Hur kan RDF-processen hos Alwex Recycling AB illustreras? Vilket slöseri finns i RDF-processen; innan, under och efter förädlingen? Hur kan de identifierade slöserierna reduceras? Hur mycket kan Alwex Recycling AB:s kostnader reduceras genom att reducera de identifierade slöserierna? Sverige förbränner en del avfall som går till bland annat fjärrvärme. Refuse derived fuel (RDF) är ett avfall bestående av bland annat plast och papper. RDF har ett högt värmevärde, problemet är att det är svårt att få en RDF-process att bli lönsam. Alwex Recycling AB förädlar RDF och har, som andra RDF-anläggningar, problem med att få verksamheten lönsam. Marknaden där RDF köps och säljs är väldigt komplex då företag får betalt för att ta hand om avfallet som sedan förädlas och som företaget sedan måste betala för att bli av med. Uppsatsens syfte är att kartlägga RDF-processen hos Alwex Recycling AB och identifiera slöseri, för att ge förslag på hur dessa kan reduceras för att på så sätt minska Alwex Recycling AB:s produktionskostnader. För att uppfylla uppsatsens syfte har författarna utgått ifrån ett kvalitativt synsätt och gjort en fallstudie på Alwex Recycling AB. Personalen på anläggningen har intervjuats i fokusgrupper samt intervjuer med viss personal för att få fram empirisk data. Observationer har även gjorts på anläggningen för att komplettera intervjuerna. I uppsatsen har författarna kartlagt processen som den ser ut idag och identifierat de slöserier som uppstår i processen. Förbättringsförslag och kostnadsberäkningar har analyserats och kalkylerats för vissa av dessa slöserier. Anläggningen anses av författarna kunna ge en generell beskrivning av en RDF-process, detta gör att förbättringsförslagen bör kunna användas på andra liknande anläggningar i en svensk kontext. / How can the RDF-process in Alwex Recycling AB be illustrated? What wastes are identified by the RDF-process; before, during and after the refining process? How can the identified waste be reduced? How much can Alwex Recycling AB’s cost be reduced by reducing the identified waste? Sweden incinerate part of their waste and a part of this particular waste is used for district heating. Refuse derived fuel (RDF) is a fuel refined from waste partly containing of plastic and paper. RDF has a high calorific value. The problem regarding the RDF material is that it is difficult to get an RDF process to become profitable. Alwex Recycling AB refines RDF and has, like other RDF plants, problems in getting the business profitable. The market where the RDF is bought and sold is complex. Companies get paid to take care of the waste. After processing the material the company has to pay to get rid of the RDF. The purpose of this paper is to map the RDF process of Alwex Recycling AB and identify non-value added wastes. Suggestions to reduce the identified wastes and reduce Alwex Recycling AB's production costs are presented. To fulfill the purpose of the paper, the authors adopted an qualitative approach and performed a single case study on Alwex Recycling AB. The staff at the facility were interviewed in focus groups and individual interviews. Additionally, observations were made at the RDF-plant to complement empirical data collected from the interviews. In this paper, the authors have mapped the present RDF-process and identified non-value added wastes. Proposals of improvements and cost estimates are analyzed in some of the identified wastes. The RDF process at Alwex Recycling AB is considered to be of general application, therefore improvement proposals can be adopted to similar RDF-plants in Sweden.

Title: Tool for NDL Author: Elena Myazina Department: Department of Software Engineering Supervisor: Doc. Ing. Karel Richta, CSc. Supervisor's Supervisor's e-mail address: richta@ksi.ms.mff.cuni.cz Abstrakt: -Current research networks allow end users to build their own application-specific connections (lightpaths) and Optical Private Networks (OPNs). This requires a clear communication between the requesting application and the network. The Network Description Language (NDL) is a vocabulary designed to describe optical networks based on the Resource Description Framework (RDF). These descriptions aid applications in querying the capabilities of the network and allow them to clearly express requests to the network. This work deals with the analysis of the current draft language NDL systems and optical components. He compares its potential and shortcomings of the proposal seeks. It also proposes a graphical representation corresponding to that language, which implements the graphical tool. The developed tool will allow the subsequent dialogs (voice) applications. Key words: NDL, RDF, optical mapping technology.

The fast evolution of the World Wide Web has offered the possibility to publish a huge amount of linked documents. Each such document represents a valuable piece of information. Linked Data is the term used to describe a method of exposing and connecting such documents. Even if this method is still in an experimental phase, it is already hard to process all existing data sources and the most obvious solution is to try and index them. The study addresses questions on how to design an index that will be capable to operate with millions of such entries. It analyses the existing projects and describes an index that may fulfill the requirements. The prototype implementation and the provided test results offer additional information about the index structure and effectiveness.

Resource Description Framework (RDF) is a modern graph database model which has a proposed extension called RDF*. However, currently there are no tools available that allow for transitions between RDF and RDF*. In this thesis tools were developed that allow for conversions between these two formats. A conversion tool for transforming RDF’s associated query language SPARQL into SPARQL* was also made. Furthermore, tools for converting between RDF* and another graph database model called Property Graph were developed. Measurements of the memory usage and conversion times for the developed conversion tools were made. Where possible, tests were also performed to control that there was no data loss in the conversions. The results showed varying memory usage and conversion times for the different conversions and that some conversions were very difficult to check for data corruption. Complex testing tools would be required to make sure all conversions are made correctly.

No description available.

Ontological engineering utilizes ontologies for various purposes across the spectrum. Just as onotlogies are being used in healthcare, researchers are also developing ontologies for unmanned aerial systems (UAS). A specific ontology domain has been created laying out various aspects of counter unmanned aerial systems (cUAS), known as the “UAS Integration Safety and Security Technology Ontology” (ISSTO). Counter unmanned aerial systems are a collection of technologies and systems that detect, track, identify, and mitigate unmanned aerial systems. ISSTO represents a compilation of classes that encompass UAS and cUAS components. The classes within ISSTO include aircraft types, weather, sensors, UAS air traffic management, and the National Airspace System (NAS). To effectively utilize the ISSTO ontology, UAS pilots and or policymakers require an innovative parsing method to extract the specific information they seek. This methodology makes use of ontology querying and natural language processing methods. By using user input, SPARQL queries are built dynamically by the parsing method. It utilizes synonym expansion and a scoring mechanism that prioritizes results by relevance using label matches, class matches, and annotation keyword matches.

The Web of Data has grown enormously over the last years. Currently, it comprises a large compendium of linked and distributed datasets from multiple domains. Due to the decentralised architecture of the Web of Data, several of these datasets contain complementary data. Running complex queries on this compendium thus often requires accessing data from different data sources within one query. The abundance of datasets and the need for running complex query has thus motivated a considerable body of work on SPARQL query federation systems, the dedicated means to access data distributed over the Web of Data. This thesis addresses two key areas of federated SPARQL query processing: (1) efficient source selection, and (2) comprehensive SPARQL benchmarks to test and ranked federated SPARQL engines as well as triple stores. Efficient Source Selection: Efficient source selection is one of the most important optimization steps in federated SPARQL query processing. An overestimation of query relevant data sources increases the network traffic, result in irrelevant intermediate results, and can significantly affect the overall query processing time. Previous works have focused on generating optimized query execution plans for fast result retrieval. However, devising source selection approaches beyond triple pattern-wise source selection has not received much attention. Similarly, only little attention has been paid to the effect of duplicated data on federated querying. This thesis presents HiBISCuS and TBSS, novel hypergraph-based source selection approaches, and DAW, a duplicate-aware source selection approach to federated querying over the Web of Data. Each of these approaches can be combined directly with existing SPARQL query federation engines to achieve the same recall while querying fewer data sources. We combined the three (HiBISCuS, DAW, and TBSS) source selections approaches with query rewriting to form a complete SPARQL query federation engine named Quetsal. Furthermore, we present TopFed, a Cancer Genome Atlas (TCGA) tailored federated query processing engine that exploits the data distribution to perform intelligent source selection while querying over large TCGA SPARQL endpoints. Finally, we address the issue of rights managements and privacy while accessing sensitive resources. To this end, we present SAFE: a global source selection approach that enables decentralised, policy-aware access to sensitive clinical information represented as distributed RDF Data Cubes. Comprehensive SPARQL Benchmarks: Benchmarking is indispensable when aiming to assess technologies with respect to their suitability for given tasks. While several benchmarks and benchmark generation frameworks have been developed to evaluate federated SPARQL engines and triple stores, they mostly provide a one-fits-all solution to the benchmarking problem. This approach to benchmarking is however unsuitable to evaluate the performance of a triple store for a given application with particular requirements. The fitness of current SPARQL query federation approaches for real applications is difficult to evaluate with current benchmarks as current benchmarks are either synthetic or too small in size and complexity. Furthermore, state-of-the-art federated SPARQL benchmarks mostly focused on a single performance criterion, i.e., the overall query runtime. Thus, they cannot provide a fine-grained evaluation of the systems. We address these drawbacks by presenting FEASIBLE, an automatic approach for the generation of benchmarks out of the query history of applications, i.e., query logs and LargeRDFBench, a billion-triple benchmark for SPARQL query federation which encompasses real data as well as real queries pertaining to real bio-medical use cases. Our evaluation results show that HiBISCuS, TBSS, TopFed, DAW, and SAFE all can significantly reduce the total number of sources selected and thus improve the overall query performance. In particular, TBSS is the first source selection approach to remain under 5% overall relevant sources overestimation. Quetsal has reduced the number of sources selected (without losing recall), the source selection time as well as the overall query runtime as compared to state-of-the-art federation engines. The LargeRDFBench evaluation results suggests that the performance of current SPARQL query federation systems on simple queries does not reflect the systems\\\' performance on more complex queries. Moreover, current federation systems seem unable to deal with many of the challenges that await them in the age of Big Data. Finally, the FEASIBLE\\\'s evaluation results shows that it generates better sample queries than the state-of-the-art. In addition, the better query selection and the larger set of query types used lead to triple store rankings which partly differ from the rankings generated by previous works.

Resource Description Framework (RDF) est devenu un modèle de données pertinentafin de décrire et de modéliser les informations qui sont partagées sur le Web.Cependant, fournir une solution permettant de stocker et de récupérer cesdonnées de manière efficace tout en passant à l’échelle reste un défi majeur.Dans le contexte de cette thèse nous proposons un intergiciel dévoué austockage, à la récupération synchrone mais aussi à la dissémination sélectiveet asynchrone en quasi temps réel d'informations RDF dans un environnementcomplètement distribué. L’objectif est de pouvoir tirer parti des informationsdu passé comme de celles filtrées en quasi temps réel. Contrairement à unegrande majorité de solutions existantes, nous avons avons fait le choixd’éviter le hachage pour indexer les données ce qui nous permet de traiter lesrequêtes à intervalles de manière efficace. Le filtrage des informations enquasi temps réel est permis par l’expression des intérêts à l’aide desouscriptions basées sur le contenu des évènements futurs. Nous avons proposédeux algorithmes qui permettent de vérifier la concordance des évènements RDFavec les souscriptions enregistrées. Les deux algorithmes ont été testésexpérimentalement. En sus de la récupération synchrone et de la diffusionasynchrone d’évènements, nous nous sommes intéressés à améliorer la répartitiondes données RDF qui souffrent de dissymétrie. Finalement, nous avons consacréun effort non négligeable à rendre notre intergiciel modulaire. / RDF has become a relevant data model for describing and modeling information on the Web but providing scalable solutions to store and retrieve RDF data in a responsive manner is still challenging. Within the context of this thesis we propose a middleware devoted to storing, retrieving synchronously but also disseminating selectively and asynchronously RDF data in a fully distributed environment. Its purposes is to allow to leverage historical information and filter data near real-time. To this aims we have built our system atop a slightly modified version of a 4-dimensional Content Addressable Network (CAN) overlay network reflecting the structure of an RDF tuple. Unlike many existing solutions we made the choice to avoid hashing for indexing data, thus allowing efficient range queries resolution. Near realtime filtering is enabled by expressing information preferences in advance through content-based subscriptions handled by a publish/subscribe layer designed atop the CAN architecture. We have proposed two algorithms to check RDF data or events satisfaction with subscriptions but also to forward solutions to interested parties. Both algorithms have been experimentally tested for throughput and scalability. Although one performs better than the other, they remain complementary to ensure correctness. Along with information retrieval and dissemination, we have proposed a solution to enhance RDF data distribution on our revised CAN network since RDF information suffers from skewness. Finally, to improve maintainability and reusability some efforts were also dedicated to provide a modular middleware reducing the coupling between its underlying software artifacts.

A presente pesquisa explora areas de Processamento de Linguagem Natural (PLN), tais como, analisadores, gramaticas e ontologias no desenvolvimento de um modelo para o mapeamento de consulta em lingua portuguesa controlada para consultas SPARQL. O SPARQL e uma linguagem de consulta capaz de recuperar e manipular dados armazenados em RDF, que e a base para a construcao de Ontologias. Este projeto pretende investigar utilizacao das tecnicas supracitadas na mitigacao do problema de consulta a Ontologias utilizando linguagem natural controlada. A principal motivacao para o desenvolvimento deste trabalho e pesquisar tecnicas e modelos que possam proporcionar uma melhor interacao do homem com o computador. Facilidade na interacao homem-computador e convergida em produtividade, eficiencia, comodidade dentre outros beneficios implicitos. Nos nos concentramos em medir a eficiencia do modelo proposto e procurar uma boa combinacao entre todas as tecnicas em questao. / This research explores areas of Natural Language Processing (NLP), such as parsers, grammars and ontologies in the development of a model for mapping queries in controlled Portuguese into SPARQL queries. The SPARQL query language allows for manipulation and retrieval of data stored as RDF, which forms the basis for building ontologies. This project aims to investigate the use of the above techniques to help curb the problem of querying ontologies using controlled natural language. The main motivation for the development of this work is to research techniques and models that could provide a better interaction between man and computer. Ease in human-computer interaction is converted into productivity, efficiency, convenience, among other implicit benefits. We focus on measuring the effectiveness of the proposed model and look for a good combination of all the techniques in question.

Avec l'avancée du Web Sémantique et des initiatives Open Linked Data, une grande quantité de documents RDF sont disponibles sur Internet. L'objectif est de rendre ces données lisibles pour les humains et les machines, en adoptant des formats spéciaux et en les connectant à l'aide des IRIs (International Resource Identifier), qui sont des abstractions de ressources réelles du monde. L’augmentation du nombre de données publiées et partagées augmente également le nombre d’informations sensibles diffusées. En conséquence, la confidentialité des entités d'intérêts (personnes, entreprises, etc.) est un véritable défi, nécessitant des techniques spéciales pour assurer la confidentialité et la sécurité adéquate des données disponibles dans un environnement où chaque utilisateur a accès à l'information sans aucune restriction (Web).Ensuite, trois aspects principaux sont considérés pour assurer la protection de l'entité: (i) Préserver la confidentialité, en identifiant les données qui peuvent compromettre la confidentialité des entités (par exemple, les identifiants, les quasi-identifiants); (ii) Identifier l'utilité des données publiques pour diverses applications (par exemple, statistiques, tests, recherche); et (iii) Les connaissances antérieures du modèle qui peuvent être utilisées par les pirates informatiques (par exemple, le nombre de relations, une relation spécifique, l'information d'un nœud).L'anonymisation est une technique de protection de la confidentialité qui a été appliquée avec succès dans les bases de données et les graphes. Cependant, les études sur l'anonymisation dans le contexte des documents RDF sont très limitées. Ces études sont les travaux initiaux de protection des individus sur des documents RDF, puisqu'ils montrent les approches pratiques d'anonymisation pour des scénarios simples comme l'utilisation d'opérations de généralisation et d'opérations de suppression basées sur des hiérarchies. Cependant, pour des scénarios complexes, où une diversité de données est présentée, les approches d'anonymisations existantes n'assurent pas une confidentialité suffisante.Ainsi, dans ce contexte, nous proposons une approche d'anonymisation, qui analyse les voisins en fonction des connaissances antérieures, centrée sur la confidentialité des entités représentées comme des nœuds dans les documents RDF. Notre approche de l'anonymisation est capable de fournir une meilleure confidentialité, car elle prend en compte la condition de la diversité de l'environnement ainsi que les voisins (nœuds et arêtes) des entités d'intérêts. En outre, un processus d'anonymisation automatique est assuré par l'utilisation d'opérations d'anonymisations associées aux types de données. / With the advance of the Semantic Web and the Open Linked Data initiatives, a huge quantity of RDF data is available on Internet. The goal is to make this data readable for humans and machines, adopting special formats and connecting them by using International Resource Identifiers (IRIs), which are abstractions of real resources of the world. As more data is published and shared, sensitive information is also provided. In consequence, the privacy of entities of interest (e.g., people, companies) is a real challenge, requiring special techniques to ensure privacy and adequate security over data available in an environment in which every user has access to the information without any restriction (Web). Then, three main aspects are considered to ensure entity protection: (i) Preserve privacy, by identifying and treating the data that can compromise the privacy of the entities (e.g., identifiers, quasi-identifiers); (ii) Identify utility of the public data for diverse applications (e.g., statistics, testing, research); and (iii) Model background knowledge that can be used for adversaries (e.g., number of relationships, a specific relationship, information of a node). Anonymization is one technique for privacy protection that has been successfully applied in practice for databases and graph structures. However, studies about anonymization in the context of RDF data, are really limited. These studies are initial works for protecting individuals on RDF data, since they show a practical anonymization approach for simple scenarios as the use of generalization and suppression operations based on hierarchies. However, for complex scenarios, where a diversity of data is presented, the existing anonymization approaches does not ensure an enough privacy. Thus, in this context, we propose an anonymization framework, which analyzes the neighbors according to the background knowledge, focused on the privacy of entities represented as nodes in the RDF data. Our anonymization approach is able to provide better privacy, since it takes into account the l-diversity condition as well as the neighbors (nodes and edges) of entities of interest. Also, an automatic anonymization process is provided by the use of anonymization operations associated to the datatypes.