This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
FedX - Optimization Techniques for Federated Query Processing on Linked Dataaschwarte
The final slides of our talk about FedX at the 10th International Semantic Web Conference in Bonn. For details about FedX see http://www.fluidops.com/fedx/
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
FedX - Optimization Techniques for Federated Query Processing on Linked Dataaschwarte
The final slides of our talk about FedX at the 10th International Semantic Web Conference in Bonn. For details about FedX see http://www.fluidops.com/fedx/
Tutorial on RDFa, to be held at ISWC2010 in Shanghai, China. (I was supposed to hold the tutorial but last minute issues made it impossible for me to travel there...)
Create Linked Open Data (LOD) Microthesauri using Art & Architecture Thesaurus (AAT) LOD. View and manage options by a non-techy person. Everyone can use, create,
derive from, & map to AAT microthesauri and make the digital collection become LOD-ready dataset.
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationMuhammad Saleem
Efficient federated query processing is of significant importance to tame the large amount of data available on the Web of Data. Previous works have focused on generating optimized query execution plans for fast result retrieval. However, devising source selection approaches beyond triple pattern-wise source selection has not received much attention. This work presents HiBISCuS, a novel hypergraph-based source selection approach to federated SPARQL querying. Our approach can be directly combined with existing SPARQL query federation engines to achieve the same recall while querying fewer data sources. We extend three well-known SPARQL query federation engines with HiBISCus and compare our extensions with the original approaches on FedBench. Our evaluation shows that HiBISCuS can efficiently reduce the total number of sources selected without losing recall. Moreover, our approach significantly reduces the execution time of the selected engines on most of the benchmark queries.
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
This presentation introduces the main principles of Linked Data, the underlying technologies and background standards. It provides basic knowledge for how data can be published over the Web, how it can be queried, and what are the possible use cases and benefits. As an example, we use the development of a music portal (based on the MusicBrainz dataset), which facilitates access to a wide range of information and multimedia resources relating to music.
Poster - Completeness Statements about RDF Data Sources and Their Use for Qu...Fariz Darari
Thousands of RDF data sources are today available on the Web.
Machine-readable qualitative descriptions of their content are crucial.
We focus on data completeness, an important aspect of data quality.
How to formalize and express in a machine-readable way completeness information about RDF data sources?
How to leveragesuch completeness information?
Formal framework for expressing completeness information.
Study of query completeness from completeness information in various settings.
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
Create Linked Open Data (LOD) Microthesauri using Art & Architecture Thesaurus (AAT) LOD. View and manage options by a non-techy person. Everyone can use, create,
derive from, & map to AAT microthesauri and make the digital collection become LOD-ready dataset.
HiBISCuS: Hypergraph-Based Source Selection for SPARQL Endpoint FederationMuhammad Saleem
Efficient federated query processing is of significant importance to tame the large amount of data available on the Web of Data. Previous works have focused on generating optimized query execution plans for fast result retrieval. However, devising source selection approaches beyond triple pattern-wise source selection has not received much attention. This work presents HiBISCuS, a novel hypergraph-based source selection approach to federated SPARQL querying. Our approach can be directly combined with existing SPARQL query federation engines to achieve the same recall while querying fewer data sources. We extend three well-known SPARQL query federation engines with HiBISCus and compare our extensions with the original approaches on FedBench. Our evaluation shows that HiBISCuS can efficiently reduce the total number of sources selected without losing recall. Moreover, our approach significantly reduces the execution time of the selected engines on most of the benchmark queries.
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
This presentation introduces the main principles of Linked Data, the underlying technologies and background standards. It provides basic knowledge for how data can be published over the Web, how it can be queried, and what are the possible use cases and benefits. As an example, we use the development of a music portal (based on the MusicBrainz dataset), which facilitates access to a wide range of information and multimedia resources relating to music.
Poster - Completeness Statements about RDF Data Sources and Their Use for Qu...Fariz Darari
Thousands of RDF data sources are today available on the Web.
Machine-readable qualitative descriptions of their content are crucial.
We focus on data completeness, an important aspect of data quality.
How to formalize and express in a machine-readable way completeness information about RDF data sources?
How to leveragesuch completeness information?
Formal framework for expressing completeness information.
Study of query completeness from completeness information in various settings.
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
An agency-by-agency guide to Obama's 2014 budgetadlerwinona
WASHINGTON (AP) - President Barack Obama of has proposed a $3.8 trillion budget for fiscal 2014 that aims to slash the resort by a net $600 billion over 10 years, raise taxes and trim popular benefit programs, including social security and Medicare. The White House claims deficit reductions of $1.8 trillion, but Obama's proposal would negate more than $1 trillion in automatic spending cuts that started in March. Those cuts average 5 percent for domestic agencies and 8 percent for the Defense Department this year.
The agency-by-agency breakdown:
Agency: Agriculture
Total spending: $145.8 billion
Percentage change from 2013: 5.9 percent decrease
Discretionary spending: $21.5 billion
Mandatory spending: $124.4 billion
Highlights: Similar to years past, Obama's budget proposes savings by cutting farm subsidies. The proposal envisions a $37.8 billion reduction in the deficit by eliminating some subsidies that are paid directly to farmers, reducing government help for crop insurance and streamlining agricultural land conservation programs.
The Obama administration says many of these subsidies can no longer be justified with the value of both crop and livestock production at all-time highs. Farm income is expected to increase 13.6 percent to $128.2 billion in 2013, the highest inflation-adjusted amount in 40 years.
Presentazione all'interno del laboratorio "Grammatica e Sessismo" (GeS5) presso la Facoltà di Lettere e Filosofia dell'Universitò di Tor Vergata di Roma, 4 ottobre 2015
As of Drupal 7 we'll have RDFa markup in core, in this session I will:
-explain what the implications are of this and why this matters
-give a short introduction to the Semantic web, RDF, RDFa and SPARQL in human language
-give a short overview of the RDF modules that are available in contrib
-talk about some of the potential use cases of all these magical technologies
This presentation looks in detail at SPARQL (SPARQL Protocol and RDF Query Language) and introduces approaches for querying and updating semantic data. It covers the SPARQL algebra, the SPARQL protocol, and provides examples for reasoning over Linked Data. We use examples from the music domain, which can be directly tried out and ran over the MusicBrainz dataset. This includes gaining some familiarity with the RDFS and OWL languages, which allow developers to formulate generic and conceptual knowledge that can be exploited by automatic reasoning services in order to enhance the power of querying.
This slides I've used on talk about Semantic Web use-case. Not all know what exactly Semantic Web is about. So I've created set of slides showing this in a simple and correct way. Use-case slides are removed on this public available slides. Animated version here goo.gl/qKoF6k . Contact me for sources!
Il web dei dati: database di dati strutturati sul mondo che ci circonda, che individui e istituzioni, aziende, organizzazioni possono donare, aggiungere, modificare e usare in modo gratuito. In Wikipedia, nelle varie versioni linguistiche e nei progetti Wikimedia. E non solo.
Presentazione di WikiDonne User Group per l'evento "Wikipedia e le donne nelle professioni culturali" (all'interno del festival "L'eredità delle donne"). Biblioteca di Scienze Sociali dell'Università di Firenze, 21 settembre 2018.
WDG - Donne e social media: pericoli e opportunità della reteCAMELIA BOBAN
Presentazione fatta durante l'incontro con gli studenti dell'Università degli Studi di Molise, "Donne e Social Media: Rischi e Opportunità".
Presentazione Google: https://docs.google.com/presentation/d/18xFafiwfMr1jK3aBfAnkMjJ5gvBOEAJkEJGo0E0Ac9Y/edit?usp=sharing
Presentazione al liceo J.Joyce di Ariccia il 26 ottobre 2016
Per una migliore visualizzazione: https://docs.google.com/presentation/d/1p-bnn1-SyVVSvWosPNTK9ad7Bvy-AfuyqVxDALr7WQw/edit?usp=sharing
Universo wiki e OpenStreetMap: non solo contenuti, ma anche templates, tools e estensioni. Statistiche, metriche e grafici. SPARQL e SQL Optimizer. Mappe.
Utilizzato il template Slides Carnival per Google Presentation. Per una vizualizzazione migliore: https://docs.google.com/presentation/d/1bYY4B7Uw6DulQYk6-lclC4gBzITKUsdi87sNIzNOfLI/edit?usp=sharing
Licenze libere in Wikipedia - GFDL e Creative Commons.
Presentazione per il workshop all'Associazione "Toponomastica Femminile", Roma 15-17 luglio 2016
Presentazione fatta il 23 giugno 2016 a Roma presso la Biblioteca della Link Campus University sulle donne e Wikipedia per l'occasione del lancio della scrittura di voci femminili appartenenti all'area STEM (Science, Technology, Engineering, Mathematics) sull'enciclopedia online. Partendo dal progetto cartaceo realizzato dall'Associazione Giulia e l'Osservatorio di Pavia nell'ambito della campagna di sensibilizzazione sul tema della parità di genere.
Angel Eats, web application about food emergency (malnutrition vs food waste) presented during the Koding's Global Virtual Hackathon on 6-8 dicember 2014
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
3. Resources for the codelab:
Eclipse Luna for J2EE developers - https://www.eclipse.org/downloads/index-developer.php
Java SE 1.8 - http://www.oracle.com/technetwork/java/javase/downloads/jre8-downloads-2133155.html
Apache Tomcat 8.0.5 - http://tomcat.apache.org/download-80.cgi
Axis2 1.6.2 - http://axis.apache.org/axis2/java/core/download.cgi
Apache Jena 2.11.1 - http://jena.apache.org/download/
Dbpedia Sparql endpoint: - dbpedia.org/sparql
BigData & Wikidata - no lies
4. JAR needed:
httpclient-4.2.3.jar httpcore-4.2.2.jar Jena-arq-2.11.1.jar
Jena-core-2.11.1.jar Jena-iri-1.0.1.jar jena-sdb-1.4.1.jar jena-tdb-1.0.1.jar
slf4j-api-1.6.4.jar slf4j-log4j12-1.6.4.jar
xercesImpl-2.11.0.jar xml-apis-1.4.01.jar
Attention!!
NO jcl-over-slf4j-1.6.4.jar (slf4j-log4j12-1.6.4 conflict, “Can’t override final class exception”)
NO httpcore-4.0.jar (made by Axis, httpcore-4.2.2.jar conflict, don’t let create the WS)
BigData & Wikidata - no lies
5. The Semantic Web
The Semantic Web is a project that intends to add computer-processable meaning
(semantics) to the Word Wide Web.
SPARQL
A a protocol and a query language SQL-like for querying RDF graphs via pattern
matching
VIRTUOSO
Both back-end database engine and the HTTP/SPARQL server.
BigData & Wikidata - no lies
7. DBpedia.org
Is the Semantic Web mirror of Wikipedia.
RDF
Is a data model of graphs on subject, predicate, object triples.
APACHE JENA
A free and open source Java framework for building Semantic Web and Linked
Data applications.
ARQ - A SPARQL Processor for Jena for querying Remote SPARQL Services
BigData & Wikidata - no lies
9. DBpedia.org extracts from Wikipedia editions in 119 languages, convert it into RDF
and make this information available on the Web:
★ 24.9 million things (16.8 million from the English Dbpedia);
★ labels and abstracts for 12.6 million unique things;
★ 24.6 million links to images and 27.6 million links to external web pages;
★ 45.0 million external links into other RDF datasets, 67.0 million links to
Wikipedia categories, and 41.2 million YAGO categories.
BigData & Wikidata - no lies
10. The dataset consists of 2.46 billion RDF triples (470 million were extracted from
the English edition of Wikipedia), 1.98 billion from other language editions, and 45
million are links to external datasets.
DBpedia uses the Resource Description Framework (RDF) as a flexible data
model for representing extracted information and for publishing it on the Web. We
use the SPARQL query language to query this data.
BigData & Wikidata - no lies
12. What is a Triple?
A Triple is the minimal amount of information expressable in Semantic Web. It is
composed of 3 elements:
1. A subject which is a URI (e.g., a "web address") that represents something.
2. A predicate which is another URI that represents a certain property of the
subject.
3. An object which can be a URI or a literal (a string) that is related to the
subject through the predicate.
BigData & Wikidata - no lies
13. John has the email address john@email.com
(subject) (predicate) (object)
Subjects, predicates, and objects are represented with URIs, which can be
abbreviated as prefixed names.
Objects can also be literals: strings, integers, booleans, etc.
BigData & Wikidata - no lies
14. Why SPARQL?
SPARQL is a quey language of the Semantic Web that lets us:
1. Extract values from structured and semi-strutured data
2. Explore data by querying unknown relatioships
3. Perform complex join query of various dataset in a unique query
4. Trasform data from a vocabulary in another
BigData & Wikidata - no lies
15. Structure of a SPARQL query:
● Prefix declarations, for abbreviating URIs ( PREFIX dbpowl:
<http://dbpedia.org/ontology/Mountain> = dbpowl:Mountain)
● Dataset definition, stating what RDF graph(s) are being queried (DBPedia,
Darwin Core Terms, Yago, FOAF - Friend of a Friend)
● A result clause, identifying what information to return from the query The
query pattern, specifying what to query for in the underlying dataset (Select)
● Query modifiers, slicing, ordering, and otherwise rearranging query results -
ORDER BY, GROUP BY
BigData & Wikidata - no lies
17. ##EXAMPLE - Give me all cities & towns in Abruzzo with more than 50,000
inhabitants
PREFIX dbpclass: <http://dbpedia.org/class/yago/>
PREFIX dbpprop: <http://dbpedia.org/property/>
SELECT ?resource ?value
WHERE {
?resource a dbpclass:CitiesAndTownsInAbruzzo .
?resource dbpprop:populationTotal ?value .
FILTER ( ?value > 50000 )
}
ORDER BY ?resource ?value
BigData & Wikidata - no lies
21. Wikipedia articles consist mostly of free text, but also contain different types of
structured information: infobox templates, categorisation information, images,
geo-coordinates, and links to external Web pages. DBpedia transforms into RDF
triples data that are entered in Wikipedia. So creating a page in Wikipedia creates
RDF in DBpedia.
BigData & Wikidata - no lies
23. Example:
https://en.wikipedia.org/wiki/Pulp_Fiction describes the movie. DBpedia creates a
URI: http://dbpedia.org/resource/wikipedia_page_name (where
wikipedia_page_name is the name of the regular Wikipedia html page) =
http://dbpedia.org/page/Pulp_Fiction. Underscore characters replace spaces.
DBpedia can be queried via a Web interface at ttp://dbpedia.org/sparql . The
interface uses the Virtuoso SPARQL Query Editor to query the DBpedia endpoint.
BigData & Wikidata - no lies
24. Public SPARQL Endpoint - use OpenLink Virtuoso
Wikipedia page: http://en.wikipedia.org/wiki/Pulp_Fiction
DBPedia resource: http://dbpedia.org/page/Pulp_Fiction
InfoBox: dbpedia-owl:abstract; dbpedia-owl:starring; dbpedia-owl:budget;
dbpprop:country; dbpprop:caption ecc.
For instance, the figure below shows the source code and the visualisation of an
infobox template containing structured information about Pulp Fiction.
BigData & Wikidata - no lies
28. Linked Data is a method of publishing RDF data on the Web and of interlinking
data between different data sources.
Query builder:
➢ http://dbpedia.org/snorql/
➢ http://querybuilder.dbpedia.org/
➢ http://dbpedia.org/isparql/
➢ http://dbpedia.org/fct/
➢ http://it.dbpedia.org/sparql
Prefix variables start with "?"
BigData & Wikidata - no lies
29. The current RDF vocabularies are available at the following locations:
➔ W3: http://www.w3.org/TR/vcard-rdf/ vCard Ontology - for describing People
and Organizations
http://www.w3.org/2003/01/geo/ Geo Ontology - for spatially-located things
http://www.w3.org/2004/02/geo/ SKOS Simple Knowledge Organization
System
BigData & Wikidata - no lies
30. ➔ GEO NAMES: http://www.geonames.org/ geospatial semantic information
(postal code)
➔ DUBLIN CORE: http://www.dublincore.org/ defines general metadata
attributes used in a particular application
➔ FOAF: http://www.foaf-project.org/ Friend of a Friend, vocabulary for
describing people
➔ UNIPROT: http://www.uniprot.org/core/, http://beta.sparql.uniprot.org/uniprot
for science articles
BigData & Wikidata - no lies
31. ➔ MUSIC ONTOLOGY: http://musicontology.com/, provides terms for
describing artists, albums and tracks.
➔ REVIEW VOCABULARY: http://purl.org/stuff/rev , vocabulary for
representing reviews.
➔ CREATIVE COMMONS (CC): http://creativecommons.org/ns , vocabulary for
describing license terms.
➔ OPEN UNIVERSITY: http://data.open.ac.uk/
BigData & Wikidata - no lies
32. ➔ Semantically-Interlinked Online Communities (SIOC): www.sioc-
project.org/, vocabulary for representing online communities
➔ Description of a Project (DOAP): http://usefulinc.com/doap/, vocabulary for
describing projects
➔ Simple Knowledge Organization System (SKOS):
http://www.w3.org/2004/02/skos/, vocabulary for representing taxonomies and
loosely structured knowledge
BigData & Wikidata - no lies
34. SPARQL queries have two parts (FROM is not indispensable):
1. The query (WHERE) part, which produces a list of variable bindings (although
some variables may be unbound).
2. The part which puts together the results. SELECT, ASK, CONSTRUCT, or
DESCRIBE.
Other keywords:
UNION, OPTIONAL (optional display if data exists), FILTER (conditions), ORDER
BY, GROUP BY
BigData & Wikidata - no lies
35. SELECT - is effectively what the query returns (a ResultSet)
ASK - just looks to see if there are any results
COSTRUCT - uses a template to make RDF from the results. For each result row
it binds the variables and adds the statements to the result model. If a template
triple contains an unbound variable it is skipped. Return a new RDF-Graph
DESCRIBE - unusual, since it takes each result node, finds triples associated with
it, and adds them to a result model. Return a new RDF-Graph
BigData & Wikidata - no lies
36. What linked data il good for? Don’t search a single thing, but explore a whole
set of related things together!
1) Revolutionize Wikipedia Search
2) Include DBpedia data in our own web page
3) Mobile and Geographic Applications
4) Document Classification, Annotation and Social Bookmarking
5) Multi-Domain Ontology
6) Nucleus for the Web of Data
BigData & Wikidata - no lies
39. WIKIPEDIA DUMPS
● Arabic Wikipedia dumps: http://dumps.wikimedia.org/arwiki/
● Dutch Wikipedia dumps: http://dumps.wikimedia.org/nlwiki/
● English Wikipedia dumps: http://dumps.wikimedia.org/enwiki/
● French Wikipedia dumps: http://dumps.wikimedia.org/frwiki/
● German Wikipedia dumps: http://dumps.wikimedia.org/dewiki/
● Italian Wikipedia dumps: http://dumps.wikimedia.org/itwiki/
● Persian Wikipedia dumps: http://dumps.wikimedia.org/fawiki/
● Polish Wikipedia dumps: http://dumps.wikimedia.org/plwiki/
BigData & Wikidata - no lies
40. WIKIPEDIA DUMPS
● Portuguese Wikipedia dumps: http://dumps.wikimedia.org/ptwiki/
● Russian Wikipedia dumps: http://dumps.wikimedia.org/ruwiki/
● Serbian Wikipedia dumps: http://dumps.wikimedia.org/srwiki/
● Spanish Wikipedia dumps: http://dumps.wikimedia.org/eswiki/
● Swedish Wikipedia dumps: http://dumps.wikimedia.org/svwiki/
● Ukrainian Wikipedia dumps: http://dumps.wikimedia.org/ukwiki/
● Vietnamese Wikipedia dumps: http://dumps.wikimedia.org/viwiki/
BigData & Wikidata - no lies
41. LINK
Codelab’s project code: http://github.com/GDG-L-Ab/SparqlOpendataWS
http://dbpedia.org/sparql & http://it.dbpedia.org/sparql
http://wiki.dbpedia.org/Datasets
http://en.wikipedia.org/ & http://it.wikipedia.org/
http://dbpedia.org/snorql, http://data.semanticweb.org/snorql/ SPARQL Explorer
http://downloads.dbpedia.org/3.9/ & http://wiki.dbpedia.org/Downloads39
BigData & Wikidata - no lies
42. Projects that use linked data:
JAVA: Open Learn Linked data: free access to Open University course materials
PHP: Semantic MediaWiki -Lllets you store and query data within the wiki's pages.
PEARL: WikSAR
PYTHON: Braindump - semantic search in Wikipedia
RUBY: SemperWiki
BigData & Wikidata - no lies
43. BigData & Wikidata - no lies
THANK YOU! :-)
I AM
CAMELIA BOBAN
G+ : https://plus.google.com/u/0/+cameliaboban
Twitter : http://twitter.com/GDGRomaLAb
LinkedIn: it.linkedin.com/pub/camelia-boban/22/191/313/
Blog: http://blog.aissatechnologies.com/
Skype: camelia.boban
camelia.boban@gmail.com