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Freebase

Freebase
Freebase is a large collaborative knowledge base consisting of metadata composed mainly by its community members. It is an online collection of structured data harvested from many sources, including individual 'wiki' contributions.[2] Freebase aims to create a global resource which allows people (and machines) to access common information more effectively. It was developed by the American software company Metaweb and has been running publicly since March 2007. Metaweb was acquired by Google in a private sale announced July 16, 2010.[3] Google's Knowledge Graph is powered in part by Freebase.[4] Freebase data is freely available for commercial and non-commercial use under a Creative Commons Attribution License, and an open API, RDF endpoint, and database dump are provided for programmers. Overview[edit] Described by Tim O'Reilly upon their launch, "Freebase is the bridge between the bottom up vision of Web 2.0 collective intelligence and the more structured world of the semantic web

Visual Data Web - Visually Experiencing the Data Web Data Dumps - Freebase API Data Dumps are a downloadable version of the data in Freebase. They constitute a snapshot of the data stored in Freebase and the Schema that structures it, and are provided under the same CC-BY license. The Freebase/Wikidata mappings are provided under the CC0 license. Freebase Triples The RDF data is serialized using the N-Triples format, encoded as UTF-8 text and compressed with Gzip. < "2001-02"^^< . If you're writing your own code to parse the RDF dumps its often more efficient to read directly from GZip file rather than extracting the data first and then processing the uncompressed data. <subject><predicate><object> . Note: In Freebase, objects have MIDs that look like /m/012rkqx. The subject is the ID of a Freebase object. Topic descriptions often contain newlines. Freebase Deleted Triples The columns in the dataset are defined as: License

YAGO - D5: Databases and Information Systems (Max-Planck-Institut für Informatik) Overview YAGO is a huge semantic knowledge base, derived from Wikipedia WordNet and GeoNames. Currently, YAGO has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities. YAGO is special in several ways: The accuracy of YAGO has been manually evaluated, proving a confirmed accuracy of 95%. YAGO is developed jointly with the DBWeb group at Télécom ParisTech University. Basic Concepts - Freebase API If you are new to Freebase, this section covers the basic terminology and concepts required to understand how Freebase works. Graphs Topics Freebase has over 39 million topics about real-world entities like people, places and things. Since Freebase data is represented a graph, these topics correspond to the nodes in the graph. However, not every node is a topic. Examples of the types of topics found in Freebase: Physical entities, e.g., Bob Dylan, the Louvre Museum, the Saturn planet, to Artistic/media creations, e.g., The Dark Knight (film), Hotel California (song), to Classifications, e.g., noble gas, Chordate, to Abstract concepts, e.g., love, to Schools of thoughts or artistic movements, e.g., Impressionism. Some topics are notable because they hold a lot of data (e.g., Wal-Mart), and some are notable because they link to many other topics, potentially in different domains of information. Types and Properties Any given topic can be seen for many different perspectives for example:

Semantic network Typical standardized semantic networks are expressed as semantic triples. History[edit] Example of a semantic network "Semantic Nets" were first invented for computers by Richard H. Richens of the Cambridge Language Research Unit in 1956 as an "interlingua" for machine translation of natural languages.[2] They were independently developed by Robert F. In the late 1980s, two Netherlands universities, Groningen and Twente, jointly began a project called Knowledge Graphs, which are semantic networks but with the added constraint that edges are restricted to be from a limited set of possible relations, to facilitate algebras on the graph.[12] In the subsequent decades, the distinction between semantic networks and knowledge graphs was blurred.[13][14] In 2012, Google gave their knowledge graph the name Knowledge Graph. Basics of semantic networks[edit] A semantic network is used when one has knowledge that is best understood as a set of concepts that are related to one another. Examples[edit]

Introducing the Knowledge Graph: things, not strings Cross-posted on the Inside Search Blog Search is a lot about discovery—the basic human need to learn and broaden your horizons. But searching still requires a lot of hard work by you, the user. So today I’m really excited to launch the Knowledge Graph, which will help you discover new information quickly and easily. Take a query like [taj mahal]. But we all know that [taj mahal] has a much richer meaning. The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query. Google’s Knowledge Graph isn’t just rooted in public sources such as Freebase, Wikipedia and the CIA World Factbook. The Knowledge Graph enhances Google Search in three main ways to start: 1. 2. How do we know which facts are most likely to be needed for each item? 3.

Mereology Mereology has been axiomatized in various ways as applications of predicate logic to formal ontology, of which mereology is an important part. A common element of such axiomatizations is the assumption, shared with inclusion, that the part-whole relation orders its universe, meaning that everything is a part of itself (reflexivity), that a part of a part of a whole is itself a part of that whole (transitivity), and that two distinct entities cannot each be a part of the other (antisymmetry). A variant of this axiomatization denies that anything is ever part of itself (irreflexive) while accepting transitivity, from which antisymmetry follows automatically. Standard university texts on logic and mathematics are silent about mereology, which has undoubtedly contributed to its obscurity. History[edit] A.N. In 1930, Henry Leonard completed a Harvard Ph.D. dissertation in philosophy, setting out a formal theory of the part-whole relation. Axioms and primitive notions[edit] The axioms are:

untitled Part I. Getting Started Chapter 1. 1.1. rdf:about Sesame 2 ¶ 1.1.1. Sesame is an open source Java framework for storage and querying of RDF data. Of course, a framework isn't very useful without implementations of the various APIs. Originally, Sesame was developed by Aduna (then known as Aidministrator) as a research prototype for the hugely successful EU research project On-To-Knowledge. Sesame is currently developed as a community project, with Aduna as the project leader. 1.1.2. This user manual covers most aspects of working with Sesame in a variety of settings. The basics of programming with Sesame are covered in chapter-repository-api. chapter-http-protocol gives an overview of the structure of the HTTP REST protocol for the Sesame Server, which is useful if you want to communicate with a Sesame Server from a programming language other than Java. Chapter 2. 2.1. Sesame releases can be downloaded from Sourceforge. openrdf-sesame-(version)-sdk.tar.gz. 2.1.1. 2.1.2. 2.2. 2.3. 2.3.1.

Semantic University Semantic University is the largest and most accessible source of educational material relating to semantics and Semantic Web technologies. It includes: Lessons suitable to those brand new to the space. Comparisons, both high-level and in-depth, with related technologies, such as SQL, NoSQL and Big Data. Interactive, hands on tutorials. There's much more, too—learn more about Semantic University. Semantic University content is split into two sections, each with several tracks. Every lesson comes with its own Forum for further discussion.

About Five AKSW Papers at ESWC 2014 Hello World! We are very pleased to announce that five of our papers were accepted for presentation at ESWC 2014. These papers range from natural-language processing to the acquisition of temporal data. AKSW Colloquium “Current semantic web initiatives in the Netherlands” on Friday, March 14, Room P901 Current semantic web initiatives in the Netherlands: Heritage & Location, PiLOD 2.0 On Friday, March 14, at 10.00 a.m. in room P901, visiting researchers Tine van Nierop and Rein van ‘t Veer from the E&L will discuss, amongst several other semantic web initiatives in the Netherlands, two different projects: Heritage & Location (www.erfgoedenlocatie. AKSW Colloquium “Towards a Computer Algebra Semantic Social Network” on Monday, March 17 Towards a Computer Algebra Semantic Social Network On Monday, March 17th, 2014 at 1.30 – 2:30 p.m. in Room P702 (Paulinum), Prof. AKSW Colloquium with Lemon – Lexicon Model for Ontologies on Wednesday, February 26

semanticweb.com - The Voice of Semantic Web Business Tools - Visual Data Web More information on the DBpedia endpoint availability. Several tools have already been developed in the project that showcase the visual power of the Data Web. The following four tools are all implemented in the open source framework Adobe Flex. They are readily configured to access RDF data of the DBpedia and/or Linking Open Data (LOD) projects and only require a Flash Player to be executed (which is usually already installed in Web browsers). Just try out the live demos or watch the screencasts first. If you want to know more about the tools, check out the separate tool pages or get in contact with the developers. Since most DBpedia data has been automatically extracted from Wikipedia and other sources, it cannot be expected to be 100% complete or correct. All tools on this website are research prototypes that might contain errors.

SweoIG/TaskForces/CommunityProjects/LinkingOpenData - W3C Wiki News 2014-12-03: The 8th edition of the Linked Data on the Web workshop will take place at WWW2015 in Florence, Italy. The paper submission deadline for the workshop is 15 March, 2015. 2014-09-10: An updated version of the LOD Cloud diagram has been published. The new version contains 570 linked datasets which are connected by 2909 linksets. Project Description The Open Data Movement aims at making data freely available to everyone. The goal of the W3C SWEO Linking Open Data community project is to extend the Web with a data commons by publishing various open data sets as RDF on the Web and by setting RDF links between data items from different data sources. RDF links enable you to navigate from a data item within one data source to related data items within other sources using a Semantic Web browser. The figures below show the data sets that have been published and interlinked by the project so far. Clickable version of this diagram. Project Pages Meetings & Gatherings See Also Demos 1. 2.

About DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself. Upcoming Events News Call for Ideas and Mentors for GSoC 2014 DBpedia + Spotlight joint proposal (please contribute within the next days)We started to draft a document for submission at Google Summer of Code 2014: are still in need of ideas and mentors. The DBpedia Knowledge Base Knowledge bases are playing an increasingly important role in enhancing the intelligence of Web and enterprise search and in supporting information integration. Within the

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