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  1. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.26 
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  2. Saabiyeh, N.: What is a good ontology semantic similarity measure that considers multiple inheritance cases of concepts? (2018) 0.09 
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    Abstract
    I need to measure semantic similarity between CSO ontology concepts, depending on Ontology structure (concept path, depth, least common subsumer (LCS) ...). CSO (Computer Science Ontology) is a large-scale ontology of research areas. A concepts in CSO may have multiple parents/super concepts (i.e. a concept may be a child of many other concepts), e.g. : (world wide web) is parent of (semantic web) (semantics) is parent of (semantic web) I found some measures that meet my needs, but the papers proposing these measures are not cited, so i got hesitated. I also found a measure that depends on weighted edges, but multiple inheritance (super concepts) is not considered..
  3. Daudaravicius, V.: ¬A framework for keyphrase extraction from scientific journals (2016) 0.07 
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    Abstract
    We present a framework for keyphrase extraction from scientific journals in diverse research fields. While journal articles are often provided with manually assigned keywords, it is not clear how to automatically extract keywords and measure their significance for a set of journal articles. We compare extracted keyphrases from journals in the fields of astrophysics, mathematics, physics, and computer science. We show that the presented statistics-based framework is able to demonstrate differences among journals, and that the extracted keyphrases can be used to represent journal or conference research topics, dynamics, and specificity.
    Content
    Vortrag, "Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop co-located with the 25th International World Wide Web Conference April 11, 2016 - Montreal, Canada", Montreal 2016.
  4. Wright, H.: Semantic Web and ontologies (2018) 0.05 
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    Abstract
    The Semantic Web and ontologies can help archaeologists combine and share data, making it more open and useful. Archaeologists create diverse types of data, using a wide variety of technologies and methodologies. Like all research domains, these data are increasingly digital. The creation of data that are now openly and persistently available from disparate sources has also inspired efforts to bring archaeological resources together and make them more interoperable. This allows functionality such as federated cross-search across different datasets, and the mapping of heterogeneous data to authoritative structures to build a single data source. Ontologies provide the structure and relationships for Semantic Web data, and have been developed for use in cultural heritage applications generally, and archaeology specifically. A variety of online resources for archaeology now incorporate Semantic Web principles and technologies.
    Theme
    Semantic Web
  5. Martínez-González, M.M.; Alvite-Díez, M.L.: Thesauri and Semantic Web : discussion of the evolution of thesauri toward their integration with the Semantic Web (2019) 0.04 
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    Abstract
    Thesauri are Knowledge Organization Systems (KOS), that arise from the consensus of wide communities. They have been in use for many years and are regularly updated. Whereas in the past thesauri were designed for information professionals for indexing and searching, today there is a demand for conceptual vocabularies that enable inferencing by machines. The development of the Semantic Web has brought a new opportunity for thesauri, but thesauri also face the challenge of proving that they add value to it. The evolution of thesauri toward their integration with the Semantic Web is examined. Elements and structures in the thesaurus standard, ISO 25964, and SKOS (Simple Knowledge Organization System), the Semantic Web standard for representing KOS, are reviewed and compared. Moreover, the integrity rules of thesauri are contrasted with the axioms of SKOS. How SKOS has been applied to represent some real thesauri is taken into account. Three thesauri are chosen for this aim: AGROVOC, EuroVoc and the UNESCO Thesaurus. Based on the results of this comparison and analysis, the benefits that Semantic Web technologies offer to thesauri, how thesauri can contribute to the Semantic Web, and the challenges that would help to improve their integration with the Semantic Web are discussed.
    Theme
    Semantic Web
  6. Klic, L.; Miller, M.; Nelson, J.K.; Germann, J.E.: Approaching the largest 'API' : extracting information from the Internet with Python (2018) 0.04 
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    Abstract
    This article explores the need for libraries to algorithmically access and manipulate the world's largest API: the Internet. The billions of pages on the 'Internet API' (HTTP, HTML, CSS, XPath, DOM, etc.) are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy) in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.
  7. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.04 
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    Abstract
    More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.
    Date
    26.12.2011 13:40:22
    Theme
    Semantic Web
  8. Menzel, C.: Knowledge representation, the World Wide Web, and the evolution of logic (2011) 0.04 
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    Abstract
    In this paper, I have traced a series of evolutionary adaptations of FOL motivated entirely by its use by knowledge engineers to represent and share information on the Web culminating in the development of Common Logic. While the primary goal in this paper has been to document this evolution, it is arguable, I think that CL's syntactic and semantic egalitarianism better realizes the goal "topic neutrality" that a logic should ideally exemplify - understood, at least in part, as the idea that logic should as far as possible not itself embody any metaphysical presuppositions. Instead of retaining the traditional metaphysical divisions of FOL that reflect its Fregean origins, CL begins as it were with a single, metaphysically homogeneous domain in which, potentially, anything can play the traditional roles of object, property, relation, and function. Note that the effect of this is not to destroy traditional metaphysical divisions. Rather, it simply to refrain from building those divisions explicitly into one's logic; instead, such divisions are left to the user to introduce and enforce axiomatically in an explicit metaphysical theory.
    Theme
    Semantic Web
  9. Mäkelä, E.; Hyvönen, E.; Ruotsalo, T.: How to deal with massively heterogeneous cultural heritage data : lessons learned in CultureSampo (2012) 0.04 
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    Abstract
    This paper presents the CultureSampo system for publishing heterogeneous linked data as a service. Discussed are the problems of converting legacy data into linked data, as well as the challenge of making the massively heterogeneous yet interlinked cultural heritage content interoperable on a semantic level. Novel user interface concepts for then utilizing the content are also presented. In the approach described, the data is published not only for human use, but also as intelligent services for other computer systems that can then provide interfaces of their own for the linked data. As a concrete use case of using CultureSampo as a service, the BookSampo system for publishing Finnish fiction literature on the semantic web is presented.
    Content
    Beitrag eines Schwerpunktthemas: Semantic Web and Reasoning for Cultural Heritage and Digital Libraries: http://www.semantic-web-journal.net/content/how-deal-massively-heterogeneous-cultural-heritage-data-%E2%80%93-lessons-learned-culturesampo http://www.semantic-web-journal.net/sites/default/files/swj160_0.pdf.
    Source
    Semantic Web journal. 3(2012) no.1, S.85-109
  10. Leskinen, P.; Hyvönen, E.: Extracting genealogical networks of linked data from biographical texts (2019) 0.04 
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    Abstract
    This paper presents the idea and our work of extracting and reassembling a genealogical network automatically from a collection of biographies. The network can be used as a tool for network analysis of historical persons. The data has been published as Linked Data and as an interactive online service as part of the in-use data service and semantic portal BiographySampo - Finnish Biographies on the Semantic Web.
    Series
    Lecture notes in computer science; vol.11762
    Source
    ¬The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Ed.: P. Hitzler et al
    Theme
    Semantic Web
  11. ¬The Computer Science Ontology (CSO) (2018) 0.04 
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    Abstract
    The Computer Science Ontology (CSO) is a large-scale ontology of research areas that was automatically generated using the Klink-2 algorithm on the Rexplore dataset, which consists of about 16 million publications, mainly in the field of Computer Science. The Klink-2 algorithm combines semantic technologies, machine learning, and knowledge from external sources to automatically generate a fully populated ontology of research areas. Some relationships were also revised manually by experts during the preparation of two ontology-assisted surveys in the field of Semantic Web and Software Architecture. The main root of CSO is Computer Science, however, the ontology includes also a few secondary roots, such as Linguistics, Geometry, Semantics, and so on. CSO presents two main advantages over manually crafted categorisations used in Computer Science (e.g., 2012 ACM Classification, Microsoft Academic Search Classification). First, it can characterise higher-level research areas by means of hundreds of sub-topics and related terms, which enables to map very specific terms to higher-level research areas. Secondly, it can be easily updated by running Klink-2 on a set of new publications. A more comprehensive discussion of the advantages of adopting an automatically generated ontology in the scholarly domain can be found in.
    Object
    Computer Science Ontology
  12. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.03 
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    Content
    Vortrag, "Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop co-located with the 25th International World Wide Web Conference April 11, 2016 - Montreal, Canada", Montreal 2016.
  13. Halpin, H.; Hayes, P.J.; McCusker, J.P.; McGuinness, D.L.; Thompson, H.S.: When owl:sameAs isn't the same : an analysis of identity in linked data (2010) 0.03 
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    Abstract
    In Linked Data, the use of owl:sameAs is ubiquitous in interlinking data-sets. There is however, ongoing discussion about its use, and potential misuse, particularly with regards to interactions with inference. In fact, owl:sameAs can be viewed as encoding only one point on a scale of similarity, one that is often too strong for many of its current uses. We describe how referentially opaque contexts that do not allow inference exist, and then outline some varieties of referentially-opaque alternatives to owl:sameAs. Finally, we report on an empirical experiment over randomly selected owl:sameAs statements from the Web of data. This theoretical apparatus and experiment shed light upon how owl:sameAs is being used (and misused) on the Web of data.
    Series
    Lecture notes in computer science; 6496
    Source
    The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Eds.: Peter F. Patel-Schneider et al
  14. Berners-Lee, T.: ¬The Father of the Web will give the Internet back to the people (2018) 0.03 
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    Content
    "This week, Berners-Lee will launch Inrupt ( https://www.password-online.de/?email_id=571&user_id=1045&urlpassed=aHR0cHM6Ly93d3cuaW5ydXB0LmNvbQ&controller=stats&action=analyse&wysija-page=1&wysijap=subscriptions ), a startup that he has been building, in stealth mode, for the past nine months. For years now, Berners-Lee and other internet activists have been dreaming of a digital utopia where individuals control their own data and the internet remains free and open. But for Berners-Lee, the time for dreaming is over. "We have to do it now," he says, displaying an intensity and urgency that is uncharacteristic for this soft-spoken academic. "It's a historical moment." If all goes as planned, Inrupt will be to Solid what Netscape once was for many first-time users of the web: an easy way in. . On his screen, there is a simple-looking web page with tabs across the top: Tim's to-do list, his calendar, chats, address book. He built this app-one of the first on Solid for his personal use. It is simple, spare. In fact, it's so plain that, at first glance, it's hard to see its significance. But to Berners-Lee, this is where the revolution begins. The app, using Solid's decentralized technology, allows Berners-Lee to access all of his data seamlessly-his calendar, his music library, videos, chat, research. It's like a mashup of Google Drive, Microsoft Outlook, Slack, Spotify, and WhatsApp. The difference here is that, on Solid, all the information is under his control. In: Exclusive: Tim Berners-Lee tells us his radical new plan to upend the World Wide Web ( https://www.password-online.de/?email_id=571&user_id=1045&urlpassed=aHR0cHM6Ly93d3cuZmFzdGNvbXBhbnkuY29tLzkwMjQzOTM2L2V4Y2x1c2l2ZS10aW0tYmVybmVycy1sZWUtdGVsbHMtdXMtaGlzLXJhZGljYWwtbmV3LXBsYW4tdG8tdXBlbmQtdGhlLXdvcmxkLXdpZGUtd2Vi&controller=stats&action=analyse&wysija-page=1&wysijap=subscriptions ), in: https://www.fastcompany.com/90243936/exclusive-tim-berners-lee-tells-us-his-radical-new-plan-to-upend-the-world-wide-web ( https://www.password-online.de/?email_id=571&user_id=1045&urlpassed=aHR0cHM6Ly93d3cuZmFzdGNvbXBhbnkuY29tLzkwMjQzOTM2L2V4Y2x1c2l2ZS10aW0tYmVybmVycy1sZWUtdGVsbHMtdXMtaGlzLXJhZGljYWwtbmV3LXBsYW4tdG8tdXBlbmQtdGhlLXdvcmxkLXdpZGUtd2Vi&controller=stats&action=analyse&wysija-page=1&wysijap=subscriptions)."
  15. Lange, C.: Ontologies and languages for representing mathematical knowledge on the Semantic Web (2011) 0.03 
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    Abstract
    Mathematics is a ubiquitous foundation of science, technology, and engineering. Specific areas, such as numeric and symbolic computation or logics, enjoy considerable software support. Working mathematicians have recently started to adopt Web 2.0 environment, such as blogs and wikis, but these systems lack machine support for knowledge organization and reuse, and they are disconnected from tools such as computer algebra systems or interactive proof assistants.We argue that such scenarios will benefit from Semantic Web technology. Conversely, mathematics is still underrepresented on the Web of [Linked] Data. There are mathematics-related Linked Data, for example statistical government data or scientific publication databases, but their mathematical semantics has not yet been modeled. We argue that the services for the Web of Data will benefit from a deeper representation of mathematical knowledge. Mathematical knowledge comprises logical and functional structures - formulæ, statements, and theories -, a mixture of rigorous natural language and symbolic notation in documents, application-specific metadata, and discussions about conceptualizations, formalizations, proofs, and (counter-)examples. Our review of approaches to representing these structures covers ontologies for mathematical problems, proofs, interlinked scientific publications, scientific discourse, as well as mathematical metadata vocabularies and domain knowledge from pure and applied mathematics. Many fields of mathematics have not yet been implemented as proper Semantic Web ontologies; however, we show that MathML and OpenMath, the standard XML-based exchange languages for mathematical knowledge, can be fully integrated with RDF representations in order to contribute existing mathematical knowledge to theWeb of Data. We conclude with a roadmap for getting the mathematical Web of Data started: what datasets to publish, how to interlink them, and how to take advantage of these new connections.
    Content
    Vgl.: http://www.semantic-web-journal.net/content/ontologies-and-languages-representing-mathematical-knowledge-semantic-web http://www.semantic-web-journal.net/sites/default/files/swj122_2.pdf.
    Source
    Semantic Web journal. 2(2012), no.x
  16. Markoff, J.: Researchers announce advance in image-recognition software (2014) 0.03 
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    Content
    "Until now, so-called computer vision has largely been limited to recognizing individual objects. The new software, described on Monday by researchers at Google and at Stanford University, teaches itself to identify entire scenes: a group of young men playing Frisbee, for example, or a herd of elephants marching on a grassy plain. The software then writes a caption in English describing the picture. Compared with human observations, the researchers found, the computer-written descriptions are surprisingly accurate. The advances may make it possible to better catalog and search for the billions of images and hours of video available online, which are often poorly described and archived. At the moment, search engines like Google rely largely on written language accompanying an image or video to ascertain what it contains. "I consider the pixel data in images and video to be the dark matter of the Internet," said Fei-Fei Li, director of the Stanford Artificial Intelligence Laboratory, who led the research with Andrej Karpathy, a graduate student. "We are now starting to illuminate it." Dr. Li and Mr. Karpathy published their research as a Stanford University technical report. The Google team published their paper on arXiv.org, an open source site hosted by Cornell University.
    In the longer term, the new research may lead to technology that helps the blind and robots navigate natural environments. But it also raises chilling possibilities for surveillance. During the past 15 years, video cameras have been placed in a vast number of public and private spaces. In the future, the software operating the cameras will not only be able to identify particular humans via facial recognition, experts say, but also identify certain types of behavior, perhaps even automatically alerting authorities. Two years ago Google researchers created image-recognition software and presented it with 10 million images taken from YouTube videos. Without human guidance, the program trained itself to recognize cats - a testament to the number of cat videos on YouTube. Current artificial intelligence programs in new cars already can identify pedestrians and bicyclists from cameras positioned atop the windshield and can stop the car automatically if the driver does not take action to avoid a collision. But "just single object recognition is not very beneficial," said Ali Farhadi, a computer scientist at the University of Washington who has published research on software that generates sentences from digital pictures. "We've focused on objects, and we've ignored verbs," he said, adding that these programs do not grasp what is going on in an image. Both the Google and Stanford groups tackled the problem by refining software programs known as neural networks, inspired by our understanding of how the brain works. Neural networks can "train" themselves to discover similarities and patterns in data, even when their human creators do not know the patterns exist.
    In living organisms, webs of neurons in the brain vastly outperform even the best computer-based networks in perception and pattern recognition. But by adopting some of the same architecture, computers are catching up, learning to identify patterns in speech and imagery with increasing accuracy. The advances are apparent to consumers who use Apple's Siri personal assistant, for example, or Google's image search. Both groups of researchers employed similar approaches, weaving together two types of neural networks, one focused on recognizing images and the other on human language. In both cases the researchers trained the software with relatively small sets of digital images that had been annotated with descriptive sentences by humans. After the software programs "learned" to see patterns in the pictures and description, the researchers turned them on previously unseen images. The programs were able to identify objects and actions with roughly double the accuracy of earlier efforts, although still nowhere near human perception capabilities. "I was amazed that even with the small amount of training data that we were able to do so well," said Oriol Vinyals, a Google computer scientist who wrote the paper with Alexander Toshev, Samy Bengio and Dumitru Erhan, members of the Google Brain project. "The field is just starting, and we will see a lot of increases."
    Computer vision specialists said that despite the improvements, these software systems had made only limited progress toward the goal of digitally duplicating human vision and, even more elusive, understanding. "I don't know that I would say this is 'understanding' in the sense we want," said John R. Smith, a senior manager at I.B.M.'s T.J. Watson Research Center in Yorktown Heights, N.Y. "I think even the ability to generate language here is very limited." But the Google and Stanford teams said that they expect to see significant increases in accuracy as they improve their software and train these programs with larger sets of annotated images. A research group led by Tamara L. Berg, a computer scientist at the University of North Carolina at Chapel Hill, is training a neural network with one million images annotated by humans. "You're trying to tell the story behind the image," she said. "A natural scene will be very complex, and you want to pick out the most important objects in the image.""
  17. Hyvönen, E.; Leskinen, P.; Tamper, M.; Keravuori, K.; Rantala, H.; Ikkala, E.; Tuominen, J.: BiographySampo - publishing and enriching biographies on the Semantic Web for digital humanities research (2019) 0.03 
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    Abstract
    This paper argues for making a paradigm shift in publishing and using biographical dictionaries on the web, based on Linked Data. The idea is to provide the user with enhanced reading experience of biographies by enriching contents with data linking and reasoning. In addition, versatile tooling for 1) biographical research of individual persons as well as for 2) prosopographical research on groups of people are provided. To demonstrate and evaluate the new possibilities,we present the semantic portal "BiographySampo - Finnish Biographies on theSemantic Web". The system is based on a knowledge graph extracted automatically from a collection of 13.100 textual biographies, enriched with data linking to 16 external data sources, and by harvesting external collection data from libraries, museums, and archives. The portal was released in September 2018 for free public use at: http://biografiasampo.fi.
    Series
    Lecture notes in computer science; vol.11503
    Source
    ¬The Semantic Web. ESWC 2019 Satellite Events, ESWC 2019 Satellite Events, Portoroz, Slovenia, June 2-6, 2019, Revised Selected Papers
    Theme
    Semantic Web
  18. Surfing versus Drilling for knowledge in science : When should you use your computer? When should you use your brain? (2018) 0.03 
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    Abstract
    For this second Special Issue of Infozine, we have invited students, teachers, researchers, and software developers to share their opinions about one or the other aspect of this broad topic: how to balance drilling (for depth) vs. surfing (for breadth) in scientific learning, teaching, research, and software design - and how the modern digital-liberal system affects our ability to strike this balance. This special issue is meant to provide a wide and unbiased spectrum of possible viewpoints on the topic, helping readers to define lucidly their own position and information use behavior.
    Content
    Editorial: Surfing versus Drilling for Knowledge in Science: When should you use your computer? When should you use your brain? Blaise Pascal: Les deux infinis - The two infinities / Philippe Hünenberger and Oliver Renn - "Surfing" vs. "drilling" in the modern scientific world / Antonio Loprieno - Of millimeter paper and machine learning / Philippe Hünenberger - From one to many, from breadth to depth - industrializing research / Janne Soetbeer - "Deep drilling" requires "surfing" / Gerd Folkers and Laura Folkers - Surfing vs. drilling in science: A delicate balance / Alzbeta Kubincová - Digital trends in academia - for the sake of critical thinking or comfort? / Leif-Thore Deck - I diagnose, therefore I am a Doctor? Will drilling computer software replace human doctors in the future? / Yi Zheng - Surfing versus drilling in fundamental research / Wilfred van Gunsteren - Using brain vs. brute force in computational studies of biological systems / Arieh Warshel - Laboratory literature boards in the digital age / Jeffrey Bode - Research strategies in computational chemistry / Sereina Riniker - Surfing on the hype waves or drilling deep for knowledge? A perspective from industry / Nadine Schneider and Nikolaus Stiefl - The use and purpose of articles and scientists / Philip Mark Lund - Can you look at papers like artwork? / Oliver Renn - Dynamite fishing in the data swamp / Frank Perabo 34 Streetlights, augmented intelligence, and information discovery / Jeffrey Saffer and Vicki Burnett - "Yes Dave. Happy to do that for you." Why AI, machine learning, and blockchain will lead to deeper "drilling" / Michiel Kolman and Sjors de Heuvel - Trends in scientific document search ( Stefan Geißler - Power tools for text mining / Jane Reed 42 Publishing and patenting: Navigating the differences to ensure search success / Paul Peters
  19. Perovsek, M.; Kranjca, J.; Erjaveca, T.; Cestnika, B.; Lavraca, N.: TextFlows : a visual programming platform for text mining and natural language processing (2016) 0.03 
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    Abstract
    Text mining and natural language processing are fast growing areas of research, with numerous applications in business, science and creative industries. This paper presents TextFlows, a web-based text mining and natural language processing platform supporting workflow construction, sharing and execution. The platform enables visual construction of text mining workflows through a web browser, and the execution of the constructed workflows on a processing cloud. This makes TextFlows an adaptable infrastructure for the construction and sharing of text processing workflows, which can be reused in various applications. The paper presents the implemented text mining and language processing modules, and describes some precomposed workflows. Their features are demonstrated on three use cases: comparison of document classifiers and of different part-of-speech taggers on a text categorization problem, and outlier detection in document corpora.
    Source
    Science of computer programming. In Press, 2016
  20. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.03 
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    Abstract
    After the launch of the World Wide Web, it became clear that searching documentson the Web would not be trivial. Well-known engines to search the web, like Google, focus on search in web documents using keywords. The documents are structured and indexed to ensure keywords match documents as accurately as possible. However, searching by keywords does not always suice. It is oen the case that users do not know exactly how to formulate the search query or which keywords guarantee retrieving the most relevant documents. Besides that, it occurs that users rather want to browse information than looking up something specific. It turned out that there is need for systems that enable more interactivity and facilitate the gradual refinement of search queries to explore the Web. Users expect more from the Web because the short keyword-based queries they pose during search, do not suffice for all cases. On top of that, the Web is changing structurally. The Web comprises, apart from a collection of documents, more and more linked data, pieces of information structured so they can be processed by machines. The consequently applied semantics allow users to exactly indicate machines their search intentions. This is made possible by describing data following controlled vocabularies, concept lists composed by experts, published uniquely identifiable on the Web. Even so, it is still not trivial to explore data on the Web. There is a large variety of vocabularies and various data sources use different terms to identify the same concepts.
    This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.
    The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. eries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research.
    Theme
    Semantic Web

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