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    Publicado el 29.10.2015 por Ricardo Alonso Maturana

    What are the differences between a Graph database and a Triple store? (by Matt Allen in Quora)

    Graph Databases vs. RDF Triple Stores
    To summarize, both graph databases and triple stores are designed to store linked data. RDF is a specific kind of linked data that is queried using SPARQL, so it is fair to say that RDF triple stores are a kind of graph database. But, there are some subtle but important differences that are described below.
    How They Are Similar
    ·       Graph databases and rdf triple stores focus on the relationships between the data, often referred to as “linked data.” Data points are called nodes, and the relationship between one data point and another is called an edge.
    ·       A web of nodes and edges can be put together into interesting visualizations—a defining characteristic of graph databases.
    How They Are Different
    ·       Graph databases are more versatile with query languages:  Neo4J can run an RDF triple store and use SPARQL but generally focuses on its own proprietary language, Cypher. Other graph databases support G, GraphLog, GOOD, SoSQL, BiQL, SNQL, and more. RDF triple stores only use SPARQL as the query language.
    ·       Graph databases can store various types of graphs, including undirected graphs, weighted graphs, hypergraphs, etc. RDF triple stores focus solely on storing rows of RDF triples.
    ·       Graph databases are node, or property, centric whereas RDF triple stores are edge-centric. RDF triple stores are really just a list of graph edges, many of which are 'properties'  of a node and not critical to the graph structure itself.
    ·       Graph databases are better optimized for graph traversals (degrees of separation or shortest path algorithms). With RDF triple stores, the cost of traversing an edge tends to be logarithmic.
    ·       RDF triple stores also provide inferences on data but graph databases do not (e.g., if humans are a subclass of mammals and man is a subclass of humans, then it can be inferred that man is a subclass of mammals).
    ·       RDF triple stores are more synonymous with the “semantic web” and the standardized universe of knowledge being stored as RDF triples on DBpedia and other sources whereas graph databases are seen as more pragmatic rather than academic.

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    Publicado el 25.7.2013 por Pablo Hermoso de Mendoza González

    OAIS: Ontologies meet Advanced Information Systems (OAIS’2013)

    Congreso internacional sobre ontologías y sistemas avanzados de información a celebrar en septiembre de este año en la localidad italiana de Génova.

    Second International Workshop on Ontologies meet Advanced Information Systems (OAIS)’

    In Conjunction with the 17th East-European Conference on Advances in Databases and Information Systems (ADBIS'2013)

    September 1-4, 2013

    Genoa, Italy

    http://oais2013.ensma.fr

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    Publicado el 21.7.2013 por Pablo Hermoso de Mendoza González

    NoSQL databases

    tipo de documento Presentación

    En esta presentación Marin Dimitrov (Ontotext) realiza un repaso de las principales categorías asociadas a Modelos de Base de Datos NOSQL: Key Value Store, Column Store, Document Store y Graph Database.  Mar 2010

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    Publicado el 14.5.2012 por Equipo GNOSS

    The 11th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2012)

    La conferencia sobre ontologías, bases de datos y aplicaciones semánticas para sistemas de información a gran escala (ODBASE'12) ofrece un foro sobre el uso de ontologías y datos semánticos en nuevas aplicaciones. Entre los temas de la conferencia podemos destacar bases de datos, redes, sistemas móviles, inteligencia artificial, recuperación de información, y lingüística computacional. También se tratarán trabajos de investigación y experiencia práctica sobre problemas en los áreas de gestión de ontologías, integración de información, y minería de datos.
     

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    Publicado el 18.8.2010 por Pablo Hermoso de Mendoza González

    Traditional relational databases and Artificial Intelligence Knowledge Bases have much in common in that both serve to store and retrieve information. However, the expressivity with which information can be represented and the flexibility with which it can be queried set true Knowledge Bases apart from more traditional data stores.

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    Publicado el 7.4.2010 por Ricardo Alonso Maturana

    NoSQL Live Boston Recap (10gen)

    NoSQL Live fue un evento celebrado en Boston en el que participaron presencialmente más de 200 personas y otras 300 lo siguieron a través de webcast. En este post se encuentran los enlaces a los blogs de los ponentes, a sus presentaciones y, en general, a todo el material que se utilizó y circuló en la jornada. Muy interesante para todos aquellos que están trabajando en la construcción y desarrollo de la tecnología de la web 3.0.

    Thanks to all of the participants and attendees for making NoSQL Live such a success! We really enjoyed working with Cloudant and Hashrocket to bring together so many innovators in the NoSQL space. Over 230 people attended the event in person, and another 300 logged into the webcast over the course of the day.

    Some bad news and some good news about the video. Bad news: The streaming service that we used had a server crash in the middle of the event, and the recording was lost. Good news: We’ve pulled together a great archive of the event from a variety of sources within the community. Special thanks to Christian Scholz for recording MP3s of the entire event. If you have any additional notes, blogs, photos, slides, or video from the event, please post in the comments section.

    We value your feedback. Please complete the conference survey.

    MP3

    Blogs/Recaps

    Slides


    Publicado en 10gen el: 16/03/2010 21:18:00

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    Compartido el 10.3.2010 por Ricardo Alonso Maturana

    Next Generation Databases mostly address some of the points: being non-relational, distributed, open-source and horizontal scalable. The original intention has been modern web-scale databases. The movement began early 2009 and is growing rapidly. Often more characteristics apply as: schema-free, replication support, easy API, eventually consistency, and more. So the misleading term "nosql" (the community now translates it mostly with "not only sql") should be seen as an alias to something like the definition above.

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