Towards Querying in Decentralized Environments with Privacy-Preserving Aggregation

The Web is a ubiquitous economic, educational, and collaborative space. However, it also serves as a haven for personal information harvesting. Existing decentralised Web-based ecosystems, such as Solid, aim to combat personal data exploitation on the Web by enabling individuals to manage their data in the personal data store of their choice. Since personal data in these decentralised ecosystems are distributed across many sources, there is a need for techniques to support efficient privacy-preserving query execution over personal data stores. Towards this end, in this position paper we present a framework for efficient privacy preserving federated querying, and highlight open research challenges and opportunities. The overarching goal being to provide a means to position future research into privacy-preserving querying within decentralised environments

Legislative Compliance Assessment: Framework, Model and GDPR Instantiation

Legislative compliance assessment tools are commonly used by companies to help them to understand their legal obligations. One of the primary limitations of existing tools is that they tend to consider each regulation in isolation. In this paper, we propose a flexible and modular compliance assessment framework that can support multiple legislations. Additionally, we describe our extension of the Open Digital Rights Language (ODRL) so that it can be used not only to represent digital rights but also legislative obligations, and discuss how the proposed model is used to develop a flexible compliance system, where changes to the obligations are automatically reflected in the compliance assessment tool. Finally, we demonstrate the effectiveness of the proposed approach through the development of a General Data Protection Regulatory model and compliance assessment too

HDT crypt: Compression and Encryption of RDF Datasets

The publication and interchange of RDF datasets online has experienced significant growth in recent years, promoted by different but complementary efforts, such as Linked Open Data, the Web of Things and RDF stream processing systems. However, the current Linked Data infrastructure does not cater for the storage and exchange of sensitive or private data. On the one hand, data publishers need means to limit access to confidential data (e.g. health, financial, personal, or other sensitive data). On the other hand, the infrastructure needs to compress RDF graphs in a manner that minimises the amount of data that is both stored and transferred over the wire. In this paper, we demonstrate how HDT - a compressed serialization format for RDF - can be extended to cater for supporting encryption. We propose a number of different graph partitioning strategies and discuss the benefits and tradeoffs of each approach

Resource Utilization Prediction in Decision-Intensive Business Processes

An appropriate resource utilization is crucial for organizations in order to avoid, among other things, unnecessary costs (e.g. when resources are under-utilized) and too long execution times (e.g. due to excessive workloads, i.e. resource over-utilization). However, traditional process control and risk measurement approaches do not address resource utilization in processes. We studied an often-encountered industry case for providing large-scale technical infrastructure which requires rigorous testing for the systems deployed and identi ed the need of projecting resource utilization as a means for measuring the risk of resource underand over-utilization. Consequently, this paper presents a novel predictive model for resource utilization in decision-intensive processes, present in many domains. In particular, we predict the utilization of resources for a desired period of time given a decision-intensive business process that may include nested loops, and historical data (i.e. order and duration of past activity executions, resource pro les and their experience etc.). We have applied our method using a real business process with multiple instances and presented the outcome.Austrian Research Promotion Agency (FFG) 845638 (SHAPE)Austrian Science Fund (FWF) V 569-N31 (PRAIS

SHAPEworks: A BPMS Extension for Complex Process Management

Abstract. Complex engineering projects, such as the deployment of a railway infrastructure or the installation of an interlocking system, involve human safety and make use of heterogeneous data sources, as well as customized engineering tools. These processes are currently carried out in an ad-hoc fashion, relying on the experience of experts who need to plan, control, and monitor the execution of processes for delivering value to the customers. This setting makes an automated overarching-process a crucial step towards supporting engineers and project managers to deal with safety-critical constraints and the plethora of details entailed by the process. This paper demonstrates a tool that combines methods from automatic reasoning, ontologies and process mining, implemented on top of a real Business Process Management System (BPMS)

Towards an Alternative Approach for Combining Ontology Matchers

Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. SpracheDas standardisierte Ontology Alignment Format der Ontology Alignment Evaluation Initiative (OAEI) erlaubt es, verschiedene Ontology Matcher zu kombinieren, um deren Stärken auszunutzen und Schwächen kompensieren zu können. In der vorliegenden Diplomarbeit präsentieren wir einen neuen Ansatz, um verschiedene, existierende Ontology Matcher zu kombinieren. Dafür werden iterative Aufrufe dieser Matcher getätigt und zusätzlich Wissen in Form von Reference Alignments ausgetauscht. Da jedoch nur eine kleine Teilmenge der verfügbaren Matcher Reference Alignments direkt untersfützt, stellen wir einen alternativen Ansatz für den Import und die Verwendung von zusätzlichem Wissen in Form von Reference Alignments vor: Basierend auf der Ersetzung von URIs von Entitäten, für welche ein Alignment gefunden wurde, ist es möglich Reference Alignments zu "emulieren". Obwohl einige Matcher Entitäten mit der selben URI nicht als vollkommen ident betrachten, zeigen wir empirisch, dass unser interativer Ansatz der Matcher-Ausführung dennoch von solchen Ersetzungen profitiert, wobei wir in Teilen der OAEI Benchmark Tracks die besten Resultate im Vegleich mit bestehenden Ontologie-mapping Tools erreichen. Der resultierende neue Ontology Matcher Mix'n'Match integriert verschiedene Ontology Matcher in einer multi-threaded Architektur und bietet zudem die Möglichkeit den Mappingprozess jederzeit - mit den besten zurzeit gefundenen Ergebnissen - zu beenden.The existence of a standardized ontology alignment format promoted by the Ontology Alignment Evaluation Initiative (OAEI) potentially enables different ontology matchers to be combined and used together, exploiting their respective strengths in a combined matching approach. In the present thesis, we present a novel architecture for combining off-the-shelf ontology matchers based on iterative calls and exchanging information in the form of reference alignments. Unfortunately though, only a few of the matchers contesting in the past years- OAEI campaigns actually allow the provision of reference alignments in the standard OAEI alignment format to support such a combined mapping process. We bypass this lacking functionality by introducing an alternative approach for aligning results of different ontology matchers using simple URI replacement to "emulate" reference alignments in the aligned ontologies. While some matchers still consider classes and properties in ontologies aligned in such fashion as different, we experimentally prove that our iterative approach benefits from this emulation, achieving the best results in terms of F-measure on parts of the OAEI benchmark suite, compared to the single results of the competing matchers as well as their combined results. The new combined matcher - Mix'n'Match - integrates different matchers in a multi-threaded architecture and provides an anytime behavior in the sense that it can be stopped anytime with the best combined mappings found so far.10

A Framework for Safety-critical Process Management in Engineering Projects

Complex technical systems, industrial systems or infrastructure systems are rich of customizable features and raise high demands on quality and safety-critical aspects. To create complete, valid and reliable planning and customization process data for a product deployment, an overarching engineering process is crucial for the successful completion of a project. In this paper, we introduce a framework for process management in complex engineering projects which are subject to a large amount of constraints and make use of heterogeneous data sources. In addition, we propose solutions for the framework components and describe a proof-of-concept implementation of the framework as an extension of a well-known BPMS.Austrian Research Promotion Agency (FFG) 845638 (SHAPE

Multiple-Quantum-Well Nonlinear Coupler

NRC publication: Ye

18th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2019)

Managing privacy and understanding handling of personal data has turned into a fundamental right, at least within the European Union, with the General Data Protection Regulation (GDPR) being enforced since May 25th 2018. This has led to tools and services that promise compliance to GDPR in terms of consent management and keeping track of personal data being processed. The information recorded within such tools, as well as that for compliance itself, needs to be interoperable to provide sufficient transparency in its usage. Additionally, interoperability is also necessary towards addressing the right to data portability under GDPR as well as creation of user-configurable and manageable privacy policies. We argue that such interoperability can be enabled through agreement over vocabularies using linked data principles. The W3C Data Privacy Vocabulary and Controls Community Group (DPVCG) was set up to jointly develop such vocabularies towards interoperability in the context of data privacy. This paper presents the resulting Data Privacy Vocabulary (DPV), along with a discussion on its potential uses, and an invitation for feedback and participation