User Validation in Ontology Alignment

Dragisic, Zlatan; Іванова, Валентина; Lambrix, Patrick; Faria, Daniel; Jiménez-Ruiz, Ernesto; Pesquita, Cátia

doi:10.1007/978-3-319-46523-4_13

Cited by 57 publications

(48 citation statements)

References 39 publications

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“…In our work, we use the alignment tool LogMap 1 [6] since that system obtained good results during the evaluation OAEI 2014 [4] and, moreover, it allows to map individuals as well as classes.…”

Section: Overview Of Our Fusion Processmentioning

confidence: 99%

Dealing with Incompatibilities During a Knowledge Bases Fusion Process

Amarger

Chanet²,

Haemmerlé

et al. 2016

Graph-Based Representation and Reasoning

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract. More and more data sets are published on the linked open data. Reusing these data is a challenging task as for a given domain, several data sets built for specific usage may exist. In this article we present an approach for existing knowledge bases fusion by taking into account incompatibilities that may appear in their representations. Equivalence mappings established by an alignment tool are considered in order to generate a subset of compatible candidates. The approach has been evaluated by domain experts on datasets dealing with agriculture.

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Section: Overview Of Our Fusion Processmentioning

confidence: 99%

Dealing with Incompatibilities During a Knowledge Bases Fusion Process

Amarger

Chanet²,

Haemmerlé

et al. 2016

Graph-Based Representation and Reasoning

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show abstract

“…We thus first identify several evaluation use cases and discuss shared activities that could be efficiently supported through interactive visualization in Subsection 2.1. In Subsection 2.2 we connect this discussion with work about cognitive support for ontology mapping [8], requirements and evaluation of user interfaces in ontology alignment systems [10,6], and review capabilities for simultaneous visualization of several alignments in existing systems. In Subsection 2.3, we study the visualization approaches taken in alignment evaluation frameworks.…”

Section: Ontology Alignment Evaluationmentioning

confidence: 99%

“…Two recent studies review exploratory features in the user interfaces of ontology alignment systems [10,6]. Only one of the tools [4] (including its recent extensions [1,15]) provides support for visualization and exploration of several alignments together after discussing the need for such in connection to analytic tasks identified in interviews with alignment experts.…”

Section: Existing Approachesmentioning

confidence: 99%

Alignment Cubes: Towards Interactive Visual Exploration and Evaluation of Multiple Ontology Alignments

Іванова¹,

Bach²,

Pietriga³

et al. 2017

Lecture Notes in Computer Science

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Abstract. Ontology alignment is an area of active research where many algorithms and approaches are being developed. Their performance is usually evaluated by comparing the produced alignments to a reference alignment in terms of precision, recall and F-measure. These measures, however, only provide an overall assessment of the quality of the alignments, but do not reveal differences and commonalities between alignments at a finer-grained level such as, e.g., regions or individual mappings. Furthermore, reference alignments are often unavailable, which makes the comparative exploration of alignments at different levels of granularity even more important. Making such comparisons efficient calls for a "human-in-the-loop" approach, best supported through interactive visual representations of alignments. Our approach extends a recent tool, Matrix Cubes, used for visualizing dense dynamic networks. We first identify use cases for ontology alignment evaluation that can benefit from interactive visualization, and then detail how our Alignment Cubes support interactive exploration of multiple ontology alignments. We demonstrate the usefulness of Alignment Cubes by describing visual exploration scenarios, showing how alignment cubes support common tasks identified in the use cases.

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“…and dedicated to issues in relation to user involvement in the ontology alignment process. Papers I and II [65,32] focus on arguably the most cognitively intensive part of the alignment process-the manual validation of the candidate mappings, Paper III [64] addresses the issue of debugging the ontologies and their alignments and Paper IV [62] investigates the benefits from the latest technological advances to the alignment process. Papers V and VI [33,63] are connected to Research Question 2: How to efficiently support users during the evaluation of ontology alignments?…”

Section: Summary Of Papersmentioning

confidence: 99%

Fostering User Involvement in Ontology Alignment and Alignment Evaluation

Іванова¹

Self Cite

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The abundance of data at our disposal empowers data-driven applications and decision making. The knowledge captured in the data, however, has not been utilized to full potential, as it is only accessible to human interpretation and data are distributed in heterogeneous repositories.Ontologies are a key technology unlocking the knowledge in the data by providing means to model the world around us and infer knowledge implicitly captured in the data. As data are hosted by independent organizations we often need to use several ontologies and discover the relationships between them in order to support data and knowledge transfer. Broadly speaking, while ontologies provide formal representations and thus the basis, ontology alignment supplies integration techniques and thus the means to turn the data kept in distributed, heterogeneous repositories into valuable knowledge.While many automatic approaches for creating alignments have already been developed, user input is still required for obtaining the highest-quality alignments. This thesis focuses on supporting users during the cognitively intensive alignment process and makes several contributions.We have identified front-and back-end system features that foster user involvement during the alignment process and have investigated their support in existing systems by user interface evaluations and literature studies. We have further narrowed down our investigation to features in connection to the, arguably, most cognitively demanding task from the users' perspective-manual validation-and have also considered the level of user expertise by assessing the impact of user errors on alignments' quality. As developing and aligning ontologies is an error-prone task, we have focused on the benefits of the integration of ontology alignment and debugging.We have enabled interactive comparative exploration and evaluation of multiple alignments at different levels of detail by developing a dedicated visual environment-Alignment Cubes-which allows for alignments' evaluation even in the absence of reference alignments.Inspired by the latest technological advances we have investigated and identified three promising directions for the application of large, high-resolution displays in the field: improving the navigation in the ontologies and their alignments, supporting reasoning and collaboration between users. The work has been supported by the Swedish Research Council (2010-4759), the Swedish Graduate School in Computer Science (CUGS), the Swedish e-Science Research Centre (SeRC) and the EU FP7 project VALCRI (FP7-IP-608142).iii POPULÄRVETENSKAPLIG SAMMANFATTNING Under de senaste 30 åren har webben fundamentalt och oåterkalleligen förändrat våra livhur vi arbetar, hur vi tar del av underhållning och hur vi kommunicerar. Webben innehåller miljarder av informationskällor i en uppsjö olika format-websidor, databaser, dokument, figurer, etc.-alla ihopkopplade genom en enorm mängd länkar. Webben är inte statisk, utan växer konstant och erbjuder ett överflöd av data, som kan använd...

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User Validation in Ontology Alignment

Cited by 57 publications

References 39 publications

Dealing with Incompatibilities During a Knowledge Bases Fusion Process

Dealing with Incompatibilities During a Knowledge Bases Fusion Process

Alignment Cubes: Towards Interactive Visual Exploration and Evaluation of Multiple Ontology Alignments

Fostering User Involvement in Ontology Alignment and Alignment Evaluation

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