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Alignment Conservativity under the Ontology Change. JOURNAL OF INFORMATION TECHNOLOGY RESEARCH 2022. [DOI: 10.4018/jitr.299923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Recently, many methods have appeared to solve the problem of the evolution of alignment under the change of ontologies. The main challenge for them is to maintain consistency of alignment after applying the change. An alignment is consistent if and only if the ontologies remain consistent even when used in conjunction with the alignment. The objective of this work is to take a step forward by considering the alignment evolution according to the conservativity principle under the change of ontologies. In this context, an alignment is conservative if the ontological change should not introduce new semantic relationships between concepts from one of the input ontologies. We give methods for the conservativity violation detection and repair under the change of ontologies and we carry out an experiment on a dataset adapted from the Ontology Alignment Evaluation Initiative. The experiment demonstrates both the practical applicability of the proposed approach and shows the limits of the alignment evolution methods compared to the alignment conservativity under the change of ontologies.
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A consensual dataset for complex ontology matching evaluation. KNOWL ENG REV 2020. [DOI: 10.1017/s0269888920000247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Abstract
Simple ontology alignments, largely studied in the literature, link one single entity of a source ontology to one single entity of a target ontology. One of the limitations of these alignments is, however, their lack of expressiveness, which can be overcome by complex alignments, which are composed of correspondences involving logical constructors or transformation functions. While most work on complex ontology matching has been dedicated to the development of complex matching approaches, there is still a lack of benchmarks on which the complex approaches can be systematically evaluated. The aim of this paper is to present the process of constructing the consensual complex Conference dataset, describing the design choices and the methodology followed for constructing it. We discuss the issues the experts were faced with during the process and discuss the lessons learned and perspectives in the field.
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Abstract
Abstract
The development of semi-automated and automated ontology alignment techniques is an important part of realizing the potential of the Semantic Web. Until very recently, most existing work in this area was focused on finding simple (1:1) equivalence correspondences between two ontologies. However, many real-world ontology pairs involve correspondences that contain multiple entities from each ontology. These ‘complex’ alignments pose a challenge for existing evaluation approaches, which hinders the development of new systems capable of finding such correspondences. This position paper surveys and analyzes the requirements for effective evaluation of complex ontology alignments and assesses the degree to which these requirements are met by existing approaches. It also provides a roadmap for future work on this topic taking into consideration emerging community initiatives and major challenges that need to be addressed.
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Abstract
Biodiversity research studies the variability and diversity of organisms, including variability within and between species with particular focus on the functional diversity of traits and their relationship to environment. Managing biodiversity data implies dealing with its heterogeneous nature using semantics and tailored ontologies. These are themselves differently conceived, and combining them in semantically enabled applications necessitates an effective alignment between their concepts. This paper describes the ontology matching of biodiversity- and ecology-related ontologies. We illustrate diverse challenges introduced by this kind of ontologies to ontology matching in general. Real use cases requiring pairwise alignments between environment and trait ontologies are introduced. We describe our experience creating a new track at the Ontology Alignment Evaluation Initiative designed for this specific domain and report on the results obtained by state-of-the-art participating systems. The biodiversity and ecology use case turns out to be a strong one for ontology matching, introducing new interesting challenges. Even if most of the matching systems perform relatively well in the proposed matching tasks, there is still room for improvement. We highlight possible directions in that matter and elaborate on our plan to further progress with the track.
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An Ontological Approach to Knowledge Building by Data Integration. LECTURE NOTES IN COMPUTER SCIENCE 2020. [PMCID: PMC7304717 DOI: 10.1007/978-3-030-50436-6_35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
This paper discusses the uncertainty in the automation of knowledge building from heterogeneous raw datasets. Ontologies play a critical role in such a process by providing a well consolidated support to link and semantically integrate datasets via interoperability, as well as semantic enrichment and annotations. By adopting Semantic Web technology, the resulting ecosystem is fully machine consumable. However, while the manual alignment of concepts from different vocabularies is reasonable at a small scale, fully automatic mechanisms are required once the target system scales up, leading to a significant uncertainty.
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Abstract
Software engineering employs different benchmarks for a software evaluation. This enables software developers to continuously improve their product. The same needs are intrinsic for software tools in the semantic web field. While there are many different benchmarks already available, there has not been their overview and categorization yet. This work provides such an overview and categorization of benchmarks specifically oriented on benchmarks where an ontology plays an important role. Benchmarks are naturally categorized in line with ontology tool categorization along with an indication which activities those benchmarks are deliberate and which are non-deliberative. Although the article itself can already navigate a reader to an adequate benchmark, we moreover automatically designed a flexible rule-based recommendation tool based on the analysis of existing benchmarks.
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Abstract
Abstract
User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of the alignments produced by automated alignment algorithms. In this paper, we present a broad study on user validation of ontology alignments that encompasses three distinct but inter-related aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative 2015–2018 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services.
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Li W, Zhang S, Qi G. A graph-based approach for resolving incoherent ontology mappings. WEB INTELLIGENCE 2018. [DOI: 10.3233/web-180371] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Weizhuo Li
- MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China. E-mail:
- University of Chinese Academy of Sciences, Beijing, China. E-mail:
| | - Songmao Zhang
- MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China. E-mail:
| | - Guilin Qi
- School of Computer Science and Engineering, Southeast University, Nanjing, China. E-mail:
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Agibetov A, Jiménez-Ruiz E, Ondrésik M, Solimando A, Banerjee I, Guerrini G, Catalano CE, Oliveira JM, Patanè G, Reis RL, Spagnuolo M. Supporting shared hypothesis testing in the biomedical domain. J Biomed Semantics 2018; 9:9. [PMID: 29422110 PMCID: PMC5804102 DOI: 10.1186/s13326-018-0177-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 01/18/2018] [Indexed: 02/01/2023] Open
Abstract
Background Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses. Results In this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences. Conclusions We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.
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Affiliation(s)
- Asan Agibetov
- Italian National Research Council, Via De Marini 6, Genoa, 16149, Italy.,Center for Medical Statistics, Informatics, and Intelligent Systems, Institute for Artificial Intelligence and Decision Support, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria
| | | | - Marta Ondrésik
- 3B's Research Group, Biomaterials, Biodegradables and Biomimetics, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, University of Minho, Caldas das Taipas, Portugal.,ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | | | - Imon Banerjee
- Italian National Research Council, Via De Marini 6, Genoa, 16149, Italy.,Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, 94305, California, USA
| | | | - Chiara E Catalano
- Italian National Research Council, Via De Marini 6, Genoa, 16149, Italy
| | - Joaquim M Oliveira
- 3B's Research Group, Biomaterials, Biodegradables and Biomimetics, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, University of Minho, Caldas das Taipas, Portugal.,ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Giuseppe Patanè
- Italian National Research Council, Via De Marini 6, Genoa, 16149, Italy
| | - Rui L Reis
- 3B's Research Group, Biomaterials, Biodegradables and Biomimetics, Headquarters of the European Institute of Excellence on Tissue Engineering and Regenerative Medicine, University of Minho, Caldas das Taipas, Portugal.,ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Michela Spagnuolo
- Italian National Research Council, Via De Marini 6, Genoa, 16149, Italy
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