Understands how the pattern matching of SPARQL queries can be expressed using functionally equivalent constructs in RDF programming libraries. – Linked Data for Professional Education

Linked Statistical Data Analysis

Sun, 13 Aug 2017 08:18:11 +0000

Linked Data design principles are increasingly employed to publish and consume high-fidelity, heterogeneous statistical datasets in a distributed fashion. While vast amounts of linked statistics are available, access and reuse of the data is subject to expertise in corresponding technologies. There exists no user-centered interfaces for researchers, journalists and interested people to compare statistical data retrieved from different sources on the Web. Given that the RDF Data Cube vocabulary is used to describe statistical data, its use makes it possible to discover and identify statistical data artifacts in a uniform way. In this article, the design and implementation of a user-centric application and service is presented. Behind the scene, the platform utilizes federated SPARQL queries to gather statistical data from distributed data stores. The R language for statistical computing is employed to perform statistical analyses and visualizations. The Shiny application and server bridges the front-end Web user interface with R on the server-side in order to compare statistical macrodata, and stores analyses results in RDF for future research. As a result, distributed linked statistics with accompanying provenance data can be more easily explored and analysed by interested parties.

URL: http://csarven.ca/linked-statistical-data-analysis
Keywords: Data analysis, R (programming language), Shiny server, Apache Jena, Federated queries
Author: Riedl, Reinhard
Publisher: CEUR (Central Europe Workshop Proceedings)
Date created: 2013-07-07 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: professionalDevelopment
Educational audience: professional
Interactivity type: expositive

SPARQL Package for R: Movie Star Graph Visualization Tutorial

Sun, 06 Aug 2017 07:58:04 +0000

The SPARQL Package allows you to directly import results of SPARQL SELECT queries into the statistical environment of R as a data frame, allowing one to directly perform statistical analysis on datasets on the web. This tutorial shows how to do a visual analysis with the Gephi graph visualization tool, and basic social network analysis with R of the data in the DBpedia repository about Hollywood movies. It makes use of the SPARQL Package for R and the igraph library.

URL: http://linkedscience.org/tools/sparql-package-for-r/sparql-package-for-r-gephi-movie-star-graph-visualization-tutorial/
Keywords: R (programming language), Linked Open Data (LOD), Statistical analysis, Data visualization, Gephi
Author: van Hage, Willem Robert
Publisher: COMBINE project
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P90M
Educational use: instruction
Educational audience: student
Interactivity type: mixed

Using the SPARQL Package in R to Handle Spatial Linked Data: Part II

Sun, 06 Aug 2017 07:58:04 +0000

Continuing where Part I left off, this tutorial shows how to access Spatial and Temporal Data about the complex environmental system of the Brazilian Amazon Rainforest, including deforestation statistics, and a variety of socio-economic variables. It shows how store this data in a meaningful way and how to plot and handle it within R.

URL: http://linkedscience.org/tools/sparql-package-for-r/tutorial-part-ii-calculating-deforestation-per-state/
Keywords: R (programming language), Linked Open Data (LOD), Statistical analysis, Data visualization
Author: Gräler, Benedikt
Publisher: COMBINE project
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P30M
Educational use: instruction
Educational audience: student
Interactivity type: mixed

Using the SPARQL Package in R to Handle Spatial Linked Data: Part I

Sun, 06 Aug 2017 07:58:04 +0000

As a solution to bridge two communities, those of statistical computing and the Semantic Web, there is now the SPARQL Package for R, which enables one to retrieve data from Linked Data services for analysis. This tutorial shows
how to access Spatial and Temporal Data about the complex environmental system of the Brazilian Amazon Rainforest, including deforestation statistics, and a variety of socio-economic variables. It shows how store this data in a meaningful way and how to plot and handle it within R.

URL: http://linkedscience.org/tools/sparql-package-for-r/tutorial-on-sparql-package-for-r/
Keywords: R (programming language), Linked Open Data (LOD), Statistical analysis, Data visualization
Author: Gräler, Benedikt
Publisher: COMBINE project
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P30M
Educational use: instruction
Educational audience: student
Interactivity type: mixed

SPARQL Package for R: Linked Open Piracy Tutorial

Sun, 06 Aug 2017 07:58:04 +0000

This tutorial shows how to do a visual analysis and basic statistical analysis of the data in the Linked Open Piracy data set. It makes use of the SPARQL Package for R and the ggmap package. The SPARQL Package allows one to directly import results of SPARQL SELECT queries into the statistical environment of R as a data frame, allowing one to directly perform statistical analysis on datasets from the web.

URL: http://linkedscience.org/tools/sparql-package-for-r/linked-open-piracy-tutorial/
Keywords: R (programming language), Linked Open Data (LOD), Statistical analysis, Data visualization
Author: van Hage, Willem Robert
Publisher: COMBINE project
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: instruction
Educational audience: student
Interactivity type: mixed

Making Sense of Linked Data with Python

Thu, 04 May 2017 06:59:04 +0000

This blog post goes over three basic tasks for consuming RDF with Python: Fetching the data; Parsing the data returned into a graph; Traversing the graph to display the data. It also includes a detailed breakdown of a piece of functional code that extracts from a virtual graph four sets of values: Name(s) of the Creative Work; Name(s) of the Author(s); Description of the Creative Work;
Name(s) of the Subject(s).

URL: http://www.oclc.org/developer/news/2016/making-sense-of-linked-data-with-python.en.html
Keywords: Python, RDFLib, Query, JSON-LD
Author: Mixter, Jeff
Publisher: OCLC (Online Computer Library Center)
Date created: 2016-06-10 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

SPARQL and Linked Data Homework Exercises

Sat, 21 Jan 2017 06:46:40 +0000

This document contains several "written" and "electronic" homework questions originally from the course "Semantic Web Topics" at LeHigh University. They include: Write a series of SPARQL queries using a provided schema; Write a SPARQL construct query that generates all triples inferred by a specific RDFS entailment rule; Write a SPARQL construct query to generate
owl:sameAs statements between domains which share specified property; Describe the pros and cons of generating links in the manner specified in the previous question; Using Jena, create a class that can read in all the files in a specified directory and create a Web page that lists a series of publications organized by topic – reading all of the files into a single model and only using SPARQL to retrieve information from the model.

URL: http://www.cse.lehigh.edu/~heflin/courses/sw-2013/hw2.pdf
Keywords: SPARQL, RDF Schema, Entailment regime, Apache Jena, Java
Author: Heflin, Jeff
Date created: 2013-02-01 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P4H
Educational use: assessment
Educational audience: teacher-educationSpecialist
Interactivity type: active

JRDF: An RDF Library in Java

Tue, 17 Jan 2017 06:46:13 +0000

JRDF is an attempt to create a standard set of APIs and base implementations to RDF using the latest version of the Java language. A key aspect will be to ensure a high degree of modularity and to follow standard Java conventions. It will be similar to other standard Java APIs such as JDBC, XML, Collections, etc. This project is based on the existing RDF libraries and is designed to include the best features from all available sources, such as: Jena, Sesame, Aquamarine, and Sergey Melnik's RDF API.

URL: http://jrdf.sourceforge.net/
Keywords: Java, API
Author: Newman, Andrew
Date created: 2011-05-08 07:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P1H
Educational use: professionalDevelopment

Using R To Do a SPARQL Query

Mon, 09 Jan 2017 06:45:30 +0000

This video tutorial shows how to use R code (specifically, the "SPARQL" package) to grab the results from a SPARQL query instead of doing it through a web browser. Also briefly discussing turning the query results into a visualization using the "igraph" package.

URL: https://www.youtube.com/watch?v=WHjtVMj-GeQ
Keywords: SPARQL, R (programming language)
Author: Sherlock, David
Date created: 2013-06-05 04:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P10M

Survey of Pythonic Tools for RDF and Linked Data Programming

Thu, 29 Dec 2016 06:44:04 +0000

In this blog post, the author shares his efforts to gather information about all the existing libraries and frameworks for doing RDF programming using Python. This is not simply a list of resources; descriptions and the author's impressions are included. In addition to Python libraries, triple stores that are Python-friendly are also covered.

URL: http://www.michelepasin.org/blog/2011/02/24/survey-of-pythonic-tools-for-rdf-and-linked-data-programming/
Keywords: Python, Triple store, SPARQL
Author: Pasin, Michele
Date created: 2011-02-24 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Interactivity type: mixed