Results of the Ontology Alignment Evaluation Initiative 2015

cheatham2016aInternational audienceOntology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2015 offered 8 tracks with 15 test cases followed by 22 participants. Since 2011, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2015 campaign

Results of the Ontology Alignment Evaluation Initiative 2014

dragisic2014aInternational audienceOntology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2014 offered 7 tracks with 9 test cases followed by 14 participants. Since 2010, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2014 campaign

Completing the Is-a Structure in Description Logics Ontologies

The World Wide Web contains large amounts of data and in most cases this data is without any explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the idea of the Semantic Web which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies which provide means for modeling a domain of interest. Developing and maintaining ontologies is not an easy task and it is often the case that defects are introduced into ontologies. This can be a problem for semantically-enabled applications such as ontology-based querying. Defects in ontologies directly influence the quality of the results of such applications as correct results can be missed and wrong results can be returned. This thesis considers one type of defects in ontologies, namely the problem of completing the is-a structure in ontologies represented in description logics. We focus on two variants of description logics, the EL family and ALC, which are often used in practice. The contributions of this thesis are as follows. First, we formalize the problem of completing the is-a structure as a generalized TBox abduction problem (GTAP) which is a new type of abduction problem in description logics. Next, we provide algorithms for solving GTAP in the EL family and ALC description logics. Finally, we describe two implemented systems based on the introduced algorithms. The systems were evaluated in two experiments which have shown the usefulness of our approach. For example, in one experiment using ontologies from the Ontology Alignment Evaluation Initiative 58 and 94 detected missing is-a relations were repaired by adding 54 and 101 is-a relations, respectively, introducing new knowledge to the ontologies

Completing the Is-a Structure in Description Logics Ontologies

The World Wide Web contains large amounts of data and in most cases this data is without any explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the idea of the Semantic Web which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies which provide means for modeling a domain of interest. Developing and maintaining ontologies is not an easy task and it is often the case that defects are introduced into ontologies. This can be a problem for semantically-enabled applications such as ontology-based querying. Defects in ontologies directly influence the quality of the results of such applications as correct results can be missed and wrong results can be returned. This thesis considers one type of defects in ontologies, namely the problem of completing the is-a structure in ontologies represented in description logics. We focus on two variants of description logics, the EL family and ALC, which are often used in practice. The contributions of this thesis are as follows. First, we formalize the problem of completing the is-a structure as a generalized TBox abduction problem (GTAP) which is a new type of abduction problem in description logics. Next, we provide algorithms for solving GTAP in the EL family and ALC description logics. Finally, we describe two implemented systems based on the introduced algorithms. The systems were evaluated in two experiments which have shown the usefulness of our approach. For example, in one experiment using ontologies from the Ontology Alignment Evaluation Initiative 58 and 94 detected missing is-a relations were repaired by adding 54 and 101 is-a relations, respectively, introducing new knowledge to the ontologies

Semantic Matching for Stream Reasoning

Autonomous system needs to do a great deal of reasoning during execution in order to provide timely reactions to changes in their environment. Data needed for this reasoning process is often provided through a number of sensors. One approach for this kind of reasoning is evaluation of temporal logical formulas through progression. To evaluate these formulas it is necessary to provide relevant data for each symbol in a formula. Mapping relevant data to symbols in a formula could be done manually, however as systems become more complex it is harder for a designer to explicitly state and maintain thismapping. Therefore, automatic support for mapping data from sensors to symbols would make system more flexible and easier to maintain. DyKnow is a knowledge processing middleware which provides the support for processing data on different levels of abstractions. The output from the processing components in DyKnow is in the form of streams of information. In the case of DyKnow, reasoning over incrementally available data is done by progressing metric temporal logical formulas. A logical formula contains a number of symbols whose values over time must be collected and synchronized in order to determine the truth value of the formula. Mapping symbols in formula to relevant streams is done manually in DyKnow. The purpose of this matching is for each variable to find one or more streams whose content matches the intended meaning of the variable. This thesis analyses and provides a solution to the process of semantic matching. The analysis is mostly focused on how the existing semantic technologies such as ontologies can be used in this process. The thesis also analyses how this process can be used for matching symbols in a formula to content of streams on distributed and heterogeneous platforms. Finally, the thesis presents an implementation in the Robot Operating System (ROS). The implementation is tested in two case studies which cover a scenario where there is only a single platform in a system and a scenario where there are multiple distributed heterogeneous platforms in a system. The conclusions are that the semantic matching represents an important step towards fully automatized semantic-based stream reasoning. Our solution also shows that semantic technologies are suitable for establishing machine-readable domain models. The use of these technologies made the semantic matching domain and platform independent as all domain and platform specific knowledge is specified in ontologies. Moreover, semantic technologies provide support for integration of data from heterogeneous sources which makes it possible for platforms to use streams from distributed sources

Completion of Ontologies and Ontology Networks

The World Wide Web contains large amounts of data, and in most cases this data has no explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the Semantic Web, which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies, which provide a means for modeling a domain of interest and are used for search and integration of data. In recent years many ontologies have been developed. To be able to use multiple ontologies it is necessary to align them, i.e., find inter-ontology relationships. However, developing and aligning ontologies is not an easy task and it is often the case that ontologies and their alignments are incorrect and incomplete. This can be a problem for semantically-enabled applications. Incorrect and incomplete ontologies and alignments directly influence the quality of the results of such applications, as wrong results can be returned and correct results can be missed. This thesis focuses on the problem of completing ontologies and ontology networks. The contributions of the thesis are threefold. First, we address the issue of completing the is-a structure and alignment in ontologies and ontology networks. We have formalized the problem of completing the is-a structure in ontologies as an abductive reasoning problem and developed algorithms as well as systems for dealing with the problem. With respect to the completion of alignments, we have studied system performance in the Ontology Alignment Evaluation Initiative, a yearly evaluation campaign for ontology alignment systems. We have also addressed the scalability of ontology matching, which is one of the current challenges, by developing an approach for reducing the search space when generating the alignment.Second, high quality completion requires user involvement. As users' time and effort are a limited resource we address the issue of limiting and facilitating user interaction in the completion process. We have conducted a broad study of state-of-the-art ontology alignment systems and identified different issues related to the process. We have also conducted experiments to assess the impact of user errors in the completion process. While the completion of ontologies and ontology networks can be done at any point in the life-cycle of ontologies and ontology networks, some of the issues can be addressed already in the development phase. The third contribution of the thesis addresses this by introducing ontology completion and ontology alignment into an existing ontology development methodology

Semantic Information Integration for Stream Reasoning

Abstract—The main contribution of this paper is a practical semantic information integration approach for stream reasoning based on semantic matching. This is an important functionality for situation awareness applications where temporal reasoning over streams from distributed sources is needed. The integration is achieved by creating a common ontology, specifying the semantic content of streams relative to the ontology and then use semantic matching to find relevant streams. By using semantic mappings between ontologies it is also possible to do semantic matching over multiple ontologies. The complete stream reasoning approach is integrated in the Robot Operating System (ROS) and used in collaborative unmanned aircraft systems missions. 1 I

Abduction Framework for Repairing Incomplete EL Ontologies: Complexity Results and Algorithms

In this paper we consider the problem of repairing missing is-a relations in ontologies. We formalize the problem as a generalized TBox abduction problem (GTAP). Based on this abduction framework, we present complexity results for the existence, relevance and necessity decision problems for the GTAP with and without some specific preference relations for ontologies that can be represented using a member of the EL family of description logics. Further, we present algorithms for finding solutions, a system as well as experiments

Integrating Ontology Debugging and Matching into the eXtreme Design Methodology

Ontology design patterns (ODPs) and related ontology development methodologies were designed as ways of sharing and reusing best practices in ontology engineering. However, while the use of these reduces the number of issues in the resulting ontologies defects can still be introduced into the ontology due to improper use or misinterpretation of the patterns. Thus, the quality of the developed ontologies is still a major concern. In this paper we address this issue by describing how ontology debugging and matching can be integrated in a state-of-the-art ontology development methodology based on ontology design patterns- the eXtreme Design methodology, and show the advantages in a case study based on a real world ontology

Completing the is-a structure in light-weight ontologies

 Background: With the increasing presence of biomedical data sources on the Internet more and more research effort is put into finding possible ways for integrating and searching such often heterogeneous sources. Ontologies are a key technology in this effort. However, developing ontologies is not an easy task and often the resulting ontologies are not complete. In addition to being problematic for the correct modelling of a domain, such incomplete ontologies, when used in semantically-enabled applications, can lead to valid conclusions being missed. Results: We consider the problem of repairing missing is-a relations in ontologies. We formalize the problem as a generalized TBox abduction problem. Based on this abduction framework, we present complexity results for the existence, relevance and necessity decision problems for the generalized TBox abduction problem with and without some specific preference relations for ontologies that can be represented using a member of the EL family of description logics. Further, we present algorithms for finding solutions, a system as well as experiments. Conclusions: Semantically-enabled applications need high quality ontologies and one key aspect is their completeness. We have introduced a framework and system that provides an environment for supporting domain experts to complete the is-a structure of ontologies. We have shown the usefulness of the approach in different experiments. For the two Anatomy ontologies from the Ontology Alignment Evaluation Initiative, we repaired 94 and 58 initial given missing is-a relations, respectively, and detected and repaired additionally, 47 and 10 missing is-a relations. In an experiment with BioTop without given missing is-a relations, we detected and repaired 40 new missing is-a relations