Apache RAT

Apache RAT is a library to add a license to your software project, or to check the licenses in your projects.
Actually, it is part of the Apache Creadur language "a build-agnostic suite of tools for auditing and comprehending software distributions".

It is made in the Apache style and it is compatible with maven and ant, but you can make it work from the command line very easily:

java -jar apache-rat-0.8.jar -d test -a

More info:
Apache RAT - Release Audit Tool


How to license an RDF document

Unfortunately, there is not a standard way of licensing RDF content. I will try to explain the alternatives that I have seen.

Annotating RDF: the simplest way

We want to state in RDF that the RDF document is licensed.

So all we have to do is declaring that our document (identified as http://example.com/example) has a license. We may use a popular license (Creative Commons Attribution, CC-BY) and a popular property to specify it.


Linked Data, Big Data, Open Data

Technology is ideology, for it transforms society. Each technology brings an unchallenged set of changes to the way man lives which is not under discussion -no Manifestos to argue with, no discussions in Parliaments, no controversy among wisemen-. Ineluctable changes, not revokable, hardly avoidable. It happened with the iron, with the gun, with the railroad and with the Internet before. Big novelties, big changes. Small novelties, small changes.


Example of use of RDFa

RDF organizes information as triples with the structure Subject-Predicate-Object.
RDFa is a RDF syntax for embedding metadata into documents like XHTML, HTML5 and other XML-based langauges (e.g. SVG).
Let's see some RDFa examples, assuming the RDFa1.1 Working Group Note version.

With the following lines, we declare the title of the web page using the DublinCore element


The man as a black box

Some see the man as a black box. He receives stimuli through his senses, he processes them (along with some data in his memory) and then he experiences feelings, express thoughts and ultimately acts. The man seen as a black box, with stimuli (actually a form of information) as input and actions as the output. Purchase intention is one of the output some are concerned with.


Broken Linked Data

I recall again my post of one year ago.
In the last few days, I have been reviewing all the RDF datasets available in this W3C wiki called Linked Data Sets (i.e., with Dereferenceable URIs) available as RDF Dumps, which appeared to be respectable. I have gone through each of the 69 datasets.


The Flickr Copyright Policeman

Most people are proud about their photos.
They upload them to the web (e.g. Flickr) because they want the photos to be seen, but they want to limit how the photos are used by others. Some are more greedy (and license them with a all rights reserved sentence) and some just want to be mentioned (CC-BY).


Mapping of the Music Ontology to MVCO and PROV-O

The Music Ontology (MO) defines a vocabulary for expressing a wide range of music-related information, like who authored which song or which is the melody line of a particular work. It was first published in 2006 and it has become a de facto standard, both as a generic model and as a way of publishing music-related data. Interlinked with other vocabularies, a rich set of data is available in the Web and feeds many real-world applications.



¿Qué sentía la persona que escribía un Tweet o publicaba una opinión en un social media hacia una determinada marca?
¿Pueden los algoritmos de inteligencia artificial determinarlo?

¿Nos ayudas tú diciéndonos que crees que sentía?

Editado: [El experimento se cerró a las pocas semanas!]


Clustering algorithm with Tweets

Obtaining Tweets is easy: Twitter wants you to do it.
Some of these Tweets are geolocated.
We may cluster them according to the time and location and extract how the people moves in the city, if people tweet uniformly.
The location of the Tweets in a cluster, define areas. And these areas may have some relevance: sociological, commercial, etc.
Moreover, according to what they say, we may infer attributes of the places. Cool.



Subscribe to www.cosasbuenas.es RSS