"Uplift" mapping execution applies a set of mapping definitions to transform non-RDF data sources to RDF. During the uplift mapping process, mapping definitions are iteratively refined until they conform with the user's expressed requirements. The W3C standard R2RML is one language which allows for specifying the mappings needed to generate RDF datasets from relational databases. Many approaches have been proposed to assess the quality of the generated RDF datasets, even though the root cause of several of those quality violations are found in mappings. In this paper, we present a framework for assessing and refining the quality of the definitions used to transform non-RDF data to RDF. This paper also provides an overview of an implementation of the proposed quality assessment framework for the R2RML mapping language, which uses the W3C standard Shapes Constraint Language (SHACL). We also provide a demonstration of the proposed framework and its implementation through a walkthrough use case.
{"title":"A Framework for Assessing and Refining the Quality of R2RML mappings","authors":"Alex Randles, Ademar Crotti Junior, D. O’Sullivan","doi":"10.1145/3428757.3429089","DOIUrl":"https://doi.org/10.1145/3428757.3429089","url":null,"abstract":"\"Uplift\" mapping execution applies a set of mapping definitions to transform non-RDF data sources to RDF. During the uplift mapping process, mapping definitions are iteratively refined until they conform with the user's expressed requirements. The W3C standard R2RML is one language which allows for specifying the mappings needed to generate RDF datasets from relational databases. Many approaches have been proposed to assess the quality of the generated RDF datasets, even though the root cause of several of those quality violations are found in mappings. In this paper, we present a framework for assessing and refining the quality of the definitions used to transform non-RDF data to RDF. This paper also provides an overview of an implementation of the proposed quality assessment framework for the R2RML mapping language, which uses the W3C standard Shapes Constraint Language (SHACL). We also provide a demonstration of the proposed framework and its implementation through a walkthrough use case.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125549862","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}
The natural way, how JSON documents can be queried and modified is to store them first in relational environment. In such a case, the features of relational DBMSs such as transaction processing, can be used. In this paper we compare two different mapping techniques: Adjacency List and the Single-Table Data Mapping (STDM) algorithm, which can be used, among other techniques, to store JSON documents in relational tables. The reason to choose and compare these two techniques is due to their origin: both are representatives of two different non-native storing techniques. The former is a general technique, which can be applied to any data presented in hierarchical form, while the latter is a representative of the family of XML-to-Relational storage algorithms, which can be used for JSON, too. Our results show that using the STDM algorithm the size of resulting relational table is approximately 70% of the size of the corresponding table generated with Adjacency List. Additionally, the STDM algorithm significantly outperforms Adjacency List concerning time.
{"title":"Non-native Techniques for Storing JSON Documents into Relational Tables","authors":"D. Petković","doi":"10.1145/3428757.3429103","DOIUrl":"https://doi.org/10.1145/3428757.3429103","url":null,"abstract":"The natural way, how JSON documents can be queried and modified is to store them first in relational environment. In such a case, the features of relational DBMSs such as transaction processing, can be used. In this paper we compare two different mapping techniques: Adjacency List and the Single-Table Data Mapping (STDM) algorithm, which can be used, among other techniques, to store JSON documents in relational tables. The reason to choose and compare these two techniques is due to their origin: both are representatives of two different non-native storing techniques. The former is a general technique, which can be applied to any data presented in hierarchical form, while the latter is a representative of the family of XML-to-Relational storage algorithms, which can be used for JSON, too. Our results show that using the STDM algorithm the size of resulting relational table is approximately 70% of the size of the corresponding table generated with Adjacency List. Additionally, the STDM algorithm significantly outperforms Adjacency List concerning time.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129569568","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}
Quality distant education has received growing scientific attention in the recent decades, which is accelerated in present times as a result of the COVID-19 pandemic; traditional in-class teaching methods needed a rapid transformation to be effective in a distant educational context as well, to reduce the existing and deepening digital divide. Convinced by the "FAIR-principles" and the "CARE" Standard, the present paper searches for gamified applicational examples in forecasting and business studies. Through the discussion of the presently existing literature reviews in this domain, the article sheds light upon the development and current scientific standing of this research area. During the search for ethical implications, the present paper aims to formulate future considerations, believing in the idea that gamification, holding the possibility of successful individual outcomes for learners in knowledge acquisition and also in the form of psychological benefits, could serve as a tool for humanity to reach a global society where no one is left behind.
{"title":"Gamification as an enabler of quality distant education: The need for guiding ethical principles towards an education for a global society leaving no one behind","authors":"A. Tjoa, Flora Poecze","doi":"10.1145/3428757.3429145","DOIUrl":"https://doi.org/10.1145/3428757.3429145","url":null,"abstract":"Quality distant education has received growing scientific attention in the recent decades, which is accelerated in present times as a result of the COVID-19 pandemic; traditional in-class teaching methods needed a rapid transformation to be effective in a distant educational context as well, to reduce the existing and deepening digital divide. Convinced by the \"FAIR-principles\" and the \"CARE\" Standard, the present paper searches for gamified applicational examples in forecasting and business studies. Through the discussion of the presently existing literature reviews in this domain, the article sheds light upon the development and current scientific standing of this research area. During the search for ethical implications, the present paper aims to formulate future considerations, believing in the idea that gamification, holding the possibility of successful individual outcomes for learners in knowledge acquisition and also in the form of psychological benefits, could serve as a tool for humanity to reach a global society where no one is left behind.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122037173","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}
Mahdi Bennara, Antoine Zimmermann, Maxime Lefrançois, Nurten Messalti
The advent of the Web of Things as an application layer for the Internet of Things has led to the proliferation of Web services exposing data and functionality of the networked objects. Since resource-oriented architectures align well with the WoT architectures, RESTful services have been the go-to interface to expose the connected devices on the Web. However, the heterogeneity of descriptions of devices and services as well as underlying IoT-level protocols has led to a number of interoperability issues. Recently, the growing popularity of semantically-enabled services has led to the emergence of services described with and exchanging RDF. In this position paper, we attempt to frame the challenges encountered in enabling semantic interoperability of heterogeneous WoT services, with the help of a real world production line scenario. We also propose preliminary solutions to the main issues hampering the establishment of true semantic interoperability on the WoT.
{"title":"Interoperability of Semantically-Enabled Web Services on the WoT: Challenges and Prospects","authors":"Mahdi Bennara, Antoine Zimmermann, Maxime Lefrançois, Nurten Messalti","doi":"10.1145/3428757.3429199","DOIUrl":"https://doi.org/10.1145/3428757.3429199","url":null,"abstract":"The advent of the Web of Things as an application layer for the Internet of Things has led to the proliferation of Web services exposing data and functionality of the networked objects. Since resource-oriented architectures align well with the WoT architectures, RESTful services have been the go-to interface to expose the connected devices on the Web. However, the heterogeneity of descriptions of devices and services as well as underlying IoT-level protocols has led to a number of interoperability issues. Recently, the growing popularity of semantically-enabled services has led to the emergence of services described with and exchanging RDF. In this position paper, we attempt to frame the challenges encountered in enabling semantic interoperability of heterogeneous WoT services, with the help of a real world production line scenario. We also propose preliminary solutions to the main issues hampering the establishment of true semantic interoperability on the WoT.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115291366","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}
Matteo Paganelli, Francesco Del Buono, F. Guerra, N. Ferro
Evaluation of the quality of data integration processes is usually performed via manual onerous data inspections. This task is particularly heavy in real business scenarios, where the large amount of data makes checking all the tuples infeasible and the frequent updates, i.e. changes in the sources and/or new sources, impose to repeat the evaluation over and over. Our idea is to address this issue by providing the experts with an unsupervised measure, based on word frequencies, which quantifies how much a dataset is representative of another dataset, giving an indication of how good is the integration process and whether deviations are happening and a manual inspection is needed. We also conducted some preliminary experiments, using shared datasets, that show the effectiveness of the proposed measures in typical data integration scenarios.
{"title":"Unsupervised Evaluation of Data Integration Processes","authors":"Matteo Paganelli, Francesco Del Buono, F. Guerra, N. Ferro","doi":"10.1145/3428757.3429129","DOIUrl":"https://doi.org/10.1145/3428757.3429129","url":null,"abstract":"Evaluation of the quality of data integration processes is usually performed via manual onerous data inspections. This task is particularly heavy in real business scenarios, where the large amount of data makes checking all the tuples infeasible and the frequent updates, i.e. changes in the sources and/or new sources, impose to repeat the evaluation over and over. Our idea is to address this issue by providing the experts with an unsupervised measure, based on word frequencies, which quantifies how much a dataset is representative of another dataset, giving an indication of how good is the integration process and whether deviations are happening and a manual inspection is needed. We also conducted some preliminary experiments, using shared datasets, that show the effectiveness of the proposed measures in typical data integration scenarios.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116968156","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}
Data integration is one of the key problems in the era of Big Data analytics. The key challenge of data integration is the identification of records representing the same entities (e.g. person). This task is referred to as Record Linkage. It is uncommon for different data sources to share a unique identifier hence the records must be matched by comparing their corresponding values. Most of the existing methods assume that records across different sources are structured and represented by the same set of attributes (e.g. name, date of birth). However, nowadays majority of the data comes without structure (e.g. social media sites). We propose a new approach to Record Linkage based on application of Siamese Neural Network. The model can be applied with structured, semi-structured and unstructured records and it does not assume a common format across different data sources. We demonstrate that the model performs on par with other approaches, which make constraining assumptions regarding the data.
{"title":"Siamese Neural Network for Unstructured Data Linkage","authors":"Anna Jurek-Loughrey","doi":"10.1145/3428757.3429106","DOIUrl":"https://doi.org/10.1145/3428757.3429106","url":null,"abstract":"Data integration is one of the key problems in the era of Big Data analytics. The key challenge of data integration is the identification of records representing the same entities (e.g. person). This task is referred to as Record Linkage. It is uncommon for different data sources to share a unique identifier hence the records must be matched by comparing their corresponding values. Most of the existing methods assume that records across different sources are structured and represented by the same set of attributes (e.g. name, date of birth). However, nowadays majority of the data comes without structure (e.g. social media sites). We propose a new approach to Record Linkage based on application of Siamese Neural Network. The model can be applied with structured, semi-structured and unstructured records and it does not assume a common format across different data sources. We demonstrate that the model performs on par with other approaches, which make constraining assumptions regarding the data.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124467979","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}
A. Khiat, Mirette Elias, A. Foldenauer, M. Koehm, I. Blumenstein, Giulio Napolitano
Inflammatory bowel disease (IBD) is a chronic disease characterized by numerous, hard to predict periods of relapse and remission. "Digital twin" approaches, leveraging personalized predictive models, would significantly enhance therapeutic decision-making and cost-effectiveness. However, the associated computational and statistical methods require high quality data from a large population of patients. Such a comprehensive repository is very challenging to build, though, and none is available for IBD. To overcome this, a promising approach is to employ a knowledge graph, which is built from the available data and would help predicting IBD episodes and delivering more relevant personalized therapy at the lowest cost. In this research, we present a knowledge graph developed on the basis of patient records which are collected from one of the largest German gastroentologic outpatient clinic. First, we designed IBD ontology that encompasses the vocabulary, specifications and characteristics associated by physicians with IBD patients, such as disease classification schemas (e.g., Montreal Classification of IBD), status of the disease activity, and medications. Next, we defined the mappings between ontology entities and database variables. Physicians and project members participating in the Fraunhofer MED2ICIN project, validated the ontology and the knowledge graph. Furthermore, the knowledge graph has been validated against the competency questions compiled by physicians.
{"title":"Towards an Ontology Representing Characteristics of Inflammatory Bowel Disease","authors":"A. Khiat, Mirette Elias, A. Foldenauer, M. Koehm, I. Blumenstein, Giulio Napolitano","doi":"10.1145/3428757.3429110","DOIUrl":"https://doi.org/10.1145/3428757.3429110","url":null,"abstract":"Inflammatory bowel disease (IBD) is a chronic disease characterized by numerous, hard to predict periods of relapse and remission. \"Digital twin\" approaches, leveraging personalized predictive models, would significantly enhance therapeutic decision-making and cost-effectiveness. However, the associated computational and statistical methods require high quality data from a large population of patients. Such a comprehensive repository is very challenging to build, though, and none is available for IBD. To overcome this, a promising approach is to employ a knowledge graph, which is built from the available data and would help predicting IBD episodes and delivering more relevant personalized therapy at the lowest cost. In this research, we present a knowledge graph developed on the basis of patient records which are collected from one of the largest German gastroentologic outpatient clinic. First, we designed IBD ontology that encompasses the vocabulary, specifications and characteristics associated by physicians with IBD patients, such as disease classification schemas (e.g., Montreal Classification of IBD), status of the disease activity, and medications. Next, we defined the mappings between ontology entities and database variables. Physicians and project members participating in the Fraunhofer MED2ICIN project, validated the ontology and the knowledge graph. Furthermore, the knowledge graph has been validated against the competency questions compiled by physicians.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125717303","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}
To support sustainable in-home long-term care, it is essential to monitor mental states of elderly people at home, and to encourage their ability of self-care. However, many challenges exist in practice, including limitations of human interventions, sensor-based monitoring, the daily recording and externalization of mental states. In the previous research, we have proposed Mind Monitoring Service, which aims to monitor mental states and promote self-care of elderly people at home. In the proposed service, a chatbot asks a user specific questions to acquire his/her mental state. Based on the answers, the service assesses the mental state. In this research, we develop a new feature of weekly feedback. The feature automatically reviews answers of past one week, and sends advice to improve the current situation. We conduct an experiment to evaluate the effectiveness. Through the experiment, it was confirmed that the weekly feedback encouraged self-care consciousness and increased motivation of subjects.
{"title":"Implementing and Evaluating feedback feature of Mind Monitoring Service for Elderly People at Home","authors":"C. Miura, S. Saiki, Masahide Nakamura, K. Yasuda","doi":"10.1145/3428757.3429124","DOIUrl":"https://doi.org/10.1145/3428757.3429124","url":null,"abstract":"To support sustainable in-home long-term care, it is essential to monitor mental states of elderly people at home, and to encourage their ability of self-care. However, many challenges exist in practice, including limitations of human interventions, sensor-based monitoring, the daily recording and externalization of mental states. In the previous research, we have proposed Mind Monitoring Service, which aims to monitor mental states and promote self-care of elderly people at home. In the proposed service, a chatbot asks a user specific questions to acquire his/her mental state. Based on the answers, the service assesses the mental state. In this research, we develop a new feature of weekly feedback. The feature automatically reviews answers of past one week, and sends advice to improve the current situation. We conduct an experiment to evaluate the effectiveness. Through the experiment, it was confirmed that the weekly feedback encouraged self-care consciousness and increased motivation of subjects.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116279122","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}
Bernhard Göschlberger, Fabian Dopler, Christoph Brandstetter
Digital learning resources are becoming increasingly important, especially in times of COVID-19 home schooling. To align resources with educational objectives defined in school curricula, we need ways to describe and relate them. In this work, we present a new data model, a data management workflow and a prototypical information system enabling annotators to describe learning resources using the terminology and structure, while maintaining applicability in other contexts through transcription. Preliminary evaluation results with metadata curators show that our model is well-suited to efficiently model secondary education curricula. Provided that future evaluations with content creators, teachers and learners yield positive results, our model may enable curriculum specific learning analytics, search and recommendation without the need to annotate resources for each curriculum.
{"title":"Managing Learning Resource Metadata for Secondary Education","authors":"Bernhard Göschlberger, Fabian Dopler, Christoph Brandstetter","doi":"10.1145/3428757.3429148","DOIUrl":"https://doi.org/10.1145/3428757.3429148","url":null,"abstract":"Digital learning resources are becoming increasingly important, especially in times of COVID-19 home schooling. To align resources with educational objectives defined in school curricula, we need ways to describe and relate them. In this work, we present a new data model, a data management workflow and a prototypical information system enabling annotators to describe learning resources using the terminology and structure, while maintaining applicability in other contexts through transcription. Preliminary evaluation results with metadata curators show that our model is well-suited to efficiently model secondary education curricula. Provided that future evaluations with content creators, teachers and learners yield positive results, our model may enable curriculum specific learning analytics, search and recommendation without the need to annotate resources for each curriculum.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951623","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}
Christian Dienbauer, Benedikt Pittl, W. Mach, E. Schikuta
Today, traded cloud services are described by service level agreements that specify the obligations of providers such as availability or reliability. Violations of service level agreements lead to penalty payments. The recent development of prominent cloud platforms such as the re-design of Amazon's spot marketspace underpins a trend towards dynamic cloud markets where consumers migrate their services continuously to different marketspaces and providers to reach a cost-optimum. This leads to a heterogeneous IT infrastructure and consequently aggravates the monitoring of the delivered service quality. Hence, there is a need for a transparent penalty management system, which ensures that consumers automatically get penalty payments from providers in case of service violations. In the paper at hand, we present a cloud monitoring system that is able to execute penalty payments autonomously. In this regard, we revert to smart contracts hosted on blockchains. They continuously monitor cloud services and trigger penalty payments to consumers in case of service violations. We implemented the presented approach with the IBM Hyperledger Fabric framework and created a use case with Amazon's cloud services as well as Azures cloud services to illustrate the universal design of the introduced approach.
{"title":"A Penalty-Aware Cloud Monitoring System based on Blockchains","authors":"Christian Dienbauer, Benedikt Pittl, W. Mach, E. Schikuta","doi":"10.1145/3428757.3429130","DOIUrl":"https://doi.org/10.1145/3428757.3429130","url":null,"abstract":"Today, traded cloud services are described by service level agreements that specify the obligations of providers such as availability or reliability. Violations of service level agreements lead to penalty payments. The recent development of prominent cloud platforms such as the re-design of Amazon's spot marketspace underpins a trend towards dynamic cloud markets where consumers migrate their services continuously to different marketspaces and providers to reach a cost-optimum. This leads to a heterogeneous IT infrastructure and consequently aggravates the monitoring of the delivered service quality. Hence, there is a need for a transparent penalty management system, which ensures that consumers automatically get penalty payments from providers in case of service violations. In the paper at hand, we present a cloud monitoring system that is able to execute penalty payments autonomously. In this regard, we revert to smart contracts hosted on blockchains. They continuously monitor cloud services and trigger penalty payments to consumers in case of service violations. We implemented the presented approach with the IBM Hyperledger Fabric framework and created a use case with Amazon's cloud services as well as Azures cloud services to illustrate the universal design of the introduced approach.","PeriodicalId":212557,"journal":{"name":"Proceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116935607","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}
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