W3C Web Ontology Language (OWL) Experiences and Directions Workshop (OWLED), 2013
The process of translating end-users' information needs into executable and optimised queries ove... more The process of translating end-users' information needs into executable and optimised queries over the data is the main problem that end-users face in Big Data scenarios. In this paper we present the recently started EU project Optique, which advocates for a next generation of the well known Ontology-Based Data Access (OBDA) approach to address this problem. We discuss challenges, present ongoing work, and our current preliminary solutions with regards to the query formulation and query-driven ontology extension.
Abstract. In large companies such as Siemens and Statoil monitoring tasks are of great importance... more Abstract. In large companies such as Siemens and Statoil monitoring tasks are of great importance, e.g., Siemens does monitoring of turbines and Statoil of oil behaviour in wells. This tasks bring up importance of both streaming and historical (temporal) data in the Big Data challenge for industries. We present the Optique project that addresses this problem by developing an Ontology Based Data Access (OBDA) system that incorporates novel tools and methodologies for processing and analyses of temporal and streaming data. In particular, we advocate for modelling time time aware data by temporal RDF and reduce monitoring tasks to knowledge discovery and data mining. 1
Abstract. The following summary tries to capture a collection of state-of-the-art techniques and ... more Abstract. The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups—one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the “Explanation” working group report for more details on the first subgroup). 1 Why lineage? Users want lineage as a basic functionality of the database or information system they use. Explicitly tracing lineage information along with the actual results of queries may help users to better understand complex workflows or to analyze results in huge data warehouses that are often derived from complicated queries and many levels of materialized views. Lineage, as a form of annotation or metadata over the actual data, can provi...
The Optique project aims at providing an end-to-end solution for scalable Ontology-Based Data Acc... more The Optique project aims at providing an end-to-end solution for scalable Ontology-Based Data Access to Big Data integration, where end-users will formulate queries based on a familiar conceptualization of the underlying domain, that is, over an ontology. From user queries the Optique platform will automatically generate appropriate queries over the underlying integrated data, optimize and execute them. The key components in the Optique platform are the ontology and mappings that provide the relationships between the ontology and the underlying data. In this paper we discuss the problem of bootstrapping and maintenance of ontologies and mappings. The important challenge in both tasks is debugging errors in ontologies and mappings. We will present examples of different kinds of error, and give our preliminary view on their debugging.
Anomaly detection in sensor time series is a crucial aspect for raw data cleaning in gas turbine ... more Anomaly detection in sensor time series is a crucial aspect for raw data cleaning in gas turbine industry. In addition to efficiency, a successful methodology for industrial applications should be also characterized by ease of implementation and operation. To this purpose, a comprehensive and straightforward approach for Detection, Classification and Integrated Diagnostics of Gas Turbine Sensors (named DCIDS) is proposed in this paper. The tool consists of two main algorithms, i.e. the Anomaly Detection Algorithm (ADA) and the Anomaly Classification Algorithm (ACA). The ADA identifies anomalies according to three different levels of filtering based on gross physics threshold application, inter-sensor statistical analysis (sensor voting) and single-sensor statistical analysis. Anomalies in the time series are identified by the ADA, together with their characteristics, which are analyzed by the ACA to perform their classification. Fault classes discriminate among anomalies according to their time correlation, magnitude and number of sensors in which an anomaly is contemporarily identified. Results of anomaly identification and classification can subsequently be used for sensor diagnostic purposes. The performance of the tool is assessed in this paper by analyzing two temperature time series with redundant sensors taken on a Siemens gas turbine in operation. The results show that the DICDS is able to identify and classify different types of anomalies. In particular, in the first dataset, two severely incoherent sensors are identified and their anomalies are correctly classified. In the second dataset, the DCIDS tool proves to be capable of identifying and classifying clustered spikes of different magnitudes.
This report summarizes the findings of a working group on ”Uncertainty and Trust” which met durin... more This report summarizes the findings of a working group on ”Uncertainty and Trust” which met during Dagstuhl Seminar 08421 ”Uncertainty Management in Information Systems”. All participants of the working group are co-authors of this report. The aim of the working group was to analyse the relationship between trust and uncertainty in distributed reputation systems. We started by identifying sources and types of uncertainty in this context and investigated their relation to trust. After that we compiled a list of desirable properties of trust representations and finally determined open research challenges in the area.
This chapter reports on the practical results of our research. We first present an overview of th... more This chapter reports on the practical results of our research. We first present an overview of the RAbIT system, which we developed as library for solving relaxed abduction problems. RAbIT provides both a glass-box algorithm for \( {\mathcal{E}\mathcal{L}}^{ + } \) knowledge bases, and a black-box variant with a broader range of supported representation languages.
This report summarizes the findings of a working group on "Uncertainty and Trust" which... more This report summarizes the findings of a working group on "Uncertainty and Trust" which met during Dagstuhl Seminar 08421 "Uncertainty Management in Information Systems". All participants of the working group are co-authors of this report. The aim of the working group was to analyse the relationship between trust and uncertainty in distributed reputation systems. We started by identifying sources and types of uncertainty in this context and investigated their relation to trust. After that we compiled a list of desirable properties of trust representations and finally determined open research challenges in the area.
L'invention concerne un systeme et un procede de configuration concus pour realiser une confi... more L'invention concerne un systeme et un procede de configuration concus pour realiser une configuration ou une reconfiguration d'applications executees par un systeme d'automatisation, ledit systeme de configuration comprenant : une unite de traitement concue pour traiter au moins une instruction en langage naturel d'une entree d'exigence d'utilisateur par un utilisateur concernant une fonctionnalite de commande et/ou de surveillance du systeme d'automatisation sur la base d'une ontologie d'utilisateur de l'utilisateur et/ou d'une ontologie de systeme d'automatisation du systeme d'automatisation pour generer une specification d'exigences formelle ; et une unite de mise en correspondance concue pour faire correspondre la specification d'exigences formelle et des specifications de composant formelles lues a partir d'une bibliotheque de composants pour deriver un deploiement de configuration comprenant un ou plusieurs compos...
In large industries usage of advanced technological methods and modern equipment comes with the p... more In large industries usage of advanced technological methods and modern equipment comes with the problem of storing, interpreting and analyzing huge amount of information. Handling information becomes more complicated and important at the same time. So, data quality is one of major challenges considering a rapid growth of information, fragmentation of information systems, incorrect data formatting and other issues. The aim of this paper is to describe industrial data processing and analytics on the realworld use case. The most crucial data quality issues are described, examined and classified in terms of Data Quality Dimensions. Factual industrial information supports and illustrates each encountered data deficiency. In addition, we describe methods for elimination data quality issues and data analysis techniques, which are applied after cleaning data procedure. In addition, an approach to address data quality problems in large-scale industrial datasets is proposed. This techniques a...
Abductive reasoning has been recognized as a valuable com- plement to deductive inference for tas... more Abductive reasoning has been recognized as a valuable com- plement to deductive inference for tasks such as diagnosis and integration of incomplete information despite its inherent computational complex- ity. This paper presents a novel, tractable abduction procedure for the lightweight description logic EL. The proposed approach extends recent research on automata-based axiom pinpointing (which is in some sense dual to our problem) by assuming information from a predefined ab- ducible part of the domain model if necessary, while the remainder of the domain is considered to be fixed. Our research is motivated by the need for efficient diagnostic reasoning for large-scale industrial systems where observations are partially incomplete and often sparse, but nevertheless the largest part of the domain such as physical structures is known. Tech- nically, we introduce a novel pattern-based definition of abducibles and show how to construct a weighted automaton that commonly encodes the de...
The following summary tries to capture a collection of state-of-the-art techniques and challenges... more The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups---one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the "Explanation" working group report for more details on the first subgroup).
Rettungsleitsystem (1), das automatisiert ohne Zwischenschaltung handischer Zuordnungsprozesse de... more Rettungsleitsystem (1), das automatisiert ohne Zwischenschaltung handischer Zuordnungsprozesse den Einsatzkraften eines Einsatzfahzeugs (2) das beste Zielkrankenhaus fur den geladenen Verletzten bzw. Patienten angibt. Das Rettungsleitsystem (1) hat eine Leistelleneinrichtung (3), welche Bereitschaftsparameter (BP1-BP4) von mehreren Krankenhausern (4-7) empfangt und Krankenhausprofile (KP1-KP4) erstellt und mindestens eine, in einem Rettungsfahrzeug (2) vorgesehene, mobile Digitalfunkeinrichtung (12), welche in Abhangigkeit von Einsatzparametern (EP1-EP4) ein Anforderungsprofil (AP) erstellt und an die Leitstelleneinrichtung (3) ubermittelt. Dabei vergleicht die Digitalfunkeinrichtung (2) oder die Leitstelleneinrichtung (3) das Anforderungsprofil (AP) mit den Krankenhausprofilen (KP1-KP4) und stellt eine geordnete Zielliste (ZL) mit geeigneten Zielkrankenhausern bereit. Rettungseinsatze, beispielsweise von Krankenwagen (2) in Wohngebieten mit vielen potenziellen Krankenhausern (4-7),...
Many industrial use cases, such as machine diagnostics, can benefit from embedded reasoning, the ... more Many industrial use cases, such as machine diagnostics, can benefit from embedded reasoning, the task of running knowledge-based reasoning techniques on embedded controllers as widely used in industrial automation. However, due to the memory and CPU restrictions of embedded devices like programmable logic controllers (PLCs), state-ofthe-art reasoning tools and methods cannot be easily migrated to industrial automation environments. In this paper, we describe an approach to porting lightweight OWL 2 EL reasoning to a PLC platform to run in an industrial automation environment. We report on initial runtime experiments carried out on a prototypical implementation of a PLC-based EL-reasoner in the context of a use case about turbine diagnostics.
The following summary tries to capture a collection of state-of-the-art techniques and challenges... more The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups—one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the “Explanation” working group report for more details on the first subgroup).
The Industrial Knowledge Graph has become an integral elements in Siemens’ digitalization strateg... more The Industrial Knowledge Graph has become an integral elements in Siemens’ digitalization strategy towards integlligent engineering and manufacturing. In the presentation, we will share details on how semantic technologies are used in Industrial Knowledge Graph use cases and generate business value in real-world applications. Siemens is building an intelligent knowledge hub that can support knowledgedriven applications across the company, and serve as a smart knowledge factory generating new knowledge. Towards this end, we are creating an industrial knowledge graph as an intelligible domain model to support the easy integration of multiple data sources and to provide a formal semantic representation to enable inference and machine processing. The path towards this goal involves four major steps: First, we extend single data silos with domain-specific models for many use cases, knowledge graphs can already generate value on this level, for instance by facilitating information access ...
The invention relates to a method for computer-assisted analysis of an object. Subobject any obje... more The invention relates to a method for computer-assisted analysis of an object. Subobject any object or living organisms are to be understood here, and the method can be used in any technical fields, for example in the fields of medicine, security, traffic engineering, and the like. With the inventive method, the information is collected to the object for a plurality of consecutive times or periods of sensor means. Subsequently, it is determined based on the individual time points or time periods a status or situation description of the object with a first method of analysis, are preferably used for this process on an ontology-based inference methods using Reasonern. The state of the object descriptions in turn then form the input variables for a second analysis method by which a temporal behavior description of the object is determined. This second analysis method is preferably also used based inference process on an ontology. The combination of two analysis methods can inventively ...
Product sensor (103) for a product (102) in a system (101) transportable, manufactured or machine... more Product sensor (103) for a product (102) in a system (101) transportable, manufactured or machined with - a processing unit (104) for providing measured data (MD) or any derivative data (d) to the system, - in which the product sensor is integrated in the product or in a carrier material for the product, - wherein based on the processing unit (104) a symptom (201) can be determined based on the measured data (202) or the data derived therefrom (202) - wherein on the basis of the symptom (201, 203), a diagnosis (205) for the plant (101) is determined based on at least one assumption - wherein the diagnosis is determined by a situation analysis function which determines a plausibility measure for the diagnosis, said threshold values are dependent on both automated reactions and interactions of the operator abuttable.
This paper introduces relaxed abduction, a novel non-standard reasoning task for description logi... more This paper introduces relaxed abduction, a novel non-standard reasoning task for description logics. Although abductive reasoning over description logic knowledge bases has been applied successfully to various information interpretation tasks, it typically fails to provide adequate (or even any) results when confronted with spurious information or incomplete models. Relaxed abduction addresses this flaw by ignoring such pieces of information automatically based on a joint optimization of the sets of explained observations and required assumptions. We present a method to solve relaxed abduction over EL TBoxes based on the notion of multi-criterion shortest hyperpaths.
The process of translating end-users’ information needs into executable and optimised queries ove... more The process of translating end-users’ information needs into executable and optimised queries over the data is the main problem that end-users face in Big Data scenarios. In this paper we present the recently started EU project Optique, which advocates for a next generation of the well known Ontology-Based Data Access (OBDA) approach to address this problem. We discuss challenges, present ongoing work, and our current preliminary solutions with regards to the query formulation and query-driven ontology extension.
W3C Web Ontology Language (OWL) Experiences and Directions Workshop (OWLED), 2013
The process of translating end-users' information needs into executable and optimised queries ove... more The process of translating end-users' information needs into executable and optimised queries over the data is the main problem that end-users face in Big Data scenarios. In this paper we present the recently started EU project Optique, which advocates for a next generation of the well known Ontology-Based Data Access (OBDA) approach to address this problem. We discuss challenges, present ongoing work, and our current preliminary solutions with regards to the query formulation and query-driven ontology extension.
Abstract. In large companies such as Siemens and Statoil monitoring tasks are of great importance... more Abstract. In large companies such as Siemens and Statoil monitoring tasks are of great importance, e.g., Siemens does monitoring of turbines and Statoil of oil behaviour in wells. This tasks bring up importance of both streaming and historical (temporal) data in the Big Data challenge for industries. We present the Optique project that addresses this problem by developing an Ontology Based Data Access (OBDA) system that incorporates novel tools and methodologies for processing and analyses of temporal and streaming data. In particular, we advocate for modelling time time aware data by temporal RDF and reduce monitoring tasks to knowledge discovery and data mining. 1
Abstract. The following summary tries to capture a collection of state-of-the-art techniques and ... more Abstract. The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups—one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the “Explanation” working group report for more details on the first subgroup). 1 Why lineage? Users want lineage as a basic functionality of the database or information system they use. Explicitly tracing lineage information along with the actual results of queries may help users to better understand complex workflows or to analyze results in huge data warehouses that are often derived from complicated queries and many levels of materialized views. Lineage, as a form of annotation or metadata over the actual data, can provi...
The Optique project aims at providing an end-to-end solution for scalable Ontology-Based Data Acc... more The Optique project aims at providing an end-to-end solution for scalable Ontology-Based Data Access to Big Data integration, where end-users will formulate queries based on a familiar conceptualization of the underlying domain, that is, over an ontology. From user queries the Optique platform will automatically generate appropriate queries over the underlying integrated data, optimize and execute them. The key components in the Optique platform are the ontology and mappings that provide the relationships between the ontology and the underlying data. In this paper we discuss the problem of bootstrapping and maintenance of ontologies and mappings. The important challenge in both tasks is debugging errors in ontologies and mappings. We will present examples of different kinds of error, and give our preliminary view on their debugging.
Anomaly detection in sensor time series is a crucial aspect for raw data cleaning in gas turbine ... more Anomaly detection in sensor time series is a crucial aspect for raw data cleaning in gas turbine industry. In addition to efficiency, a successful methodology for industrial applications should be also characterized by ease of implementation and operation. To this purpose, a comprehensive and straightforward approach for Detection, Classification and Integrated Diagnostics of Gas Turbine Sensors (named DCIDS) is proposed in this paper. The tool consists of two main algorithms, i.e. the Anomaly Detection Algorithm (ADA) and the Anomaly Classification Algorithm (ACA). The ADA identifies anomalies according to three different levels of filtering based on gross physics threshold application, inter-sensor statistical analysis (sensor voting) and single-sensor statistical analysis. Anomalies in the time series are identified by the ADA, together with their characteristics, which are analyzed by the ACA to perform their classification. Fault classes discriminate among anomalies according to their time correlation, magnitude and number of sensors in which an anomaly is contemporarily identified. Results of anomaly identification and classification can subsequently be used for sensor diagnostic purposes. The performance of the tool is assessed in this paper by analyzing two temperature time series with redundant sensors taken on a Siemens gas turbine in operation. The results show that the DICDS is able to identify and classify different types of anomalies. In particular, in the first dataset, two severely incoherent sensors are identified and their anomalies are correctly classified. In the second dataset, the DCIDS tool proves to be capable of identifying and classifying clustered spikes of different magnitudes.
This report summarizes the findings of a working group on ”Uncertainty and Trust” which met durin... more This report summarizes the findings of a working group on ”Uncertainty and Trust” which met during Dagstuhl Seminar 08421 ”Uncertainty Management in Information Systems”. All participants of the working group are co-authors of this report. The aim of the working group was to analyse the relationship between trust and uncertainty in distributed reputation systems. We started by identifying sources and types of uncertainty in this context and investigated their relation to trust. After that we compiled a list of desirable properties of trust representations and finally determined open research challenges in the area.
This chapter reports on the practical results of our research. We first present an overview of th... more This chapter reports on the practical results of our research. We first present an overview of the RAbIT system, which we developed as library for solving relaxed abduction problems. RAbIT provides both a glass-box algorithm for \( {\mathcal{E}\mathcal{L}}^{ + } \) knowledge bases, and a black-box variant with a broader range of supported representation languages.
This report summarizes the findings of a working group on "Uncertainty and Trust" which... more This report summarizes the findings of a working group on "Uncertainty and Trust" which met during Dagstuhl Seminar 08421 "Uncertainty Management in Information Systems". All participants of the working group are co-authors of this report. The aim of the working group was to analyse the relationship between trust and uncertainty in distributed reputation systems. We started by identifying sources and types of uncertainty in this context and investigated their relation to trust. After that we compiled a list of desirable properties of trust representations and finally determined open research challenges in the area.
L'invention concerne un systeme et un procede de configuration concus pour realiser une confi... more L'invention concerne un systeme et un procede de configuration concus pour realiser une configuration ou une reconfiguration d'applications executees par un systeme d'automatisation, ledit systeme de configuration comprenant : une unite de traitement concue pour traiter au moins une instruction en langage naturel d'une entree d'exigence d'utilisateur par un utilisateur concernant une fonctionnalite de commande et/ou de surveillance du systeme d'automatisation sur la base d'une ontologie d'utilisateur de l'utilisateur et/ou d'une ontologie de systeme d'automatisation du systeme d'automatisation pour generer une specification d'exigences formelle ; et une unite de mise en correspondance concue pour faire correspondre la specification d'exigences formelle et des specifications de composant formelles lues a partir d'une bibliotheque de composants pour deriver un deploiement de configuration comprenant un ou plusieurs compos...
In large industries usage of advanced technological methods and modern equipment comes with the p... more In large industries usage of advanced technological methods and modern equipment comes with the problem of storing, interpreting and analyzing huge amount of information. Handling information becomes more complicated and important at the same time. So, data quality is one of major challenges considering a rapid growth of information, fragmentation of information systems, incorrect data formatting and other issues. The aim of this paper is to describe industrial data processing and analytics on the realworld use case. The most crucial data quality issues are described, examined and classified in terms of Data Quality Dimensions. Factual industrial information supports and illustrates each encountered data deficiency. In addition, we describe methods for elimination data quality issues and data analysis techniques, which are applied after cleaning data procedure. In addition, an approach to address data quality problems in large-scale industrial datasets is proposed. This techniques a...
Abductive reasoning has been recognized as a valuable com- plement to deductive inference for tas... more Abductive reasoning has been recognized as a valuable com- plement to deductive inference for tasks such as diagnosis and integration of incomplete information despite its inherent computational complex- ity. This paper presents a novel, tractable abduction procedure for the lightweight description logic EL. The proposed approach extends recent research on automata-based axiom pinpointing (which is in some sense dual to our problem) by assuming information from a predefined ab- ducible part of the domain model if necessary, while the remainder of the domain is considered to be fixed. Our research is motivated by the need for efficient diagnostic reasoning for large-scale industrial systems where observations are partially incomplete and often sparse, but nevertheless the largest part of the domain such as physical structures is known. Tech- nically, we introduce a novel pattern-based definition of abducibles and show how to construct a weighted automaton that commonly encodes the de...
The following summary tries to capture a collection of state-of-the-art techniques and challenges... more The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups---one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the "Explanation" working group report for more details on the first subgroup).
Rettungsleitsystem (1), das automatisiert ohne Zwischenschaltung handischer Zuordnungsprozesse de... more Rettungsleitsystem (1), das automatisiert ohne Zwischenschaltung handischer Zuordnungsprozesse den Einsatzkraften eines Einsatzfahzeugs (2) das beste Zielkrankenhaus fur den geladenen Verletzten bzw. Patienten angibt. Das Rettungsleitsystem (1) hat eine Leistelleneinrichtung (3), welche Bereitschaftsparameter (BP1-BP4) von mehreren Krankenhausern (4-7) empfangt und Krankenhausprofile (KP1-KP4) erstellt und mindestens eine, in einem Rettungsfahrzeug (2) vorgesehene, mobile Digitalfunkeinrichtung (12), welche in Abhangigkeit von Einsatzparametern (EP1-EP4) ein Anforderungsprofil (AP) erstellt und an die Leitstelleneinrichtung (3) ubermittelt. Dabei vergleicht die Digitalfunkeinrichtung (2) oder die Leitstelleneinrichtung (3) das Anforderungsprofil (AP) mit den Krankenhausprofilen (KP1-KP4) und stellt eine geordnete Zielliste (ZL) mit geeigneten Zielkrankenhausern bereit. Rettungseinsatze, beispielsweise von Krankenwagen (2) in Wohngebieten mit vielen potenziellen Krankenhausern (4-7),...
Many industrial use cases, such as machine diagnostics, can benefit from embedded reasoning, the ... more Many industrial use cases, such as machine diagnostics, can benefit from embedded reasoning, the task of running knowledge-based reasoning techniques on embedded controllers as widely used in industrial automation. However, due to the memory and CPU restrictions of embedded devices like programmable logic controllers (PLCs), state-ofthe-art reasoning tools and methods cannot be easily migrated to industrial automation environments. In this paper, we describe an approach to porting lightweight OWL 2 EL reasoning to a PLC platform to run in an industrial automation environment. We report on initial runtime experiments carried out on a prototypical implementation of a PLC-based EL-reasoner in the context of a use case about turbine diagnostics.
The following summary tries to capture a collection of state-of-the-art techniques and challenges... more The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups—one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the “Explanation” working group report for more details on the first subgroup).
The Industrial Knowledge Graph has become an integral elements in Siemens’ digitalization strateg... more The Industrial Knowledge Graph has become an integral elements in Siemens’ digitalization strategy towards integlligent engineering and manufacturing. In the presentation, we will share details on how semantic technologies are used in Industrial Knowledge Graph use cases and generate business value in real-world applications. Siemens is building an intelligent knowledge hub that can support knowledgedriven applications across the company, and serve as a smart knowledge factory generating new knowledge. Towards this end, we are creating an industrial knowledge graph as an intelligible domain model to support the easy integration of multiple data sources and to provide a formal semantic representation to enable inference and machine processing. The path towards this goal involves four major steps: First, we extend single data silos with domain-specific models for many use cases, knowledge graphs can already generate value on this level, for instance by facilitating information access ...
The invention relates to a method for computer-assisted analysis of an object. Subobject any obje... more The invention relates to a method for computer-assisted analysis of an object. Subobject any object or living organisms are to be understood here, and the method can be used in any technical fields, for example in the fields of medicine, security, traffic engineering, and the like. With the inventive method, the information is collected to the object for a plurality of consecutive times or periods of sensor means. Subsequently, it is determined based on the individual time points or time periods a status or situation description of the object with a first method of analysis, are preferably used for this process on an ontology-based inference methods using Reasonern. The state of the object descriptions in turn then form the input variables for a second analysis method by which a temporal behavior description of the object is determined. This second analysis method is preferably also used based inference process on an ontology. The combination of two analysis methods can inventively ...
Product sensor (103) for a product (102) in a system (101) transportable, manufactured or machine... more Product sensor (103) for a product (102) in a system (101) transportable, manufactured or machined with - a processing unit (104) for providing measured data (MD) or any derivative data (d) to the system, - in which the product sensor is integrated in the product or in a carrier material for the product, - wherein based on the processing unit (104) a symptom (201) can be determined based on the measured data (202) or the data derived therefrom (202) - wherein on the basis of the symptom (201, 203), a diagnosis (205) for the plant (101) is determined based on at least one assumption - wherein the diagnosis is determined by a situation analysis function which determines a plausibility measure for the diagnosis, said threshold values are dependent on both automated reactions and interactions of the operator abuttable.
This paper introduces relaxed abduction, a novel non-standard reasoning task for description logi... more This paper introduces relaxed abduction, a novel non-standard reasoning task for description logics. Although abductive reasoning over description logic knowledge bases has been applied successfully to various information interpretation tasks, it typically fails to provide adequate (or even any) results when confronted with spurious information or incomplete models. Relaxed abduction addresses this flaw by ignoring such pieces of information automatically based on a joint optimization of the sets of explained observations and required assumptions. We present a method to solve relaxed abduction over EL TBoxes based on the notion of multi-criterion shortest hyperpaths.
The process of translating end-users’ information needs into executable and optimised queries ove... more The process of translating end-users’ information needs into executable and optimised queries over the data is the main problem that end-users face in Big Data scenarios. In this paper we present the recently started EU project Optique, which advocates for a next generation of the well known Ontology-Based Data Access (OBDA) approach to address this problem. We discuss challenges, present ongoing work, and our current preliminary solutions with regards to the query formulation and query-driven ontology extension.
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Papers by Thomas Hubauer