{"title":"Reasoning on Health Condition Evolution for Enhanced Detection of Vulnerable People in Emergency Settings","authors":"A. M. Tirado, E. Daga, E. Motta","doi":"10.1145/3460210.3493551","DOIUrl":"https://doi.org/10.1145/3460210.3493551","url":null,"abstract":"During an emergency event, such as a fire evacuation, support services benefit from having information about people who may require special assistance. In this context, health data represents a particularly important source of information, as it can allow an emergency response system to build an accurate picture of people's relevant health conditions and use this to advise responders. However, to perform this task, a system needs to represent and reason over the evolution of health conditions over time. Crucially, it needs to predict the probability that a potentially relevant condition mentioned in a health record is still valid at the time of the emergency. In this paper, we propose a methodology for representing the evolution of health conditions and reasoning about them in the context of an emergency scenario. To support our approach with data, we develop a pipeline to capture knowledge about condition evolution from reliable sources in natural language. We incorporate these two components into a system that predicts a person's likelihood of being vulnerable during an emergency event. Finally, we demonstrate that representing and reasoning about condition evolution improves the quality and precision of the recommendations provided by our system to emergency services.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124731457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lucas Simonne, N. Pernelle, Fatiha Saïs, R. Thomopoulos
{"title":"Differential Causal Rules Mining in Knowledge Graphs","authors":"Lucas Simonne, N. Pernelle, Fatiha Saïs, R. Thomopoulos","doi":"10.1145/3460210.3493584","DOIUrl":"https://doi.org/10.1145/3460210.3493584","url":null,"abstract":"In recent years, keen interest towards Knowledge Graphs has increased in both academia and the industry which has led to the creation of various datasets and the development of different research topics. In this paper, we present an approach that discovers differential causal rules in Knowledge Graphs. Such rules express that for two different class instances, a different treatment leads to different outcomes. Discovering causal rules is often the key of experiments, independently of their domain. The proposed approach is based on semantic matching relying on community detection and strata that can be defined as complex sub-classes. An experimental evaluation on two datasets shows that such mined rules can help gain insights into various domains.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121968279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Triple Classification for Scholarly Knowledge Graph Completion","authors":"M. Y. Jaradeh, Kuldeep Singh, M. Stocker, S. Auer","doi":"10.1145/3460210.3493582","DOIUrl":"https://doi.org/10.1145/3460210.3493582","url":null,"abstract":"structured information representing knowledge encoded in scientific publications. With the sheer volume of published scientific literature comprising a plethora of inhomogeneous entities and relations to describe scientific concepts, these KGs are inherently incomplete. We present exBERT, a method for leveraging pre-trained transformer language models to perform scholarly knowledge graph completion. We model triples of a knowledge graph as text and perform triple classification (i.e., belongs to KG or not). The evaluation shows that exBERT outperforms other baselines on three scholarly KG completion datasets in the tasks of triple classification, link prediction, and relation prediction. Furthermore, we present two scholarly datasets as resources for the research community, collected from public KGs and online resources.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128062734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ling Cai, K. Janowicz, Bo Yan, Rui Zhu, Gengchen Mai
{"title":"Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes","authors":"Ling Cai, K. Janowicz, Bo Yan, Rui Zhu, Gengchen Mai","doi":"10.1145/3460210.3493566","DOIUrl":"https://doi.org/10.1145/3460210.3493566","url":null,"abstract":"Almost all statements in knowledge bases have a temporal scope during which they are valid. Hence, knowledge base completion (KBC) on temporal knowledge bases (TKB), where each statementmay be associated with a temporal scope, has attracted growing attention. Prior works assume that each statement in a TKBmust be associated with a temporal scope. This ignores the fact that the scoping information is commonly missing in a KB. Thus prior work is typically incapable of handling generic use cases where a TKB is composed of temporal statements with/without a known temporal scope. In order to address this issue, we establish a new knowledge base embedding framework, called TIME2BOX, that can deal with atemporal and temporal statements of different types simultaneously. Our main insight is that answers to a temporal query always belong to a subset of answers to a time-agnostic counterpart. Put differently, time is a filter that helps pick out answers to be correct during certain periods. We introduce boxes to represent a set of answer entities to a time-agnostic query. The filtering functionality of time is modeled by intersections over these boxes. In addition, we generalize current evaluation protocols on time interval prediction. We describe experiments on two datasets and show that the proposed method outperforms state-of-the-art (SOTA) methods on both link prediction and time prediction.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114875619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Wind in Our Sails: Developing a Reusable and Maintainable Dutch Maritime History Knowledge Graph","authors":"Stijn Schouten, V. D. Boer, L. Petram, M. Erp","doi":"10.1145/3460210.3493548","DOIUrl":"https://doi.org/10.1145/3460210.3493548","url":null,"abstract":"Digital sources are more prevalent than ever but effectively using them can be challenging. One core challenge is that digitized sources are often distributed, thus forcing researchers to spend time collecting, interpreting, and aligning different sources. A knowledge graph can accelerate research by providing a single connected source of truth that humans and machines can query. During two design-test cycles, we convert four data sets from the historical maritime domain into a knowledge graph. The focus during these cycles is on creating a sustainable and usable approach that can be adopted in other linked data conversion efforts. Furthermore, our knowledge graph is available for maritime historians and other interested users to investigate the daily business of the Dutch East India Company through a unified portal.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Order Matters: Matching Multiple Knowledge Graphs","authors":"S. Hertling, Heiko Paulheim","doi":"10.1145/3460210.3493556","DOIUrl":"https://doi.org/10.1145/3460210.3493556","url":null,"abstract":"Knowledge graphs (KGs) provide information in machine interpretable form. In cases where multiple KGs are used in the same system, that information needs to be integrated. This is usually done by automated matching systems. Most of those systems consider only 1:1 (binary) matching tasks. Thus, matching a larger number of knowledge graphs with such systems would lead to quadratic efforts. In this paper, we empirically analyze different approaches to reduce the task of multi-source matching to a linear number of executions of binary matching systems. We show that the matching order of KGs and the multi-source strategy actually matter and that near-optimal results can be achieved with linear efforts.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115364254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Marriage is a Peach and a Chalice: Modelling Cultural Symbolism on the Semantic Web","authors":"Bruno Sartini, M. Erp, Aldo Gangemi","doi":"10.1145/3460210.3493552","DOIUrl":"https://doi.org/10.1145/3460210.3493552","url":null,"abstract":"In this work, we fill the gap in the Semantic Web in the context of Cultural Symbolism. Building upon earlier work in citesartini_towards_2021, we introduce the Simulation Ontology, an ontology that models the background knowledge of symbolic meanings, developed by combining the concepts taken from the authoritative theory of Simulacra and Simulations of Jean Baudrillard with symbolic structures and content taken from \"Symbolism: a Comprehensive Dictionary'' by Steven Olderr. We re-engineered the symbolic knowledge already present in heterogeneous resources by converting it into our ontology schema to create HyperReal, the first knowledge graph completely dedicated to cultural symbolism. A first experiment run on the knowledge graph is presented to show the potential of quantitative research on symbolism.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114945704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michel Wijkstra, Timo Lek, Tobias Kuhn, Kasper Welbers, Mickey Steijaert
{"title":"Living Literature Reviews","authors":"Michel Wijkstra, Timo Lek, Tobias Kuhn, Kasper Welbers, Mickey Steijaert","doi":"10.1145/3460210.3493567","DOIUrl":"https://doi.org/10.1145/3460210.3493567","url":null,"abstract":"Literature reviews have long played a fundamental role in synthesizing the current state of a research field. However, in recent years, certain fields have evolved at such a rapid rate that literature reviews quickly lose their relevance as new work is published that renders them outdated. We should therefore rethink how to structure and publish such literature reviews with their highly valuable synthesized content. Here, we aim to determine if existing Linked Data technologies can be harnessed to prolong the relevance of literature reviews and whether researchers are comfortable with working with such a solution. We present here our approach of \"living literature reviews'' where the core information is represented as Linked Data which can be amended with new findings after the publication of the literature review. We present a prototype implementation, which we use for a case study where we expose potential users to a concrete literature review modeled with our approach. We observe that our model is technically feasible and is received well by researchers, with our \"living'' versions scoring higher than their traditional counterparts in our user study. In conclusion, we find that there are strong benefits to using a Linked Data solution to extend the effective lifetime of a literature review.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130127211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Richardson, R. Çelebi, Sven van der Burg, Djura Smits, Lars Ridder, M. Dumontier, Tobias Kuhn
{"title":"User-friendly Composition of FAIR Workflows in a Notebook Environment","authors":"R. Richardson, R. Çelebi, Sven van der Burg, Djura Smits, Lars Ridder, M. Dumontier, Tobias Kuhn","doi":"10.1145/3460210.3493546","DOIUrl":"https://doi.org/10.1145/3460210.3493546","url":null,"abstract":"There has been a large focus in recent years on making assets in scientific research findable, accessible, interoperable and reusable, collectively known as the FAIR principles. A particular area of focus lies in applying these principles to scientific computational workflows. Jupyter notebooks are a very popular medium by which to program and communicate computational scientific analyses. However, they present unique challenges when it comes to reuse of only particular steps of an analysis without disrupting the usual flow and benefits of the notebook approach, making it difficult to fully comply with the FAIR principles. Here we present an approach and toolset for adding the power of semantic technologies to Python-encoded scientific workflows in a simple, automated and minimally intrusive manner. The semantic descriptions are published as a series of nanopublications that can be searched and used in other notebooks by means of a Jupyter Lab plugin. We describe the implementation of the proposed approach and toolset, and provide the results of a user study with 15 participants, designed around image processing workflows, to evaluate the usability of the system and its perceived effect on FAIRness. Our results show that our approach is feasible and perceived as user-friendly. Our system received an overall score of 78.75 on the System Usability Scale, which is above the average score reported in the literature.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126738988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Bucur, Tobias Kuhn, D. Ceolin, J. V. Ossenbruggen
{"title":"Expressing High-Level Scientific Claims with Formal Semantics","authors":"C. Bucur, Tobias Kuhn, D. Ceolin, J. V. Ossenbruggen","doi":"10.1145/3460210.3493561","DOIUrl":"https://doi.org/10.1145/3460210.3493561","url":null,"abstract":"The use of semantic technologies is gaining significant traction in science communication with a wide array of applications in disciplines including the life sciences, computer science, and the social sciences. Languages like RDF, OWL, and other formalisms based on formal logic are applied to make scientific knowledge accessible not only to human readers but also to automated systems. These approaches have mostly focused on the structure of scientific publications themselves, on the used scientific methods and equipment, or on the structure of the used datasets. The core claims or hypotheses of scientific work have only been covered in a shallow manner, such as by linking mentioned entities to established identifiers. In this research, we therefore want to find out whether we can use existing semantic formalisms to fully express the content of high-level scientific claims using formal semantics in a systematic way. Analyzing the main claims from a sample of scientific articles from all disciplines, we find that their semantics are more complex than what a straight-forward application of formalisms like RDF or OWL account for, but we managed to elicit a clear semantic pattern which we call the \"super-pattern''. We show here how the instantiation of the five slots of this super-pattern leads to a strictly defined statement in higher-order logic. We successfully applied this super-pattern to an enlarged sample of scientific claims. We show that knowledge representation experts, when instructed to independently instantiate the super-pattern with given scientific claims, show a high degree of consistency and convergence given the complexity of the task and the subject. These results therefore open the door on the longer run for allowing researchers to express their high-level scientific findings in a manner they can be automatically interpreted. This in turn will allow for automated consistency checking, question answering, aggregation, and much more.","PeriodicalId":377331,"journal":{"name":"Proceedings of the 11th on Knowledge Capture Conference","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130897155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}