as well as shown competitive performance in the binary relation Drug-Drug Interaction Extraction 2011 and 2013 shared tasks. The Turku Event Extraction System is published as a freely available open-source project, documenting the research in detail as well as making the method available for practical applications. In particular, in this thesis we describe the application of the event extraction method to PubMed-scale text mining, showing how the developed approach not only shows good performance, but is generalizable and applicable to large-scale real-world text mining projects. Finally, we discuss related literature, summarize the contributions of the work and present some thoughts on future directions for biomedical event extraction. This thesis includes and builds on six original research publications. The first of these introduces the analysis of dependency parses that leads to development of TEES. The entries in the three BioNLP Shared Tasks, as well as in the DDIExtraction 2011 task are covered in four publications, and the sixth one demonstrates the application of the system to PubMed-scale text mining.

Becoming Locals in a Borderland of Exiles. Sense of Place in the Stories of Lithuania Minor Dwellers

This thesis deals with sense of place, the relation that we construct with our dwelling and the surrounding environment. The topic belongs to the field of human geography. Sense of place is deeply intertwined with the ideas of feeling at home and having a place where to return. I argue that narratives of life experience help us relate to the places we inhabit, go through, leave. My analysis concerns Lithuania Minor, the Lithuanian region lying by the border with Kaliningrad, and focuses in particular on Vilkyškiai, a village in the municipality of Pagėgiai. Most of the area’s original population disappeared in the war. After 1945, people from all over the country and the USSR settled here. This raised the prickly question of who belongs to the borderland. Refugees, migrants and settlers allow us to observe closely the development of sense of place and its main constituents. Through this analysis, I challenge the idea of people’s natural rights to places and shows how time, engagement in local-based cultural activities and recollection help foreigners become locals. To grasp the locals’ sense of place, I collected open, light-structured interviews and applied some elements of semantic analysis to interpret the materials. From my research, it emerges that the cultivation of the region’s cultural heritage and the practice of storytelling were crucial in making the respondents feel at home. Leaving aside all legalistic claims concerning the issue, I suggest that people belong to the land they dwell. I believe that their sense of place deserves consideration from the State and the other actors seeing them as migrants.

Connections that work – Linked Open Data demystified

Esitys Kirjastoverkkopäivillä 22.10.2014 Helsingissä – Presentation of Jakob Voß at the Library Network Days, October 22, 2014 in Helsinki.

A systematic mapping study of web services discovery mechanisms

Context: Web services have been gaining popularity due to the success of service oriented architecture and cloud computing. Web services offer tremendous opportunity for service developers to publish their services and applications over the boundaries of the organization or company. However, to fully exploit these opportunities it is necessary to find efficient discovery mechanism thus, Web services discovering mechanism has attracted a considerable attention in Semantic Web research, however, there have been no literature surveys that systematically map the present research result thus overall impact of these research efforts and level of maturity of their results are still unclear. This thesis aims at providing an overview of the current state of research into Web services discovering mechanism using systematic mapping. The work is based on the papers published 2004 to 2013, and attempts to elaborate various aspects of the analyzed literature including classifying them in terms of the architecture, frameworks and methods used for web services discovery mechanism. Objective: The objective if this work is to summarize the current knowledge that is available as regards to Web service discovery mechanisms as well as to systematically identify and analyze the current published research works in order to identify different approaches presented. Method: A systematic mapping study has been employed to assess the various Web Services discovery approaches presented in the literature. Systematic mapping studies are useful for categorizing and summarizing the level of maturity research area. Results: The result indicates that there are numerous approaches that are consistently being researched and published in this field. In terms of where these researches are published, conferences are major contributing publishing arena as 48% of the selected papers were conference published papers illustrating the level of maturity of the research topic. Additionally selected 52 papers are categorized into two broad segments namely functional and non-functional based approaches taking into consideration architectural aspects and information retrieval approaches, semantic matching, syntactic matching, behavior based matching as well as QOS and other constraints.

Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Category fluency test: effects of age, gender and education on total scores, clustering and switching in Brazilian Portuguese-speaking subjects

Verbal fluency tests are used as a measure of executive functions and language, and can also be used to evaluate semantic memory. We analyzed the influence of education, gender and age on scores in a verbal fluency test using the animal category, and on number of categories, clustering and switching. We examined 257 healthy participants (152 females and 105 males) with a mean age of 49.42 years (SD = 15.75) and having a mean educational level of 5.58 (SD = 4.25) years. We asked them to name as many animals as they could. Analysis of variance was performed to determine the effect of demographic variables. No significant effect of gender was observed for any of the measures. However, age seemed to influence the number of category changes, as expected for a sensitive frontal measure, after being controlled for the effect of education. Educational level had a statistically significant effect on all measures, except for clustering. Subject performance (mean number of animals named) according to schooling was: illiterates, 12.1; 1 to 4 years, 12.3; 5 to 8 years, 14.0; 9 to 11 years, 16.7, and more than 11 years, 17.8. We observed a decrease in performance in these five educational groups over time (more items recalled during the first 15 s, followed by a progressive reduction until the fourth interval). We conclude that education had the greatest effect on the category fluency test in this Brazilian sample. Therefore, we must take care in evaluating performance in lower educational subjects.