abstract: The concept of Linked Data is gaining widespread popularity and importance. The method of publishing and linking structured data on the web is called Linked Data. Emergence of Linked Data has made it possible to make sense of huge data, which is scattered all over the web, and link multiple heterogeneous sources. This leads to the challenge of maintaining the quality of Linked Data, i.e., ensuring outdated data is removed and new data is included. The focus of this thesis is devising strategies to effectively integrate data from multiple sources, publish it as Linked Data, and maintain the quality of Linked Data. The domain used in the study is online education. With so many online courses offered by Massive Open Online Courses (MOOC), it is becoming increasingly difficult for an end user to gauge which course best fits his/her needs. Users are spoilt for choices. It would be very helpful for them to make a choice if there is a single place where they can visually compare the offerings of various MOOC providers for the course they are interested in. Previous work has been done in this area through the MOOCLink project that involved integrating data from Coursera, EdX, and Udacity and generation of linked data, i.e. Resource Description Framework (RDF) triples. The research objective of this thesis is to determine a methodology by which the quality of data available through the MOOCLink application is maintained, as there are lots of new courses being constantly added and old courses being removed by data providers. This thesis presents the integration of data from various MOOC providers and algorithms for incrementally updating linked data to maintain their quality and compare it against a naïve approach in order to constantly keep the users engaged with up-to-date data. A master threshold value was determined through experiments and analysis that quantifies one algorithm being better than the other in terms of time efficiency. An evaluation of the tool shows the effectiveness of the algorithms presented in this thesis. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Several institutions collect statistical data about cities, regions, and countries for various purposes. Yet, while access to high quality and recent such data is both crucial for decision makers and a means for achieving transparency to the public, all too often such collections of data remain isolated and not re-useable, let alone comparable or properly integrated. In this paper we present the Open City Data Pipeline, a focused attempt to collect, integrate, and enrich statistical data collected at city level worldwide, and re-publish the resulting dataset in a re-useable manner as Linked Data. The main features of the Open City Data Pipeline are: (i) we integrate and cleanse data from several sources in a modular and extensible, always up-to-date fashion; (ii) we use both Machine Learning techniques and reasoning over equational background knowledge to enrich the data by imputing missing values, (iii) we assess the estimated accuracy of such imputations per indicator. Additionally, (iv) we make the integrated and enriched data, including links to external data sources, such as DBpedia, available both in a web browser interface and as machine-readable Linked Data, using standard vocabularies such as QB and PROV. Apart from providing a contribution to the growing collection of data available as Linked Data, our enrichment process for missing values also contributes a novel methodology for combining rule-based inference about equational knowledge with inferences obtained from statistical Machine Learning approaches. While most existing works about inference in Linked Data have focused on ontological reasoning in RDFS and OWL, we believe that these complementary methods and particularly their combination could be fruitfully applied also in many other domains for integrating Statistical Linked Data, independent from our concrete use case of integrating city data.

The goal with this project was to convert open structured data, e.g. csv-files, to Linked Open Data and to demonstrate possible uses of such data. The project was also supposed to inspire and lay a foundation for future work in the area. The conversion was done using the D2RQ platform, and the chosen dataset contains air quality measurements from Umeå Municipality. The resulting data was then published on the internet with D2R server. For demonstration purposes two tasks were done. A visualization of the converted data was published on the web, together with traffic and weather data. Secondly a physical city model was built of carton with eight photodiodes, a Raspberry Pi and visualized with a local webserver. The goals for the project were fulfilled and it has also inspired Knowit to continue with commercial projects in the area of Linked Open Data. Future effort should be put in converting more data to Linked Open Data and to create full scale sensor networks in a city.

Conferencia realizada en el marco de la Semana del Acceso Abierto Perú, llevada a cabo del 24 al 26 de Octubre de 2016 en Lima, Peru. Las instituciones organizadoras: Universidad Peruana de Ciencias aplciadasd (UPC), Pontificia Universidad Católica del Perú (PUCP) y Universidad Peruana Cayetano Heredia (UPCH). / Conferencia que aborda aspectos del protocolo Linked Data, temas de Big Data y Web Semantica,

Conferencia realizada en el marco de la Semana del Acceso Abierto Perú, llevada a cabo del 24 al 26 de Octubre de 2016 en Lima, Peru. Las instituciones organizadoras: Universidad Peruana de Ciencias aplciadasd (UPC), Pontificia Universidad Católica del Perú (PUCP) y Universidad Peruana Cayetano Heredia (UPCH). / Conferencia que aborda aspectos del protocolo Linked Data, temas de Big Data y Web Semantica,

Within the project Maps without Barriers realized under Charta 77 Foundation - Barriers Account, in 2015 we intend to map accessibility of buildings and its premises from the perspective of people with limited mobility. We plan to inspect nearly 600 castles, palaces and other tourist attractions in the Czech Republic. The acquired data will be gathered and published as an on-line map in form of open and machine-readable data. It will also appear as Linked Open Data. However, the project will not end with mapping premises, the main objective is to provide a solid foundation for a unified database of accessibility of buildings and its premises. Negotiations with institutions and organizations interested in mapping are in progress and we try to offer them our project platform for publication of their data. The required RDFS vocabulary will be designed and carried out as part of this diploma thesis. It will be tested on the data from a number of forms describing existing objects. The data will be gathered by means of services designed in terms of this theses and provided for purchasers and users equally.

Sharing information securely between business partners and managing large supply chains effciently will be a crucial competitive advantage for enterprises in the near future. In this paper, we present a concept that allows for building value networks between business partners in a distributed manner. Companies are able to publish Linked Data which participants of the network can clone and subscribe to. Subscribers get noticed as soon as new information becomes available. This provides a technical infrastructure for business communication acts such as supply chain communication or master data management. In addition to the conceptual analysis, we provide an implementation enabling companies to create such dynamic semantic value networks.

Little-known lexicographic resources can be of tremendous value to users once digitised. By extending the digitisation efforts for a lexicographic resource, converting the human readable digital object to a state that is also machine-readable, structured data can be created that is semantically interoperable, thereby enabling the lexicographic resource to access, and be accessed by, other semantically interoperable resources. The purpose of this study is to formulate a process when converting a lexicographic resource in print form to a machine-readable bilingual lexicographic resource applying linguistic linked data principles, using the English-Xhosa Dictionary for Nurses as a case study. This is accomplished by creating a linked data framework, in which data are expressed in the form of RDF triples and URIs, in a manner which allows for extensibility to a multilingual resource. Click languages with characters not typically represented by the Roman alphabet are also considered. The purpose of this linked data framework is to define each lexical entry as “historically dynamic”, instead of “ontologically static” (Rafferty, 2016:5). For a framework which has instances in constant evolution, focus is thus given to the management of provenance and linked data generation thereof. The output is an implementation framework which provides methodological guidelines for similar language resources in the interdisciplinary field of Library and Information Science.

No description available.

The success of semantic systems has been proven over the last years. Nowadays, Linked Data is the driver for the rapid development of ever new intelligent systems. Especially in enterprise environments semantic systems successfully support more and more business processes. This is especially true for after sales service in the mechanical engineering domain. Here, service technicians need effective access to relevant technical documentation in order to diagnose and solve problems and defects. Therefore, the usage of semantic information retrieval systems has become the new system metaphor. Unlike classical retrieval software Linked Enterprise Data graphs are exploited to grant targeted and problem-oriented access to relevant documents. However, huge parts of legacy technical documents have not yet been integrated into Linked Enterprise Data graphs. Additionally, a plethora of information models for the semantic representation of technical information exists. The semantic maturity of these information models can hardly be measured. This thesis motivates that there is an inherent need for a self-contained semantification approach for technical documents. This work introduces a maturity model that allows to quickly assess existing documentation. Additionally, the approach comprises an abstracting semantic representation for technical documents that is aligned to all major standard information models. The semantic representation combines structural and rhetorical aspects to provide access to so called Core Documentation Entities. A novel and holistic semantification process describes how technical documents in different legacy formats can be transformed to a semantic and linked representation. The practical significance of the semantification approach depends on tools supporting its application. This work presents an accompanying tool chain of semantification applications, especially the semantification framework CAPLAN that is a highly integrated development and runtime environment for semantification processes. The complete semantification approach is evaluated in four real-life projects: in a spare part augmentation project, semantification projects for earth moving technology and harvesting technology, as well as an ontology population project for special purpose vehicles. Three additional case studies underline the broad applicability of the presented ideas. / Semantische Systeme haben in den letzten Jahren ihren Erfolg bewiesen. Linked Data ist heute der Treiber für die rasante Entwicklung immer neuer intelligenter Systeme. Insbesondere in Unternehmensumgebungen unterstützen semantische Systeme erfolgreich immer mehr Geschäftsprozesse. Dies gilt insbesondere für den After-Sales-Service im Maschinenbau. Hier benötigen Servicetechniker einen effektiven Zugang zu relevanter technischer Dokumentation, um Probleme und Defekte effizient zu diagnostizieren und zu lösen. Daher ist die Verwendung semantischer Information Retrieval Systeme zur neuen Systemmetapher geworden. Im Gegensatz zur klassischen Retrieval-Software werden Linked Enterprise Data Graphen genutzt, um einen gezielten und problemorientierten Zugriff auf relevante Dokumente zu ermöglichen. Große Teile der alten technischen Dokumente wurden jedoch noch nicht mit Enterprise Linked Data Graphen verknüpft. Darüber hinaus gibt es eine Vielzahl von unterschiedlichen Informationsmodellen zur semantischen Repräsentation technischer Informationen. Der semantische Reifegrad dieser Informationsmodelle war bisher kaum messbar. Diese Arbeit zeigt, dass es einen inhärenten Bedarf an einem in sich geschlossenen Semantifizierungs-Ansatz für technische Dokumente gibt. Diese Arbeit stellt ein semantisches Reifegradmodell vor, das es ermöglicht, bestehende Dokumentationen schnell zu bewerten. Darüber hinaus umfasst der Ansatz eine abstrahierende semantische Darstellung für technische Dokumente, die auf alle wichtigen Standardinformationsmodelle abgestimmt ist. Die semantische Repräsentation kombiniert strukturelle und rhetorische Aspekte, um Zugang zu so genannten Core Documentation Entities zu ermöglichen. Ein neuartiger und ganzheitlicher Semantifizierungs-Prozess beschreibt, wie technische Dokumente in verschiedenen Legacy-Formaten in eine semantische und vernetzte Repräsentation transformiert werden können. Die praktische Bedeutung des Semantifizierungsansatzes hängt von Werkzeugen ab, die seine Anwendung unterstützen. Diese Arbeit stellt eine Software-Werkzeugbox von Semantifizierungs-Anwendungen vor, insbesondere das Semantifizierungs-Framework CAPLAN, eine hochintegrierte Entwicklungs- und Laufzeitumgebung für Semantifizierungs-Prozesse. Der vollständige Semantifizierungs-Aansatz wurde in vier realen Projekten evaluiert: einem Projekt zur semantischen Anreicherung von Ersatzteilinformationen, Semantifizierungs-Projekten für Erdbewegungstechnik und Erntetechnik sowie einem Ontologie-Populationsprojekt für Spezialfahrzeuge. Drei weitere Fallstudien unterstreichen die breite Anwendbarkeit der vorgestellten Ideen.