"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
The Pregel Programming Model with Spark GraphXAndrea Iacono
GraphX is Apache Spark's API for graph distributed computing based on the Pregel programming model. In this talk we'll see a brief introduction to Pregel and then we'll focus on transforming standard graph algorithms in their distributed counterpart using GraphX to speedup performance in a distributed environment.
"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
The Pregel Programming Model with Spark GraphXAndrea Iacono
GraphX is Apache Spark's API for graph distributed computing based on the Pregel programming model. In this talk we'll see a brief introduction to Pregel and then we'll focus on transforming standard graph algorithms in their distributed counterpart using GraphX to speedup performance in a distributed environment.
My presentation at SMX Milan 2015. New ways to compile and offer structured data to search engines for improved online visibility. Real life examples ready to use for websites and blogs.
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
Zenoh is rapidly growing Eclipse project that unifies data in motion, data at rest and computations. It elegantly blends traditional pub/sub with geo distributed storage, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks. This presentation will provide an introduction to Eclipse Zenoh along with a crisp explanation of the challenges that motivated the creation of this project. We will go through a series of real-world use cases that demonstrate the advantages brought by Zenoh in enabling and optimising typical edge scenarios and in simplifying the development of any scale distributed applications.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Deep Dive Into Kafka Streams (and the Distributed Stream Processing Engine) (...confluent
Kafka Streams is a library for developing applications for processing records from topics in Apache Kafka. It provides high-level Streams DSL and low-level Processor API for describing fault-tolerant distributed streaming pipelines in Java or Scala programming languages. Kafka Streams also offers elaborate API for stateless and stateful stream processing. That’s a high-level view of Kafka Streams. Have you ever wondered how Kafka Streams does all this and what the relationship with Apache Kafka (brokers) is? That’s among the topics of the talk.
During this talk we will look under the covers of Kafka Streams and deep dive into Kafka Streams’ Fault-Tolerant Distributed Stream Processing Engine. You will know the role of StreamThreads, TaskManager, StreamTasks, StandbyTasks, StreamsPartitionAssignor, RebalanceListener and few others. The aim of this talk is to get you equipped with knowledge about the internals of Kafka Streams that should help you fine-tune your stream processing pipelines for better performance.
This introduction to graph databases is specifically designed for Enterprise Architects who need to map business requirements to architectural components like graph databases. It explains how and why graphs matter for Enterprise Architecture and reviews the architectural differences between relational and graph models.
Definition of Digital Twin, how does it work, what's the origin, what the use case of the digital twin in industries, what's the relationship between JSON-LD and RDFs. What is the current market for digital twins and what are the available tools in the market to create a digital twin? Does digital twin only works with JSON-LD or does it works as well with RDF?
Atlas Search combines the power of Apache Lucene - the technology behind the world’s most popular search engines - with the developer productivity, scale, and resilience of MongoDB Atlas to make it easier than ever to integrate fast, relevance-based search capabilities into all of your MongoDB applications.
Watch the Getting Started with MongoDB Atlas Search webinar where, with a few clicks and keystrokes, we unravel the mystery behind the search bar. The session searches through different data types, including text, numbers, dates, and geoJSON while exploring a variety of search capabilities.
My presentation at SMX Milan 2015. New ways to compile and offer structured data to search engines for improved online visibility. Real life examples ready to use for websites and blogs.
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
Zenoh is rapidly growing Eclipse project that unifies data in motion, data at rest and computations. It elegantly blends traditional pub/sub with geo distributed storage, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks. This presentation will provide an introduction to Eclipse Zenoh along with a crisp explanation of the challenges that motivated the creation of this project. We will go through a series of real-world use cases that demonstrate the advantages brought by Zenoh in enabling and optimising typical edge scenarios and in simplifying the development of any scale distributed applications.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Deep Dive Into Kafka Streams (and the Distributed Stream Processing Engine) (...confluent
Kafka Streams is a library for developing applications for processing records from topics in Apache Kafka. It provides high-level Streams DSL and low-level Processor API for describing fault-tolerant distributed streaming pipelines in Java or Scala programming languages. Kafka Streams also offers elaborate API for stateless and stateful stream processing. That’s a high-level view of Kafka Streams. Have you ever wondered how Kafka Streams does all this and what the relationship with Apache Kafka (brokers) is? That’s among the topics of the talk.
During this talk we will look under the covers of Kafka Streams and deep dive into Kafka Streams’ Fault-Tolerant Distributed Stream Processing Engine. You will know the role of StreamThreads, TaskManager, StreamTasks, StandbyTasks, StreamsPartitionAssignor, RebalanceListener and few others. The aim of this talk is to get you equipped with knowledge about the internals of Kafka Streams that should help you fine-tune your stream processing pipelines for better performance.
This introduction to graph databases is specifically designed for Enterprise Architects who need to map business requirements to architectural components like graph databases. It explains how and why graphs matter for Enterprise Architecture and reviews the architectural differences between relational and graph models.
Definition of Digital Twin, how does it work, what's the origin, what the use case of the digital twin in industries, what's the relationship between JSON-LD and RDFs. What is the current market for digital twins and what are the available tools in the market to create a digital twin? Does digital twin only works with JSON-LD or does it works as well with RDF?
Atlas Search combines the power of Apache Lucene - the technology behind the world’s most popular search engines - with the developer productivity, scale, and resilience of MongoDB Atlas to make it easier than ever to integrate fast, relevance-based search capabilities into all of your MongoDB applications.
Watch the Getting Started with MongoDB Atlas Search webinar where, with a few clicks and keystrokes, we unravel the mystery behind the search bar. The session searches through different data types, including text, numbers, dates, and geoJSON while exploring a variety of search capabilities.
Présentation sur la démarche de l'Open Data (quelles données ? Quels acteurs ?) et sur les technologies gravitant autour du Linked Data (le modèle RDF, RDFS, OWL, les ontologies, les triplestores, etc).
Swift est désormais open source ! "Google considérerait Swift comme un langage « de première classe » pour Android" pouvait-on lire en avril sur le réseau. Et enfin un portage Android du langage a été "merge" dans la base de code officielle de Swift.
Bon tout ceci est un bon prétexte pour apprendre ce nouveau langage et les possibilités qu'il peut nous apporter en terme de développement. Une comparaison avec Java sera notamment proposée afin de montrer les similitudes et differences entre ces deux langages .
SPARQL introduction and training (130+ slides with exercices)Thomas Francart
Full SPARQL training
Covers all SPARQL : basic graph patterns, FILTERs, functions, property paths, optional, negation, assignation, aggregation, subqueries, federated queries.
Does not cover except SPARQL updates.
Includes exercices on DBPedia.
CC BY license
CIDOC-CRM + SPARQL Tutorial sur les données DoremusThomas Francart
Introduction aux requêtes SPARQL sur les données du projet Doremus (http://data.doremus.org) qui modélise et diffuse les données de création d'oeuvres musicales sur la base du modèle CIDOC-CRM / FRBRoo.
Partager et réutiliser des données sur le webThomas Francart
open data, schema.org, DBPedia et Wikidata : Panorama et introduction à la problématique du partage des données structurées sur le web : entre la réutilisation des données des portails open-data, la structuration du contenu des pages web pour Google, l'exploitation des données de DBPedia, et la pose de liens entre les données pour favoriser leur découverte et leur réutilisation...
SKOS Play! (http://labs.sparna.fr/skos-play)
est une application open-source de visualisation de thesaurus, taxonomies ou vocabulaires contrôlés exprimés en SKOS.
1. RDFS
Thomas Francart, sparna.fr
Ce travail est réutilisable et modifiable librement, y compris à des fins commerciales, à
condition de citer son auteur et d’être placé sous la même licence.
Pour plus d’informations, voir la licence.
Crédits :
Ce travail remixe, traduit et complète une présentation de Fabien Gandon de l’INRIA, publiée sous
licence libre. Merci à lui.
10. RDFS définit une signature par
... le “domain” (fr : domaine) : type de
la ressource d’où part la relation.
... le “range” (fr: co-domaine ou portée)
: type de la ressource vers laquelle
pointe la relation.
10
11. RDFS définit une sémantique :
des règles de déduction standard
permettant de créer des triplets
additionnels à partir des triplets
existants.
11
12. (c2, subClassOf, c1)
ET
(x, type, c2)
ALORS (x, type, c1)
SI
Propagation des types
SI
ET
ALORS
(Man, subClassOf, Animal)
(Tom, type, Man)
(Tom, type, Animal)
12
13. (p2, subPropertyOf, p1)
ET
(x, p2 , y)
ALORS (x, p1 , y)
SI
Propagation des propriétés
SI
(auteur, subPropertyOf, créateur)
ET
(Tom, auteur, Report12)
ALORS (Tom, créateur, Report12)
13
14. (c2, subClassOf, c1)
ET
(c3, subClassOf, c2)
ALORS (c3, subClassOf, c1)
SI
Transitivité des sous-classes
SI
(Animal, subClassOf, EtreVivant)
ET
(Man, subClassOf, Animal)
ALORS (Man, subClassOf, EtreVivant)
14
15. SI
ET
ALORS
(p2, subPropertyOf, p1)
(p3, subPropertyOf, p2)
(p3, subPropertyOf, p1)
Transitivité des sous-propriétés
SI
(parentDe, subPropertyOf, ancetreDe)
ET
(pèreDe, subPropertyOf, parentDe)
ALORS (pèreDe, subPropertyOf, ancêtreDe)
15
16. SI
ET
ALORS
(p1, domain, c1)
(x, p1, y)
(x, type, c1)
Inférence sur le domaine
SI
(auteur, domain, Personne)
ET
(Tom, auteur, Report12)
16
17. SI
ET
ALORS
(p1, range, c1)
(x, p1, y)
(y, type, c1)
Inférence sur le range
SI
(auteur, range, Document)
ET
(Tom, auteur, report2)
17
18. RDFS fournit aussi 2 primitives
très utiles pour nommer ou commenter
n’importe quelle ressource
rdfs:label
rdfs:comment
18
21. RDFS
permet
... De déclarer des classes et des propriétés et
de les organiser en hiérarchie
... De déclarer la signature des propriétés
(domain, range)
... De les documenter avec des libellés et des
commentaires
... De faire des déductions simples sur les
classes et les propriétés
21