As of Today (2017) Geographic Information (GI) is a vital part of our daily life. With different applications like Google Maps it is hard to not get in contact with these platforms. Applications like Google are becoming more than just maps for us to find our way in the real world, they contain important data. As of now some of these datasets are kept by authorities and institutes with no connection to each other. One way to link this information to each other is by using Linked Data and more specifically when it comes to GI, Linked Geodata. By linking data together, information becomes connected, which can help the structure of Open Data and other data collaborates. It also enables ways to query the data to for example in search engines. This Bachelor of Science thesis has been conducted at KTH Royal Institute of Technology, in cooperation with Digpro AB. This thesis purpose is to examine whether the Linked Geodata is something to invest in. This was done by investigating current use to understand how Linked Geodata is implemented, as well to describe challenges and possibilities in respect to Linked Geodata. This is done by literature review and through interviews with personnel working with implementation of Linked Geodata. The result showed some implementations in the Netherlands and in Finland, also a private initiative from the University of Leipzig called LinkedGeoData. In Sweden authorities had explored the topic of Linked Geodata without any actual attempts to implement it. The biggest challenges was that queries did not supported all kind of spatial data, maintain the Linked Geodata consistent and find a way to fund the workload. The biggest possibilities were to create cooperation between authorities, integration and discoverability of data in search engines and to improve the environment for publishing open data, which could lead to an improved social and economic situation. After evaluation this thesis concludes that there is a lot of potential use for Linked Geodata. The most considerable possible use is for authorities with a larger amount of geodata especially regarding their publishing of Open Data and integrating their data to search engines to provide more advanced queries. The technology seems to have some problems, mainly the lack of support for spatial data and also problems with maintaining the connections. However the problems are not too severe in order to not invest in the technology. The technology just needs some improvements and more initiatives. / Idag (2017) är Geografisk Information (GI) en viktigt del av vårt dagliga liv. Med olika applikationer som Google Maps så är det svårt att inte komma i kontakt med sådana plattformar. Dem börjar bli mer än bara kartor för att hitta vart man ska. Idag är informationen i många fall inte knuten till varandra vilket betyder att informationen skulle kunna utnyttjas bättre om det var länkat. Ett sätt att länka sådan information och länka objekt till varandra är med Länkade Data och mer specifikt när det kommer till GI Länkade Geodata. Länkade Data kan sedan användas vid publicering av öppen data, för att berika mängden information. Det kan också användas för att förberedd webben för maskin läsning. Med detta menas att datorer ska kunna läsa av webben. Detta är en Kandidat examensarbete som har varit dirigerat av Kungliga Tekniska Högskolan, i samarbete med företaget Digpro AB. Syftet med denna uppsats är att ta reda på om Länkade Geodata är något att investera i. Detta var utfört genom att ta reda på hur dagsläget ser ut i olika länder samt hur det är implementerat. Samt beskriva utmaningar och möjligheter med Länkade Geodata. Detta är utfört genom litteraturstudier och intervjuer med behörig personal som antingen arbetar inom Geodata sektorn eller med Länkade Geodata. Resultatet visade några implementationer i Nederländer och Finland samt ett privat initiativ av ett Universitet kallat LinkedGeoData. I Sverige hade institut utvärderat möjligheterna för Länkade Geodata samt kommit fram med riktlinjer, men ingen storskalig implementation har blivit gjord. De störst utmaningarna var hitta tillräckligt med stöd för alla typer av spatial data, underhålla det så kallade Semantiska Molnet samt fördela arbetsbörda och hitta en finansiär. Det största möjligheterna var att kunna skapa en samverkan mellan olika instituts data, integration och upptäckbarhet av information i sökmotorer samt en förbättrad miljö för publicering av öppen data som kan leda till social och ekonomiska förbättringar. Den här uppsatsen drar slutsatsen att det finns stor potential användande för Länkade Geodata. Det störst användningsområdet är för institut med stor mängder geodata speciellt när det kommer till användandet av att publicera Öppen Data och integrera information till sökmotorer för att möjligöra svårare frågeställningar. Tekniken har en del problem t.ex. med att bearbeta spatial data och att den är svår att underhålla. Dock är dessa problem inte graverande nog att stoppa investeringar i den. Tekniken behöver förbättringar och mer initiativ till bearbetning av den.

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[pt] O Resource Description Framework (RDF) foi adotado como uma recomendação do W3C em 1999 e hoje é um padrão para troca de dados na Web. De fato, uma grande quantidade de dados foi convertida em RDF, muitas vezes em vários conjuntos de dados fisicamente distribuídos ao longo de diferentes localizações. A linguagem de consulta SPARQL (sigla do inglês de SPARQL Protocol and RDF Query Language) foi oficialmente introduzido em 2008 para recuperar dados RDF e fornecer endpoints para consultar fontes distribuídas. Uma maneira alternativa de acessar conjuntos de dados RDF é usar consultas baseadas em palavras-chave, uma área que tem sido extensivamente pesquisada, com foco recente no conteúdo da Web. Esta dissertação descreve uma estratégia para compilar consultas baseadas em palavras-chave em consultas SPARQL federadas sobre conjuntos de dados RDF distribuídos, assumindo que cada conjunto de dados RDF tem um esquema e que a federação tem um esquema mediado. O processo de compilação da consulta SPARQL federada é explicado em detalhe, incluindo como computar o conjunto de joins externos entre as subconsultas locais geradas, como combinar, com a ajuda de cláusulas UNION, os resultados de consultas locais que não têm joins entre elas, e como construir a cláusula TARGET, de acordo com a composição da cláusula WHERE. Finalmente, a dissertação cobre experimentos com dados do mundo real para validar a implementação. / [en] The Resource Description Framework (RDF) was adopted as a W3C recommendation in 1999 and today is a standard for exchanging data in the Web. Indeed, a large amount of data has been converted to RDF, often as multiple datasets physically distributed over different locations. The SPARQL Protocol and RDF Query Language (SPARQL) was officially introduced in 2008 to retrieve RDF datasets and provide endpoints to query distributed sources. An alternative way to access RDF datasets is to use keyword-based queries, an area that has been extensively researched, with a recent focus on Web content. This dissertation describes a strategy to compile keyword-based queries into federated SPARQL queries over distributed RDF datasets, under the assumption that each RDF dataset has a schema and that the federation has a mediated schema. The compilation process of the federated SPARQL query is explained in detail, including how to compute a set of external joins between the local subqueries, how to combine, with the help of the UNION clauses, the results of local queries which have no external joins between them, and how to construct the TARGET clause, according to the structure of the WHERE clause. Finally, the dissertation covers experiments with real-world data to validate the implementation.

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Medical researchers utilize data sharing agreements (DSA) to communicate privacy policies that govern the treatment of data in their collaboration. Expression of privacy policies in DSAs have been achieved through the use of natural and policy languages. However, ambiguity in natural language and rigidness in policy languages make them unsuitable for use in collaborative medical research. Our goal is to develop an unambiguous and flexible form of expression of privacy policies for collaborative medical research. In this thesis, we developed a DSA Privacy Ontology to express privacy policies in medical research. Our ontology was designed with hierarchy structure, lightweight in expressivity, closed world assumption in interpretation, and the reuse of other ontologies. The design allows our ontology to be flexible and extensible. Being flexible allows our ontology to express different types of privacy policies. Being extensible allows our ontology to be mapped to other linkable ontologies without the need to change our existing ontology. We demonstrate that our ontology is capable of supporting the DSA in a collaborative research data sharing scenario through providing the appropriate vocabulary and structure to log privacy events in a linked data based audit log. Furthermore, through querying the audit log, we can answer privacy competency questions relevant to medical researchers. / Thesis / Master of Science (MSc)

Linklets are location-independent web services, which consume and produce Linked Data resources. These resources form a web of data - the semantic web - that is an abstraction of the web 2.0. However, enterprises are reluctant to provide valuable Linked Data resources due to missing financial stimuli. Operations are not representable in the semantic web. Linklets aim to solve both problems. Previous work developed a prototype. The goal of this thesis is to enhance it by a component model, a formal description and a permission model. A business model has to be developed. This thesis follows a bottom-up approach. The formalization of the Linklet concept creates a foundation. Then, an improved architecture and its reference implementation are studied. It is evaluated by tests, show cases and economic considerations. The resulting component system is based on web-service component systems, while a sandbox concept is the core of the permission model. The formal description shows limits of OWLs open world assumption. A platform leader strategy is the foundation for the business model. In conclusion, the advantages of the Linklet concept provide a way to enhance and monetize the value of the semantic web. Further research is required; the practical use has to be considered.

[pt] Com o surgimento da Linked (Open) Data, uma série de novos e importantes desafios de pesquisa vieram à tona. A abertura de dados, como muitas vezes a Linked Data é conhecida, oferece uma oportunidade para integrar e conectar, de forma homogênea, fontes de dados heterogêneas na Web. Como diferentes fontes de dados, com recursos em comum ou relacionados, são publicados por diferentes editores, a sua integração e consolidação torna-se um verdadeiro desafio. Outro desafio advindo da Linked Data está na criação de um grafo denso de dados na Web. Com isso, a identificação e interligação, não só de recursos idênticos, mas também dos recursos relacionadas na Web, provê ao consumidor (data consumer) uma representação mais rica dos dados e a possibilidade de exploração dos recursos conectados. Nesta tese, apresentamos três abordagens para enfrentar os problemas de integração, consolidação e interligação de dados. Nossa primeira abordagem combina técnicas de informação mútua e programação genética para solucionar o problema de alinhamento complexo entre fontes de dados, um problema raramente abordado na literatura. Na segunda e terceira abordagens, adotamos e ampliamos uma métrica utilizada em teoria de redes sociais para enfrentar o problema de consolidação e interligação de dados. Além disso, apresentamos um aplicativo Web chamado Cite4Me que fornece uma nova perspectiva sobre a pesquisa e recuperação de conjuntos de Linked Open Data, bem como os benefícios da utilização de nossas abordagens. Por fim, uma série de experimentos utilizando conjuntos de dados reais demonstram que as nossas abordagens superam abordagens consideradas como estado da arte. / [en] With the emergence of Linked (Open) Data, a number of novel and notable research challenges have been raised. The openness that often characterises Linked Data offers an opportunity to homogeneously integrate and connect heterogeneous data sources on the Web. As disparate data sources with overlapping or related resources are provided by different data publishers, their integration and consolidation becomes a real challenge. An additional challenge of Linked Data lies in the creation of a well-interlinked graph of Web data. Identifying and linking not only identical Web resources, but also lateral Web resources, provides the data consumer with richer representation of the data and the possibility of exploiting connected resources. In this thesis, we present three approaches that tackle data integration, consolidation and linkage problems. Our first approach combines mutual information and genetic programming techniques for complex datatype property matching, a rarely addressed problem in the literature. In the second and third approaches, we adopt and extend a measure from social network theory to address data consolidation and interlinking. Furthermore, we present a Web-based application named Cite4Me that provides a new perspective on search and retrieval of Linked Open Data sets, as well as the benefits of using our approaches. Finally, we validate our approaches through extensive evaluations using real-world datasets, reporting results that outperform state of the art approaches.

Trotz eines verbesserten digitalen Zugangs zu wissenschaftlichen Publikationen in den letzten Jahren bleiben die Grundprinzipien der wissenschaftlichen Kommunikation unverändert und sind weiterhin weitgehend dokumentenbasiert. Die dokumentorientierten Arbeitsabläufe in der Wissenschaft haben die Grenzen der Angemessenheit erreicht, wie die jüngsten Diskussionen über das ungebremste Wachstum wissenschaftlicher Literatur, die Mängel des Peer-Review und die Reproduzierbarkeitskrise zeigen. Open Access ist eine wichtige Voraussetzung diesen Herausforderungen zu begegnen, aber auch nur der erste Schritt. Wir müssen die wissenschaftliche Kommunikation stärker wissensbasiert organisieren, indem wir wissenschaftliche Beiträge und verwandte Artefakte durch semantisch reichhaltige, vernetzte Wissensgraphen ausdrücken und miteinander vernetzen. In diesem Vortrag werden wir mit der Open Research Knowledge Graph Initiative erste Schritte in diese Richtung vorstellen.