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Matches in ScholarlyData for { ?s <https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstract> ?o. }

• 57 abstract "Semantic similarity and relatedness measures between ontology concepts are useful in many research areas. While similarity only considers subsumption relations to assess how two objects are alike, relatedness takes into account a broader range of relations (e.g., part-of). In this paper, we present a framework, which maps the feature-based model of similarity into the information theoretic domain. A new way of computing IC values directly from an ontology structure is also introduced. This new model, called Extended Information Content (eIC) takes into account the whole set of semantic relations defined in an ontology. The proposed framework enables to rewrite existing similarity measures that can be augmented to compute semantic relatedness. Upon this framework, a new measure called FaITH (Feature and Information THeoretic) has been devised. Extensive experimental evaluations confirmed the suitability of the framework.".
• 61 abstract "Increasingly huge RDF data sets are being published on theWeb. Currently, they use different syntaxes of RDF, contain high levels of redundancy and have a plain indivisible structure. All this leads to fuzzy publications, inefficient management, complex processing and lack of scalability. This paper presents a novel RDF representation (HDT) which takes advantage of the structural properties of RDF graphs for splitting and representing, efficiently, three components of RDF data: Header, Dictionary and Triples structure. On-demand management operations can be implemented on top of HDT representation. Experiments show that data sets can be compacted in HDT by more than fifteen times the current naive representation, improving parsing and processing while keeping a consistent publication scheme. For exchanging, specific compression techniques over HDT improve current compression solutions.".
• 66 abstract "Biomedical ontologies and semantic web policy languages based on description logics (DLs) provide fresh motivations for extending DLs with nonmonotonic inferences - a topic that has attracted a significant amount of attention along the years. Despite this, nonmonotonic inferences are not yet supported by the existing DL engines. One reason is the high computational complexity of the existing decidable fragments of nonmonotonic DLs. In this paper we identify a fragment of circumscribed $\EL^\bot$ that supports attribute inheritance with specificity-based overriding (much like an object-oriented language), and such that reasoning about default attributes is in P.".
• 70 abstract "RDF(S) and OWL 2 currently support only static ontologies. In practice, however, the truth of statements often changes with time, and Semantic Web applications often need to represent such changes and reason about them. In this paper we present a logic-based approach for representing validity time in RDF and OWL. Unlike the existing proposals, our approach is applicable to entailment relations that are not deterministic, such as the Direct Semantics or the RDF-Based Semantics of OWL 2.We also extend SPARQL to temporal RDF graphs and present a query evaluation algorithm. Finally, we present an optimization of our algorithm that is applicable to entailment relations characterized by a set of deterministic rules, such RDF(S) and OWL 2 RL/RDF entailment.".
• 83 abstract "The Web of Data is increasingly becoming an important infrastructure for such diverse sectors as entertainment, government, e-commerce and science. As a result, the robustness of this Web of Data is now crucial. Prior studies show that the Web of Data is strongly dependent on a small number of central hubs, making it highly vulnerable to single points of failure. In this paper, we present concepts and algorithms to analyse and repair the brittleness of the Web of Data. We apply these on a substantial subset of it, the 2010 Billion Triple Challenge dataset. We first distinguish the physical structure of the Web of Data from its semantic structure. For both of these structures, we then calculate their robustness, taking betweenness centrality as a robustness-measure. To the best of our knowledge, this is the first time that such robustness-indicators have been calculated for the Web of Data. Finally, we determine which links should be added to the Web of Data in order to improve its robustness most effectively. We are able to determine such links by interpreting the question as a very large optimisation problem and deploying an evolutionary algorithm to solve this problem. We believe that with this work, we offer an effective method to analyse and improve the most important structure that the Semantic Web community has constructed to date.".
• 84 abstract "Several projects have brought rich data semantics to collaborative wikis, but blogging platforms remain primarily limited to text. As blogs comprise a significant portion of the web's content, engagement of the blogging community is crucial to the development of the semantic web. We provide a study of blog content to show a latent need for better data publishing and visualization support in blogging software. We then present DataPress, an extension to the WordPress blogging platform that enables users to publish, share, aggregate, and visualize structured information using the same workflow that they already apply to text-based content. In particular, we aim to preserve those attributes that make blogs such a successful publication medium: one-click access to the information, one-click publishing of it, natural authoring interfaces, and easy copy and paste of information (and visualizations) from other sources. We reflect on how our designs make progress toward these goals with a study of how users who installed DataPress made use of various features.".
• 900 abstract "The Open Graph protocol enables any web page to become a rich object in a social graph. It was created by Facebook but designed to be generally useful to anyone. While many different technologies and schemas exist and could be combined together, there is not a single technology which provides enough information to richly represent any web page within the social graph. The Open Graph protocol builds on these existing technologies and gives developers one thing to implement. Developer simplicity is a key goal of the Open Graph protocol which has informed many of the technical design decisions. This talk will explore the motivation of the Open Graph protocol and the design decisions which went into creating it.".
• 901 abstract "It is no doubt that search is critical to the web. And I believe it will be of similar importance to the semantic web. Once you are talking about searching from billions of objects, it will be impossible to always give a single right result, no matter how intelligent the search engine is. Instead, a set of possible results will be provided for the user to choose from. Moreover, if we consider the trade-off between the system costs of generating a single right result and a set of possible results, we may choose the latter. This will naturally lead to the question of how to decide on and present the set to the user and how to evaluate the outcome. In this presentation, I will talk about some new results in the methodology and technology developed for evaluation of web search technologies and systems. As we know, the dominant method for evaluating search engines is the Cranfield paradigm, which employs a test collection to qualify the systems' performance. However, the modern search engines are much different than the traditional information retrieval systems when the Cranfield paradigm was proposed: 1. Mostmodernsearchengineshavemuchmorefeatures,suchasquery-dependent document snippets and query suggestions, and the quality of such features can affect the users' effectiveness to find out useful information; 2. The document collections used in search engines are much larger than ever, so the complete test collection that contain all query-document judgments is not available. As response to the above differences and difficulties, the evaluation based on implicit feedback is a promising alternative methodology employed in IR evaluation. With this approach, no extra human effort is required to judge the querydocument relevance. Instead, such judgments information can be automatically predicted from real users' implicit feedback data. There are three key issues in this methodology: 1. How to predict the query-document relevance and other useful features that useful to qualify the search engine performance; 2. If the complete "judgments" are not available, how can we efficiently collect the most critical information that can determine the system performance; 3. Because more than query-document relevance features can affect the performance, how can they integrate to be a good metric to predict the system performance. We will show a set of technologies dealing with these issues. While semantic web search may present different requirements from web search, evaluation of any search technology will be inevitable. As such, I hope the materials covered in the talk will benefit some of you in semantic web community in the future.".
• 902 abstract "At last year's International Semantic Web Conference, The New York Times Company announced the release of our Linked Open Data Platform available at http://data.nytimes.com. In the subsequent year, we have continued our efforts in this space and learned many valuable lessons. In our remarks, we will review these lessons; demonstrate innovative prototypes built on our linked data; explore the future of RDF and RDFa in the News Industry and announce an exciting new milestone in our Linked Data efforts.".
• 903 abstract "Are we in the semantic web/linked data community effectively attempting to make possible a new literacy - one of data rather than document analysis? By opening up data beyond the now familiar hand crafted Web 2 mash up of data about X plus geography, what are we trying to do, really? Is the goal at least in part to enable net citizens rather than only geeks the ability to pick up, explore, blend, interogate and represent data sources so that we may draw our own statistically informed conclusions about information, and thereby build new knowledge in ways not readily possible before without access to these data seas? If we want citizens rather than just scientists or statisticians or journalists for that matter to be able to pour over data and ask statistically sophisticated questions of comparison and contrast betewen times, places and people, does that mission re-order our research priorities at all? If the goal is to enpower citizens to be able to make use of data, what do we need to make this vision real beyond attending to Tim Berners-Lee's call to "free your data"? The purpose of this talk therefore will be to look at key interaction issues around defining and delivering a useful, usable *data explorotron* for citizens. In particular, we'll consider who is a "citizen user" and what access to and tools for linked data sense making means in this case. From that perspective, we'll consider research issues around discovery, exploration, interrogation and representation of data for not only a single wild data source but especially for multiple wild heterogeneous data sources. I hope this talk may help frame some stepping stones towards useful and usable interaction with linked data, and look forward to input from the community to refine such a new literacy agenda further.".
• paper-01 abstract "In May 2012, the Web search engine Google has introduced the so-called Knowledge Graph, a graph that understands real-world entities and their relationships to one another. Entities covered by the Knowledge Graph include landmarks, celebrities, cities, sports teams, buildings, movies, celestial objects, works of art, and more. The graph enhances Google search in three main ways: by disambiguation of search queries, by search log-based summarization of key facts, and by explorative search suggestions. With this paper, we suggest a fourth way of enhancing Web search: through the addition of realtime coverage of what people say about real-world entities on social networks. We report on a browser extension that seamlessly adds relevant microposts from the social networking sites Google+, Facebook, and Twitter in form of a panel to Knowledge Graph entities. In a true Linked Data fashion, we interlink detected concepts in microposts with Freebase entities, and evaluate our approach for both relevancy and usefulness. The extension is freely available, we invite the reader to reconstruct the examples of this paper to see how realtime opinions may have changed since time of writing.".
• paper-02 abstract "A key objective of multidimensional dataset analysis is to reveal patterns of interest to analysts. However, multidimensional analysis has been observed to be dicult for analysts, due to the challenges of both presenting and navigating large datasets. This work explores how initial summarizations of multidimensional datasets can be generated for consuming parties (designed to reduce the number of data points which would need to be displayed) driven by summarization policies based on provided dataset values. Additionally, functionality for explaining the derivation of summarizations is being developed - in line with prior work on aiding analyst interactions with data processing systems. To help drive development of this work, as well as provide illustrative use cases, we are presently developing a dataset summarization generator as part of greater work being done in the Foresight and Understanding from Scientific Exposition (FUSE) program.".
• paper-03 abstract "Retrieving the causes of road traffic congestions in quasi real-time is an important task that will enable city managers to get better insight into traffic issues and thus take appropriate corrective actions in a timely way. Our work, accepted at ISWC 2012 In-Use track, tackles this problem by integrating and reasoning over a variety of heterogeneous data sources including data streams. In this paper we present an initial prototype of our work for the city of Dublin, Ireland.".
• paper-04 abstract "In order to realize sophisticated medical information systems, many medical ontologies have been developed. We proposed a definition of disease based on River Flow Model which captures a disease as a causal chain of clinical disorders. We also developed a disease ontology based on the model. It includes definitions of more than 6,000 diseases with 17,000 causal relationships. This demonstration summarizes the disease ontology and a browsing system for causal chains defined in it.".
• paper-05 abstract "Recently more and more structured data in form of RDF triples have been published and integrated into Linked Open Data (LOD). While the current LOD contains hundreds of data sources with billions of triples, it has a small number of distinct relations compared with the large number of entities. On the other hand, Web pages are growing rapidly, which results in much larger number of textual contents to be exploited. With the popularity and wide adoption of open information extraction technology, extracting entities and relations among them from text at the Web scale is possible. In this paper, we present an approach to extract the subject individuals and the object counterparts for the relations from text and determine the most appropriate domain and range as well as the most confident dependency path patterns for the given relation based on the EM algorithm. As a preliminary results, we built a knowledge base for relations extracted from Chinese encyclopedias. The experimental results show the effectiveness of our approach to extract relations with reasonable domain, range and path pattern restrictions as well as high-quality triples.".
• paper-06 abstract "This demo enables the automatic creation of semantically annotated YouTube media fragments. A video is first ingested in the Synote system and a new method enables to retrieve its associated subtitles or closed captions. Next, NERD is used to extract named entities from the transcripts which are then temporally aligned with the video. The entities are disambiguated in the LOD clound and a user interface enables to browse through the entities detected in a video or get more information. We evaluated our application with 60 videos from 3 YouTube channels.".
• paper-07 abstract "In this paper we present a demo for efficient detecting of visitor’s attention in museum environment based on the application of intelligent complex event processing and semantic technologies. The detection takes advantage of semantics: (i) in design time for the correlation of sensors’ data via modeling of the interesting situations and annotation of artworks and their parts and (ii) in real-time for the more accurate and precise detection of the interesting situation. The results of the proposed approach have been applied in the EU project ARtSENSE.".
• paper-08 abstract "The ability to compute the differences that exist between two RDF/S Knowledge Bases (KBs) is important for aiding humans to understand the evolution of knowledge, and for reducing the amount of data that need to be exchanged and managed over the network in order to build synchronization, versioning and replication services. We will show how we can exploit blank node anonymity in order to reduce the delta size when comparing RDF/S KBs. We will show experimental results over real and synthetic data sets that demonstrate significant reductions of the sizes of the computed deltas, and how the reduced deltas can be visualized. (This demo paper accompanies a research paper accepted for ISWC'2012)".
• paper-09 abstract "Modern ontology debugging methods allow efficient identification and localization of faulty axioms defined by a user while developing an ontology. However, in many use cases such as ontology alignment the ontologies might include many conflict sets, i.e. sets of axioms preserving the faults, thus making ontology diagnosis infeasible. In this paper we present a debugging approach based on a direct computation of diagnoses that omits calculation of conflict sets. Embedded in an ontology debugger, the proposed algorithm is able to identify diagnoses for an ontology which includes a large number of faults and for which application of standard diagnosis methods fails. The evaluation results show that the approach is practicable and is able to identify a fault in adequate time.".
• paper-10 abstract "We demonstrate the DiscOU engine implementing a resource discovery approach where the textual components of open educational resources are automatically annotated with relevant entities (using a named entity recognition system), so that these rich annotations can be searched by similarity, based on existing resources of interest.".
• paper-11 abstract "This paper introduces a Linked Data application for automatically generating a story between two concepts in the Web of Data, based on formally described links. A path between two concepts is obtained by querying multiple linked open datasets; the path is then enriched with multimedia presentation material for each node in order to obtain a full multimedia presentation of the found path.".
• paper-12 abstract "The main goal of current Web navigation languages is to retrieve set of nodes reachable from a given node. No information is provided about the fragments of the Web navigated to reach these nodes. In other words, information about their connections is lost. This paper presents an efficient algorithm to extract relevant parts of these Web fragments and shows the importance of producing subgraphs besides of sets of nodes. We discuss examples with real data using an implementation of the algorithm in the EXpRESs tool.".
• paper-13 abstract "Smart environments require collaboration of multi-platform sensors operated by multiple parties. Proprietary event processing solutions do not have enough interoperation flexibility, easily leading to overlapping functions wasting hardware and software resources as well as data communications. Our goal is to verify the applicability of standard-compliant SPARQL for any complex event processing task. If found feasible, semantic web methods RDF, SPARQL and OWL have the built-in support for interconnecting disjoint vocabularies, enriching event information with linked open data and reasoning over semantically annotated content, yielding a very flexible event processing environment. Our approach is designed to meet these requirements. Our INSTANS platform based on continuous execution of interconnected SPARQL queries using the Rete-algorithm is a new approach showing improved performance for event processing tasks over current SPARQL-based solutions.".
• paper-14 abstract "Lack of scalability is one of the most significant problems faced by single machine RDF data stores. The advent of Cloud Computing and related tools and technologies has paved a way for a distributed ecosystem of RDF triple stores that can potentially allow up to a planet scale storage along with distributed query processing capabilities. Towards this end, we present Jena-HBase, a HBase backed triple store that can be used with the Jena framework. Jena-HBase provides end-users with a scalable storage and querying solution that supports all features from the RDF specification.".
• paper-15 abstract "As part of LOD2 project and OpenData.cz initiative, we are developing an ODCleanStore framework enabling management of Linked Data. In this paper, we focus on the query-time data fusion in ODCleanStore, which provides data consumers with integrated views on Linked Data; the fused data (1) has solved conflicts according to the preferred conflict resolution policies and (2) is accompanied with provenance and quality scores, so that the consumers can judge the usefulness and trustworthiness of the data for their task at hand.".
• paper-16 abstract "While there are many tools and services which support the exploration of research data, by and large these tend to provide a limited set of functionalities, which cover primarily ranking measures and mechanisms for relating authors, typically on the basis of simple co-authorship relations. To try and improve over the current state of affairs, we are developing a novel tool for exploring research data, which is called Rexplore. Rexplore builds on an intelligent algorithm for automatically identifying hierarchical and equivalence relations between research areas, to provide a variety of functionalities and visualizations to help users to make sense of a research area. These include visualizations to detect trends in research; ways to cluster authors according to several dynamic similarity measures; and fine-grained mechanisms for ranking authors, taking into account parameters such as ranking criterion, career stage, calendar years, publication venues, etc.".
• paper-17 abstract "Recently, with the ever-growing of textual medicine records, annotating domain entities has been regarded as an important task in the biomedical field. On the other hand, the process of interlinking open data sources is actively pursued within the Linking Open Data (LOD) project. The number of entities and the number of properties describing semantic relationships between entities within the linked data cloud are very large. In this paper, we propose a knowledge-incentive approach based on LOD for entity annotation in the biomedical field. With this approach, we implement MeDetect, a prototype system to solve the problems mentioned above. The experimental results verify the effectiveness and efficiency of our approach.".
• paper-18 abstract "Annotations of clinical trials with controlled vocabularies of drugs and diseases, encode scientific knowledge that can be mined to discover relationships between scientific concepts. We present PAnG (Patterns in Annotation Graphs), a tool that relies on dense subgraphs, graph summarization and taxonomic distance metrics, computed using the NCI Thesaurus, to identify patterns.".
• paper-19 abstract "In this demo we present ourSpaces, a semantic Virtual Research Environment designed to support inter-disciplinary research teams. The system utilizes technologies such as OWL, RDF and a rule-based reasoner to support the management of provenance information, social networks, online communication and policy enforcement within the VRE.".
• paper-20 abstract "We present QAKiS, a system for open domain Question Answering over linked data. It addresses the problem of question interpretation as a relation-based match, where fragments of the question are matched to binary relations of the triple store, using relational textual patterns automatically collected. For the demo, the relational patterns are automatically extracted from Wikipedia, while DBpedia is the RDF data set to be queried using a natural language interface.".
• paper-21 abstract "This paper introduces the ontology mapping approach of a system that automatically integrates data sources into an ontology-based data integration system (OBDI). In addition to the domain and source ontologies, the mapping algorithm requires a SPARQL query to determine the ontology mapping. Further, the mapping algorithm is dynamic; running each time a query is processed and producing only a partial mapping sufficient to reformulate the query. This approach enables the mapping algorithm to exploit query semantics to correctly choose among ontology mappings that are indistinguishable when only the ontologies are considered. Also, the mapping associates paths with paths, instead of entities with entities. This approach simplifies query reformulation. The sys- tem achieves favorable results when compared to the algorithms developed for Clio, the best automated relational data integration system.".
• paper-22 abstract "In this demo we introduce Quest, a new system that provides SPARQL query answering with support for OWL~2~QL and RDFS entailments. Quest allows to link the vocabulary of an ontology to the content of a relational database through mapping axioms. These are then used together with the ontology to answer a SPARQL query by means of a single SQL query that is executed over the database. Quest uses highly-optimised query rewriting techniques to generate the SQL query which not only takes into account the entailments of the ontology and data, but is also 'lean' and simple so that it can be executed efficiently by any SQL engine. Quest supports commercial and open source databases, including database federation tools like Teiid to allow for Ontology Based Data Integration of relational and other sources (e.g., CSV, Excel, XML). Here we will briefly describe Quest mapping language, the query answering process and the most relevant optimisation techniques used by the system. We will conclude with a brief description of the content of this demo.".
• paper-23 abstract "TELEIOS is a recent European project that addresses the need for scalable access to petabytes of Earth Observation data and the discovery and exploitation of knowledge that is hidden in them. In this demo paper we demonstrate a fire monitoring service that we have implemented in context of the project TELEIOS and explain how Semantic Web and Linked Data technologies allow the service to go beyond relevant services currently deployed in various Earth Observation data centers.".
• paper-24 abstract "Although it appears that reasoning in RDFS is embarrassingly parallel, this is not the case. Because all vocabulary is treated the same way in RDF, it is possible to extend the RDFS ontology vocabulary. The ability permits the creation of useful constructs that are not amenable to parallelism, and that in the end require serial processing.".
• paper-25 abstract "Interactive ontology debugging incorporates a user who answers queries about entailments of their intended ontology. In order to minimize the amount of user interaction in a debugging session, a user must choose an appropriate query selection strategy. However, the choice of an unsuitable strategy may result in tremendous overhead in terms of time and cost. We present a learning method for query selection which unites the advantages of existing approaches while overcoming their flaws. Our tests show the utility of our approach when applied to a large set of real-world ontologies, its scalability and adequate reaction time allowing for continuous interactivity.".
• paper-26 abstract "The Semantic Vernacular System is a novel naming system for creating named, machine-interpretable descriptions for groups of organisms. Unlike the traditional scientific naming system, which is based on evolutionary relationships, it emphasizes the observable features of organisms. By independently naming the descriptions composed of sets of observational features, as well as maintaining connections to scientific names, it preserves the observational data used to identify organisms. The system is designed to support a peer-review mechanism for creating new names, and uses a controlled vocabulary encoded in the Web Ontology Language to represent the observational features. A prototype of the system is currently under development in collaboration with the Mushroom Observer website. It allows users to propose new names and descriptions, provide feedback on those proposals, and ultimately have them formally approved. This effort aims at offering the mycology community a knowledge base of fungal observational features and a tool for identifying fungal observations.".
• paper-27 abstract "The Web Ontology Language (OWL) is a commonly used standard for creating ontology artifacts. However, its capabilities for reusing existing OWL artifacts in the creation of new artifacts is limited to the import of whole ontologies, even when only a small handful of classes, object properties, and so on (which we refer to generically as OWL components) are relevant. This situation can result in extremely large and unwieldy, or even broken, ontologies. To address this problem while still promoting ontology reuse, the OBI Consortium has elucidated the Minimum Information to Reference an External Ontology Term (MIREOT). We provide a suite of plugins to the Protege editor that greatly simplifies the use of MIREOT principles during ontology creation and editing.".
• paper-28 abstract "Heterogeneity of ontologies on the web of data is very important problem. To solve this problem, there are a lot of researches about ontology mapping/alignment/matching. This paper shows an application called “SPARQLoid” that is using a query rewriting method to enable the users to query any SPARQL endpoint with the user’s own ontology even when their mappings are not reliable enough. Often ontology matching is very difficult problem and it sometimes produces mappings under a certain reliability. Based on the given reliability degrees on those mappings, SPARQLoid allows users to query data in the target SPARQL endpoints by using their own (or a specified certain) ontology under a control of sorting order based on their mapping reliability.".
• paper-29 abstract "The potential of the semantic data available in the Web is enormous but in most cases it is very difficult for users to explore and use this data. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. We devise a formal Linked Data Visualization model (LDVM), which allows to dynamically connect data with visualizations.".
• paper-30 abstract "We propose a general framework to attach the licensing terms to the data where the compatibility of the licensing terms concerning the data affected by a query is verified, and, if compatible, the licenses are combined into a composite license. The framework returns the composite license as licensing term about the data resulting from the query.".
• paper-31 abstract "The use of social media has been rapidly increasing in the last years. Social media such as Twitter has become an important source of information for a variety of people. The public availability of data describing some of these social networks has led to a lot of research in this area. Link prediction, user classification and community detection are some of the main research areas related to social networks. In this paper we present a user modeling framework that uses Wikipedia as a frame to model user interests inside a social network. Our fine grained model of user interests reflects the areas a user is interested in as well as the level of expertise a user has in a certain field.".
• paper-01 abstract "Since 2001, the semantic web community has been working hard towards creating standards which will increase the accessibility of available information on the web. Yahoo research recently reported that 30% of all HTML pages contain structured data such as microdata, RDFa, or microformat. Although multilinguality of the web is a hurdle in information access, the rapid growth of the semantic web enables us to retrieve fine grained information across the language barrier. In this thesis, firstly, we focus on developing a methodology to perform cross-lingual semantic search over structured data (knowledge base), by transforming natural language queries into SPARQL. Secondly, we focus on improving the semantic similarity and relatedness measures, to overcome the semantic gap between the vocabulary in the knowledge base and the terms appearing in the query. The preliminary results are evaluated against the QALD-2 test dataset, which achieved a F1 score of 0.46, an average precision of 0.44, and an average recall of 0.48.".
• paper-02 abstract "Assessing the quality of data published on the Web has been identified as an essential step in selecting reliable information for use in tasks such as decision making. This paper discusses a quality assessment framework based on semantic web technologies and outlines a role for provenance in supporting and documenting such assessments.".
• paper-03 abstract "Personalization techniques aim at helping people dealing with the ever growing amount of information by filtering it according to their interests. However, to avoid the information overload, such techniques often create an over-personalization effect, i.e. users are exposed only to the content systems assume they would like. To break this "personalization bubble" we introduce the notion of serendipity as a performance measure for recommendation algorithms. For this, we first identify aspects from the user perspective, which can determine level and type of serendipity desired by users. Then, we propose a user model that can facilitate such user requirements, and enables serendipitous recommendations. The use case for this work focuses on TV recommender systems, however the ultimate goal is to explore the transferability of this method to different domains. This paper covers the work done in the first eight months of research and describes the plan for the entire PhD trajectory.".
• paper-04 abstract "Provenance is an increasingly important aspect of data management that is often underestimated and neglected by practitioners. In our work, we target the problem of reconstructing provenance of files in a shared folder setting, assuming that only standard filesystem metadata are available. We propose a content-based approach that is able to reconstruct provenance automatically, leveraging several similarity measures and edit distance algorithms, adapting and integrating them into a multi-signal pipeline. We discuss our research methodology and show some promising preliminary results.".
• paper-05 abstract "Due to recent developments in reasoning algorithms of the various OWL profiles, the classification time for an ontology has come down drastically. For all of the popular reasoners, in order to process an ontology, an implicit assumption is that the ontology should fit in primary memory. The memory requirements for a reasoner are already quite high, and considering the ever increasing size of the data to be processed and the goal of making reasoning Web scale, this assumption becomes overly restrictive. In our work, we study several distributed classification approaches for the description logic EL+ (a fragment of OWL 2 EL profile). We present the lessons learned from each approach, our current results, and plans for future work.".
• paper-06 abstract "With the Semantic Web scaling up, and more triple-stores with update facilities being available, the need for higher levels of simultaneous triple-stores with identical information becomes more and more urgent. However, where such Data Replication approaches are common in the database community, there is no comprehensive approach for data replication for the Semantic Web. In this research proposal, we will discuss the problem space and scenarios of data replication in the Semantic Web, and explain how we plan on dealing with this issue.".
• paper-07 abstract "Due to the decentralized nature of the Semantic Web, the same real world entity may be described in various data sources and assigned syntactically distinct identifiers. In order to facilitate data utilization in the Semantic Web, without compromising the freedom of people to publish their data, one critical problem is to appropriately interlink such heterogeneous data. This interlinking process can also be referred to as Entity Coreference, i.e., finding which identifiers refer to the same real world entity. This proposal will investigate algorithms to solve this entity coreference problem in the Semantic Web in several aspects. The essence of entity coreference is to compute the similarity of instance pairs. Given the diversity of domains of existing datasets, it is important that an entity coreference algorithm be able to achieve good precision and recall across domains represented in various ways. Furthermore, in order to scale to large datasets, an algorithm should be able to intelligently select what information to utilize for comparison and determine whether to compare a pair of instances to reduce the overall complexity. Finally, appropriate evaluation strategies need to be chosen to verify the effectiveness of the algorithms.".
• paper-08 abstract "Data streams are being continually generated in diverse application domains such as traffic monitoring, smart buildings, and so on. Stream Reasoning is the area that aims to combine reasoning techniques with data streams. In this paper, we present our approach to enable rule-based reasoning on semantic data streams using data flow networks in a distributed manner.".
• paper-09 abstract "Designing domain ontologies from scratch is a time-consuming endeavor requiring a lot of close collaboration with domain experts. However, domain descriptions such as XML Schemas are often available in early stages of the ontology development process. For my dissertation, I propose a method to convert XML Schemas to OWL ontologies in an automatic way. The approach addresses the transformation of any XML Schema documents by using the XML Schema metamodel, which is completely represented by the XML Schema Metamodel Ontology. Automatically, all Schema declarations and definitions are converted to class axioms, which are intended to be enriched with additional domain-specific semantic information in form of domain ontologies.".
• paper-10 abstract "In this paper, we present a doctoral thesis which introduces a new approach of time series enrichment with semantics. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing users. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.".
• paper-11 abstract "In real world cases, building reliable problem centric views over Linked Data is a challenging task. An ideal method should include a formal representation of the requirements of the needed dataset and a controlled process moving from the original sources to the outcome. We believe that a goal oriented approach, similar to the AI planning problem, could be successful in controlling the process of linked data fusion, as well as to formalize the relations between requirements, process and result.".
• paper-12 abstract "Knowledge interaction in Web context is a challenging problem. For instance, it requires to deal with complex structures able to filter knowledge by drawing a meaningful context boundary around data. We assume that these complex structures can be formalized as Knowledge Patterns (KPs), aka frames. This Ph.D. work is aimed at developing methods for extracting KPs from the Web and at applying KPs to exploratory search tasks. We want to extract KPs by analyzing the structure of Web links from rich resources, such as Wikipedia.".
• paper-13 abstract "Complex event processing is currently done primarily with proprietary definition languages. Future smart environments will require collaboration of multi-platform sensors operated by multiple parties. The goal of my research is to verify the applicability of standard-compliant SPARQL for complex event processing tasks. If successful, semantic web standards RDF, SPARQL and OWL with their established base of tools have many other benefits for event processing including support for interconnecting disjoint vocabularies, enriching event information with linked open data and reasoning over semantically annotated content. A software platform capable of continuous incremental evaluation of multiple parallel SPARQL queries is a key enabler of the approach.".
• paper-14 abstract "A pair of RDF instances are said to corefer when they are intended to denote the same thing in the world, for example, when two nodes of type foaf:Person describe the same individual. This problem is central to integrating and inter-linking semi-structured datasets. We are developing an online, unsupervised coreference resolution framework for heterogeneous, semi-structured data. The online aspect requires us to process new instances as they appear and not as a batch. The instances are heterogeneous in that they may contain terms from different ontologies whose alignments are not known in advance. Our framework encompasses a two-phased clustering algorithm that is both flexible and distributable, a probabilistic multidimensional attribute model that will support robust schema mappings, and a consolidation algorithm that will be used to perform instance consolidation in order to improve accuracy rates over time by addressing data sparseness.".
• paper-15 abstract "We address the problem of developing a scalable composition framework for Linked Data-based services, which retains the advantages of the loose coupling fostered by REST.".
• paper-16 abstract "Linked Stream Data, i.e., the RDF data model extended for representing stream data generated from sensors social network applications, is gaining popularity. This has motivated considerable work on developing corresponding data models associated with processing engines. However, current implemented engines have not been thoroughly evaluated to assess their capabilities. For reasonable systematic evaluations, in this work we propose a novel, customizable evaluation framework and a corresponding methodology for realistic data generation, system testing, and result analysis. Based on this evaluation environment, extensive experiments have been conducted in order to compare the state-of-the-art LSD engines wrt. qualitative and quantitative properties, taking into account the underlying principles of stream processing. Consequently, we provide a detailed analysis of the experimental outcomes that reveal useful findings for improving current and future engines.".
• paper-17 abstract "We present a question answering system architecture which processes natural language questions in a pipeline consisting of five steps: i) question parsing and query template generation, ii) lookup in an inverted index, iii) string similarity computation, iv) lookup in a lexical database in order to find synonyms, and v) semantic similarity computation. These steps are ordered with respect to their computational effort, following the idea of layered processing: questions are passed on along the pipeline only if they cannot be answered on the basis of earlier processing steps, thereby invoking computationally expensive operations only for complex queries that require them. In this paper we present an evaluation of the system on the dataset provided by the 2nd Open Challenge on Question Answering over Linked Data (QALD-2). The main, novel contribution is a systematic empirical investigation of the impact of the single processing components on the overall performance of question answering over linked data.".
• paper-18 abstract "We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., concepts) directly from a collaborative, user-driven ontology. We compare the effectiveness of a series of approaches to select the best tags ranging from traditional IR techniques such as TF/IDF weighting to novel techniques based on ontological distances and latent Dirichlet allocation. All our experiments are run against a real corpus of tags and documents extracted from the ScienceWise portal, which is connected to ArXiv.org and is currently used by growing number of researchers. The datasets for the experiments are made available online for reproducibility purposes.".
• paper-19 abstract "Usability and user satisfaction are of paramount importance when designing interactive software solutions. Furthermore, the optimal design can be dependent not only on the task but also on the type of user. Evaluations can shed light on these issues; however, very few studies have focused on assessing the usability of semantic search systems. As semantic search becomes mainstream, there is growing need for standardised, comprehensive evaluation frameworks. In this study, we assess the usability and user satisfaction of different semantic search query input approaches (natural language and view-based) from the perspective of different user types (experts and casuals). Contrary to previous studies, we found that casual users preferred the form-based query approach whereas expert users found the graph-based to be the most intuitive. Additionally, the controlled-language model offered the most support for casual users but was perceived as restrictive by experts, thus limiting their ability to express their information needs.".
• paper-20 abstract "Testbeds proposed so far to evaluate, compare, and eventually improve SPARQL query federation systems have still some limitations. Some variables and configurations that may have an impact on the behavior of these systems (e.g., network latency, data partitioning and query properties) are not sufficiently defined; this affects the results and repeatability of independent evaluation studies, and hence the insights that can be obtained from them. In this paper we evaluate FedBench, the most comprehensive testbed up to now, and empirically probe the need of considering additional dimensions and variables. The evaluation has been conducted on three SPARQL query federation systems, and the analysis of these results has allowed to uncover properties of these systems that would normally be hidden with the original testbeds.".
• paper-21 abstract "This paper presents an evaluation of state of the art black box justification finding algorithms on the NCBO BioPortal ontology corpus. This corpus represents a set of naturally occurring ontologies that vary greatly in size and expressivity. The results paint a picture of the performance that can be expected when finding all justifications for entailments using black box justification finding techniques. The results also show that many naturally occurring ontologies exhibit a rich justificatory structure, with some ontologies having extremely high numbers of justifications per entailment.".
• paper-22 abstract "In recent years, strategies for Linked Data consumption have caught attention in Semantic Web research. For direct consumption by users, Linked Data mashups, interfaces, and visualizations have become a popular research area. Many approaches in this field aim to make Linked Data interaction more user friendly to improve its accessibility for nontechnical users. A subtask for Linked Data interfaces is to present entities and their properties in a concise form. In general, these summaries take individual attributes and sometimes user contexts and preferences into account. But the objective evaluation of the quality of such summaries is an expensive task. In this paper we introduce a game-based approach aiming to establish a ground truth for the evaluation of entity summarization. We exemplify the applicability of the approach by evaluating two recent summarization approaches.".
• paper-23 abstract "In this paper we present the Quonto Inconsistent Data handler (QuID). QuID is a reasoner for OWL 2 QL that is based on the system Quonto and is able to deal with inconsistent ontologies. The central aspect of QuID is that it implements two different, orthogonal strategies for dealing with inconsistency: ABox repairing techniques, based on data manipulation, and consistent query answering techniques, based on query rewriting. Moreover, by exploiting the ability of Quonto to delegate the management of the ABox to a relational database system (DBMS), such techniques are potentially able to handle very large inconsistent ABoxes. For the above reasons, QuID allows for experimentally comparing the above two different strategies for inconsistency handling in the context of OWL 2 QL. We thus report on the experimental evaluation that we have conducted using QuID. Our results clearly point out that inconsistency-tolerance in OWL 2 QL ontologies is feasible in practical cases. Moreover, our evaluation singles out the different sources of complexity for the data manipulation technique and the query rewriting technique, and allows for identifying the conditions under which one method is more efficient than the other.".
• paper-24 abstract "This paper proposes to apply semantic technologies in a new domain, Field research. It is said that if "raw data" is openly available on the Web, it will be used by other people to do wonderful things. But, it would be better to show a use case together with that data, especially in the dawn of LOD. Therefore, we are proceeding with both of LOD content generation and its application for a specific domain. The application addresses an issue of information retrieval in the field, and the mechanism of LOD generation from the Web might be applied to the other domain. Firstly, we demonstrate the use of our mobile application, which searches a plant fitting the environmental conditions obtained by the smartphone's sensors. Then, we introduce our approach of the LOD generation, and present an evaluation showing its practical effectiveness.".
• paper-25 abstract "Many industrial use cases, such as machine diagnostics, can benefit from embedded reasoning, the task of running knowledge-based reasoning techniques on embedded controllers as widely used in industrial automation. However, due to the memory and CPU restrictions of embedded devices like programmable logic controllers (PLCs), state-of-the-art reasoning tools and methods cannot be easily migrated to industrial automation environments. In this paper, we describe an approach to porting lightweight OWL 2 EL reasoning to a PLC platform to run in an industrial automation environment. We report on initial runtime experiments carried out on a prototypical implementation of a PLC-based EL+ -reasoner in the context of a use case about turbine diagnostics.".
• paper-26 abstract "Robust solutions for ambient assisted living are numerous, yet predominantly specific in their scope of usability. In this paper, we describe the potential contribution of semantic web technologies to building more versatile solutions - a step towards adaptable context-aware engines and simplified deployments. Our conception and deployment work in hindsight, we highlight some implementation challenges and requirements for semantic web tools that would help to ease the development of context-aware services and thus generalize real-life deployment of semantically driven assistive technologies. We also compare available tools with regard to these requirements and validate our choices by providing some results from a real-life deployment.".
• paper-27 abstract "Biomedical ontologies have become a mainstream topic in medical research. They represent important sources of evolved knowledge that may be automatically integrated in decision support methods. Grounding clinical and radiographic findings in concepts defined by a biomedical ontology, e.g., the Human Phenotype Ontology, enables us to compute semantic similarity between them. In this paper, we focus on using such similarity measures to predict disorders on undiagnosed patient cases in the bone dysplasia domain. Different methods for computing the semantic similarity have been implemented. All methods have been evaluated based on their support in achieving a higher prediction accuracy. The outcome of this research enables us to understand the feasibility of developing decision support methods based on ontology-driven semantic similarity in the skeletal dysplasia domain.".
• paper-28 abstract "Semantic annotation of patient data in the skeletal dysplasia domain (e.g., clinical summaries) is a challenging process due to the structural and lexical differences existing between the terms used to describe radiographic findings. In this paper we propose an ontology aimed at representing the intrinsic structure of such radiographic findings in a standard manner, in order to bridge the different lexical variations of the actual terms. Furthermore, we describe and evaluate an algorithm capable of mapping concepts of this ontology to exact or broader terms in the main phenotype ontology used in the bone dysplasia domain.".
• paper-29 abstract "It has become common to use RDF to store the results of Natural Language Processing (NLP) as a graph of the entities mentioned in the text with the relationships mentioned in the text as links between them. These NLP graphs can be measured with Precision and Recall against a ground truth graph representing what the documents actually say. When asking conjunctive queries on NLP graphs, the Recall of the query is expected to be roughly the product of the Recall of the relations in each conjunct. Since Recall is typically less than one, conjunctive query Recall on NLP graphs degrades geometrically with the number of conjuncts. We present an approach to address this Recall problem by hypothesizing links in the graph that would improve query Recall, and then attempting to find more evidence to support them. Using this approach, we confirm that in the context of answering queries over NLP graphs, we can use lower confidence results from NLP components if they complete a query result.".
• paper-30 abstract "Our work is settled in the context of the public administration domain, where data can come from different entities, can be produced, stored and delivered in different formats and can have different levels of quality. Hence, such a heterogeneity has to be addressed, while performing various data integration tasks. We report our experimental work on publishing some government linked open geo-metadata and geo-data of the Italian Trentino region. Specifically, we illustrate how 161 core geographic datasets were released by leveraging on the geo-catalogue application within the existing geo-portal. We discuss the lessons we learned from deploying and using the application as well as from the released datasets.".
• paper-31 abstract "Questions often explicitly request a particular type of answer. One popular approach to answering natural language questions involves filtering candidate answers based on precompiled lists of instances of common answer types (e.g., countries, animals, foods, etc.). Such a strategy is poorly suited to an open domain in which there is an extremely broad range of types of answers, and the most frequently occurring types cover only a small fraction of all answers. In this paper we present an alternative approach called TyCor, that employs soft filtering of candidates using multiple strategies and sources. We find that TyCor significantly outperforms a single-source, single-strategy hard filtering approach, demonstrating both that multi-source multi-strategy outperforms a single source, single strategy, and that its fault tolerance yields significantly better performance than a hard filter.".
• paper-32 abstract "The success of pervasive computing depends on the ability to compose a multitude of networked applications dynamically in order to achieve user goals. However, applications from different providers are not able to interoperate due to incompatible interaction protocols or disparate data models. Instant messaging is a representative example of the current situation, where various competing applications keep emerging. To enforce interoperability at runtime and in a non-intrusive manner, mediators are used to perform the necessary translations and coordination between the heterogeneous applications. Nevertheless, the design of mediators requires considerable knowledge about each application as well as a substantial development effort. In this paper we present an approach based on ontology reasoning and model checking in order to generate correct-by-construction mediators automatically. We demonstrate the feasibility of our approach through a prototype tool and show that it synthesises mediators that achieve efficient interoperation of instant messaging applications.".
• paper-33 abstract "In this paper, we present QuerioCity, a platform to catalog, index and query highly heterogenous information coming from complex systems, such as cities. A series of challenges are identified: namely, the heterogeneity of the domain and the lack of a common model, the volume of information and the number of data sets, the requirement for a low entry threshold to the system, the diversity of the input data, in terms of format, syntax and update frequency (streams vs static data), and the sensitivity of the information. We propose an approach for incremental and continuous integration of static and streaming data, based on Semantic Web technologies. The proposed system is unique in the literature in terms of handling of multiple integrations of available data sets in combination with flexible provenance tracking, privacy protection and continuous integration of streams. We report on lessons learnt from building the first prototype for Dublin.".
• paper-34 abstract "The LOD2 Stack is an integrated distribution of aligned tools which support the whole life cycle of Linked Data from extraction, authoring/creation via enrichment, interlinking, fusing to maintenance. The LOD2 Stack comprises new and substantially extended existing tools from the LOD2 project partners and third parties. The stack is designed to be versatile; for all functionality we define clear interfaces, which enable the plugging in of alternative third-party implementations. The architecture of the LOD2 Stack is based on three pillars: (1) Software integration and deployment using the Debian packaging system. (2) Use of a central SPARQL endpoint and standardized vocabularies for knowledge base access and integration between the different tools of the LOD2 Stack. (3) Integration of the LOD2 Stack user interfaces based on REST enabled Web Applications. These three pillars comprise the methodological and technological framework for integrating the very heterogeneous LOD2 Stack components into a consistent framework. In this article we describe these pillars in more detail and give an overview of the individual LOD2 Stack components. The article also includes a description of a real-world usage scenario in the publishing domain.".
• paper-35 abstract "BioPortal is a repository of biomedical ontologies - the largest such repository, with more than 300 ontologies to date. This set includes ontologies that were developed in OWL, OBO and other languages, as well as a large number of medical terminologies that the US National Library of Medicine distributes in its own proprietary format. We have published the RDF based serializations of all these ontologies and their metadata at sparql.bioontology.org. This dataset contains 203M triples, representing both content and metadata for the 300+ ontologies; and 9M mappings between terms. This endpoint can be queried with SPARQL which opens new usage scenarios for the biomedical domain. This paper presents lessons learned from having redesigned several applications that today use this SPARQL endpoint to consume ontological data.".
• paper-36 abstract "In this paper we discuss our experience with the design, development and deployment of the ourSpaces Virtual Research Environment. ourSpaces makes use of Semantic Web technologies to create a platform to support multidisciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to support interaction between users and metadata within the VRE. We discuss the lessons learnt during the deployment process with three case study groups. Finally, we present our conclusions and future directions for exploration in terms of developing ourSpaces further.".
• paper-37 abstract "Diagnosis, or the method to connect causes to its effects, is an important reasoning task for obtaining insight on cities and reaching the concept of sustainable and smarter cities that is envisioned nowadays. This paper, focusing on transportation and its road traffic, presents how road traffic congestions can be detected and diagnosed in quasi real-time. We adapt pure Artificial Intelligence diagnosis techniques to fully exploit knowledge which is captured through relevant semantics-augmented stream and static data from various domains. Our prototype of semantic-aware diagnosis of road traffic congestions, experimented in Dublin Ireland, works efficiently with large, heterogeneous information sources and delivers value-added services to citizens and city managers in quasi real-time.".
• paper-38 abstract "Despite decades of effort, intelligent object search remains elusive. Neither search engine nor semantic web technologies alone have managed to provide usable systems for simple questions such as "Find me a flat with a garden and more than two bedrooms near a supermarket." We introduce DEQA, a conceptual framework that achieves this elusive goal through combining state-of-the-art semantic technologies with effective data extraction. To that end, we apply DEQA to the UK real estate domain and show that it can answer a significant percentage of such questions correctly. DEQA achieves this by mapping natural language questions to SPARQL patterns. These patterns are then evaluated on an RDF database of current real estate offers. The offers are obtained using OXPATH, a state-of-the-art data extraction system, on the major agencies in the Oxford area and linked through LIMES to background knowledge such as the location of supermarkets.".
• paper-39 abstract "Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.".
• paper-40 abstract "To realize the Smart Cities vision, applications can leverage the large availability of open datasets related to urban environments. Those datasets need to be integrated, but it is often hard to automatically achieve a high-quality interlinkage. Human Computation approaches can be employed to solve such a task where machines are ineffective. We argue that in this case not only people's background knowledge is useful to solve the task, but also people's physical presence and direct experience can be successfully exploited. In this paper we present UrbanMatch, a Game with a Purpose for players in mobility aimed at validating links between points of interest and their photos; we discuss the design choices and we show the high throughput and accuracy achieved in the interlinking task.".
• paper-41 abstract "The original vision of the Semantic Web was to encode semantic content on the web in a form with which machines can reason. But in the last few years, we've seen many new Internet-based applications (such as Wikipedia, Linux, and prediction markets) where the key reasoning is done, not by machines, but by large groups of people. This talk will show how a relatively small set of design patterns can help understand a wide variety of these examples. Each design pattern is useful in different conditions, and the patterns can be combined in different ways to create different kinds of collective intelligence. Building on this foundation, the talk will consider how the Semantic Web might contribute to - and benefit from - these more human-intensive forms of collective intelligence.".
• paper-42 abstract "Data.gov, a flagship open government project from the US government, opens and shares data to improve government efficiency and drive innovation. Sharing such data allows us to make rich comparisons that could never be made before and helps us to better understand the data and support decision making. The adoption of open linked data, vocabularies and ontologies, the work of the W3C, and semantic technologies is helping to drive Data.gov and US data forward. This session will help us to better understand the changing global landscape of data sharing and the role the semantic web is playing in it. This session highlights specific data sharing examples of solving mission problems from NASA, the White House, and many other governments agencies and citizen innovators.".
• paper-43 abstract "In the 1990s, as the World Wide Web became not only world wide but also dense and ubiquitous, workers in the artificial intelligence community were drawn to the possibility that the Web could provide the foundation for a new kind of AI. Having survived the AI Winter of the 1980s, the opportunities that they saw in the largest, most interconnected computing platform imaginable were obviously compelling. With the subsequent success of the Semantic Web, however, our community seems to have stopped talking about many of the issues that researchers believe led to the AI Winter in the first place: the cognitive challenges in debugging and maintaining complex systems, the drift in the meanings ascribed to symbols, the situated nature of knowledge, the fundamental difficulty of creating robust models. These challenges are still with us; we cannot wish them away with appeals to the open-world assumption or to the law of large numbers. Embracing these challenges will allow us to expand the scope of our science and our practice, and will help to bring us closer to the ultimate vision of the Semantic Web.".
• paper-01 abstract "An increasing amount of data is published and consumed on the Web according to the Linked Data paradigm. In consideration of both publishers and consumers, the temporal dimension of data is important. In this paper we investigate the characterisation and availability of temporal information in Linked Data at large scale. Based on an abstract definition of temporal information we conduct experiments to evaluate the availability of such information using the data from the 2011 Billion Triple Challenge (BTC) dataset. Focusing in particular on the representation of temporal meta-information, i.e., temporal information associated with RDF statements and graphs, we investigate the approaches proposed in the literature, performing both a quantitative and a qualitative analysis and proposing guidelines for data consumers and publishers. Our experiments show that the amount of temporal information available in the LOD cloud is still very small; several different models have been used on different datasets, with a prevalence of approaches based on the annotation of RDF documents.".
• paper-02 abstract "The amount of data available in the Linked Data cloud continues to grow. Yet, few services consume and produce linked data. There is recent work that allows a user to define a linked service from an online service, which includes the specifications for consuming and producing linked data, but building such models is time consuming and requires specialized knowledge of RDF and SPARQL. This paper presents a new approach that allows domain experts to rapidly create semantic models of services by demonstration in an interactive web-based interface. First, the user provides examples of the service request URLs. Then, the system automatically proposes a service model the user can refine interactively. Finally, the system saves a service specification using a new expressive vocabulary that includes lowering and lifting rules. This approach empowers end users to rapidly model existing services and immediately use them to consume and produce linked data.".
• paper-03 abstract "Time-efficient algorithms are essential to address the complex linking tasks that arise when trying to discover links on the Web of Data. Although several lossless approaches have been developed for this exact purpose, they do not offer theoretical guarantees with respect to their performance. In this paper, we address this drawback by presenting the first Link Discovery approach with theoretical quality guarantees. In particular, we prove that given an achievable reduction ratio r, our Link Discovery approach HR3 can achieve a reduction ratio r'<=r in a metric space where distances are measured by the means of a Minkowski metric of any order p >= 2. We compare HR3 and the HYPPO algorithm implemented in LIMES 0.5 with respect to the number of comparisons they carry out. In addition, we compare our approach with the algorithms implemented in the state-of-the-art frameworks LIMES 0.5 and SILK 2.5 with respect to runtime. We show that HR3 outperforms these previous approaches with respect to runtime in each of our four experimental setups.".
• paper-04 abstract "The lightweight ontology language OWL RL is used for reasoning with large amounts of data. To this end, the W3C standard provides a simple system of deduction rules, which operate directly on the RDF syntax of OWL. Several similar systems have been studied. However, these approaches are usually complete for instance retrieval only. This paper asks if and how such methods could also be used for computing entailed subclass relationships. Checking entailment for arbitrary OWL RL class subsumptions is co-NP-hard, but tractable rule-based reasoning is possible when restricting to subsumptions between atomic classes. Surprisingly, however, this cannot be achieved in any RDF-based rule system, i.e., the W3C calculus cannot be extended to compute all atomic class subsumptions. We identify syntactic restrictions to mitigate this problem, and propose a rule system that is sound and complete for many OWL RL ontologies.".
• paper-05 abstract "Classification is a fundamental reasoning task in ontology design, and there is currently a wide range of reasoners highly optimised for classification of OWL 2 ontologies. There are also several reasoners that are complete for restricted fragments of OWL 2 , such as the OWL 2 EL profile. These reasoners are much more efficient than fully-fledged OWL 2 reasoners, but they are not complete for ontologies containing (even if just a few) axioms outside the relevant fragment. In this paper, we propose a novel classification technique that combines an OWL 2 reasoner and an efficient reasoner for a given fragment in such a way that the bulk of the workload is assigned to the latter. Reasoners are combined in a black-box modular manner, and the specifics of their implementation (and even of their reasoning technique) are irrelevant to our approach.".
• paper-06 abstract "Detecting, much less understanding, the difference between two description logic based ontologies is challenging for ontology engineers due, in part, to the possibility of complex, non-local logic effects of axiom changes. First, it is often quite difficult to even determine which concepts have had their meaning altered by a change. Second, once a concept change is pinpointed, the problem of distinguishing whether the concept is directly or indirectly affected by a change has yet to be tackled. To address the first issue, various principled notions of ``semantic diff'' (based on deductive inseparability) have been proposed in the literature and shown to be computationally practical for the expressively restricted case of ELHr-terminologies. However, problems arise even for such limited logics as ALC: First, computation gets more difficult, becoming undecidable for logics such as SROIQ which underly the Web Ontology Language (OWL). Second, the presence of negation and disjunction make the standard semantic difference too sensitive to change: essentially, any logically effectual change always affects all terms in the ontology. In order to tackle these issues, we formulate the central notion of finding the minimal change set based on model inseparability, and present a method to differentiate changes which are specific to (thus directly affect) particular concept names. Subsequently we devise a series of computable approximations, and compare the variously approximated change sets over a series of versions of the NCI Thesaurus (NCIt).".
• paper-07 abstract "Most of the semantic content available has been generated automatically by using annotation services for existing content. Automatic annotation is not of sufficient quality to enable focused search and retrieval: either too many or too few terms are semantically annotated. User-defined semantic enrichment allows for a more targeted approach. We developed a tool for semantic annotation of digital documents and conducted an end-user study to evaluate its acceptance by and usability for non-expert users. This paper presents the results of this user study and discusses the lessons learned about both the semantic enrichment process and our methodology of exposing non-experts to semantic enrichment.".
• paper-08 abstract "Modelling and understanding various contexts of users is important to enable personalised selection of Web APIs in directories such as Programmable Web. Currently, relationships between users and Web APIs are not clearly understood and utilized by existing selection approaches. In this paper, we present a semantic model of a Web API directory graph that captures relationships such as Web APIs, mashups, developers, and categories. We describe a novel configurable graph-based method for selection of Web APIs with personalised and temporal aspects. The method allows users to get more control over their preferences and recommended Web APIs while they can exploit information about their social links and preferences. We evaluate the method on a real-world dataset from ProgrammableWeb.com, and show that it provides more contextualised results than currently available popularity based rankings.".
• paper-09 abstract "Tracking user interests over time is important for making accurate recommendations. However, the widely-used time-decay-based approach worsens the sparsity problem because it deemphasizes old item transactions. We introduce two ideas to solve the sparsity problem. First, we divide the users' transactions into epochs i.e. time periods, and identify epochs that are dominated by interests similar to the current interests of the active user. Thus, it can eliminate dissimilar transactions while making use of similar transactions that exist in prior epochs. Second, we use a taxonomy of items to model user item transactions in each epoch. This well captures the interests of users in each epoch even if there are few transactions. It suits the situations in which the items transacted by users dynamically change over time; the semantics behind classes do not change so often while individual items often appear and disappear. Fortunately, many taxonomies are now available on the web because of the spread of the Linked Open Data vision. We can now use those to understand dynamic user interests semantically. We evaluate our method using a dataset, a music listening history, extracted from users' tweets and one containing a restaurant visit history gathered from a gourmet guide site. The results show that our method predicts user interests much more accurately than the previous time-decay-based method.".
• paper-10 abstract "Top-k queries, i.e. queries returning the top k results ordered by a user-defined scoring function, are an important category of queries. Order is an important property of data that can be exploited to speed up query processing. State-of-the-art SPARQL engines underuse order, and top-k queries are mostly managed with a materialize-then-sort processing scheme that computes all the matching solutions (e.g. thousands) even if only a limited number k (e.g. ten) are requested. The SPARQL-RANK algebra is an extended SPARQL algebra that treats order as a first class citizen, enabling efficient split-and-interleave processing schemes that can be adopted to improve the performance of top-k SPARQL queries. In this paper we propose an incremental execution model for SPARQL-RANK queries, we compare the performance of alternative physical operators, and we propose a rank-aware join algorithm optimized for native RDF stores. Experiments conducted with an open source implementation of a SPARQL-RANK query engine based on ARQ show that the evaluation of top-k queries can be sped up by orders of magnitude.".
• paper-11 abstract "The paper presents an approach for cost-based query planning for SPARQL queries issued over an OWL ontology using the OWL Direct Semantics entailment regime of SPARQL 1.1. The costs are based on information about the instances of classes and properties that are extracted from a model abstraction built by an OWL reasoner. A static and a dynamic algorithm are presented which use these costs to find optimal or near optimal execution orders for the atoms of a query. For the dynamic case, we improve the performance by exploiting an individual clustering approach that allows for computing the cost functions based on one individual sample from a cluster. Our experimental study shows that the static ordering usually outperforms the dynamic one when accurate statistics are available. This changes, however, when the statistics are less accurate, e.g., due to non-deterministic reasoning decisions.".
• paper-12 abstract "For Linked Data query engines, there are inherent trade-offs between centralised approaches that can efficiently answer queries over data cached from parts of the Web, and live decentralised approaches that can provide fresher results over the entire Web at the cost of slower response times. Herein, we propose a hybrid query execution approach that returns fresher results from a broader range of sources vs. the centralised scenario, while speeding up results vs. the live scenario. We first compare results from two public SPARQL stores against current versions of the Linked Data sources they cache; results are often missing or out-of-date. We thus propose using coherence estimates to split a query into a sub-query for which the cached data have good fresh coverage, and a sub-query that should instead be run live. Finally, we evaluate different hybrid query plans and split positions in a real-world setup. Our results show that hybrid query execution can improve freshness vs. fully cached results while reducing the time taken vs. fully live execution.".
• paper-13 abstract "We present Tipalo, an algorithm and tool for automatically typing DBpedia entities. Tipalo identifies the most appropriate types for an entity by interpreting its natural language definition, which is extracted from its corresponding Wikipedia page abstract. Types are identified by means of a set of heuristics based on graph patterns, disambiguated to WordNet, and aligned to two top-level ontologies: WordNet supersenses and a subset of DOLCE+DnS Ultra Lite classes. The algorithm has been tuned against a golden standard that has been built online by a group of selected users, and further evaluated in a user study.".
• paper-14 abstract "Existing approaches for link prediction, in the domain of network science, exploit a network's topology to predict future connections by assessing existing edges and connections, and inducing links given the presence of mutual nodes. Despite the rise in popularity of Attention-Information Networks (i.e. microblogging platforms) and the production of content within such platforms, no existing work has attempted to exploit the semantics of published content when predicting network links. In this paper we present an approach that fills this gap by a) predicting follower edges within a directed social network by exploiting concept graphs and thereby significantly outperforming a random baseline and models that rely solely on network topology information, and b) assessing the different behavior that users exhibit when making followee-addition decisions. This latter contribution exposes latent factors within social networks and the existence of a clear need for topical affinity between users for a follow link to be created.".
• paper-15 abstract "Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labeled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.".
• paper-16 abstract "We propose a framework for querying probabilistic instance data in the presence of an OWL2 QL ontology, arguing that the interplay of probabilities and ontologies is fruitful in many applications such as managing data that was extracted from the web. The prime inference problem is computing answer probabilities, and it can be implemented using standard probabilistic database systems. We establish a PTime vs. #P dichotomy for the data complexity of this problem by lifting a corresponding result from probabilistic databases. We also demonstrate that query rewriting (backwards chaining) is an important tool for our framework, show that non-existence of a rewriting into first-order logic implies #P-hardness, and briefly discuss approximation of answer probabilities.".

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