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The word La palabra "informationinformación" is used in many waysse utiliza de muchas maneras. We mentioned the lay person's sense aboveHemos mencionado el sentido de la persona laica arriba, but it is also used of a sequence of symbols pero también se utiliza una secuencia de símbolos (such as letters of como letras de un idioma (ver foto a language (see picture at rightla derecha), dots and dashes of puntos y rayas del código Morse code, or the arrangement of the bumps of o la disposición de los golpes de Braille) that convey meaningque transmiten significado.Another way the term is used is in communications theoryOtra forma en que se utiliza el término es en teoría de la comunicación, and compression of messagesy la compresión de mensajes.It is mainly the last two of those senses that are discussed in this articleSe trata principalmente de los dos últimos de los sentidos que se analizan en este artículo.

Royal Truman, in his analysis published in the en su análisis publicada en el ''[[Journal of Creation]]'' discusses two families of approachesanaliza dos familias de enfoques: The one derived from El uno derivado de trabajo de Shannon's work and the other derived from y el otro derivado de la obra de [[Werner Gitt|Gitt]]'s work.<ref name=truman1>{{cite journal|title=Information Theory-Part 1:Overview of Key Ideas|author=Truman, Royal|year=2012|journal=[[Journal of Creation]]|volume=26|issue=3|pages=101-106|issn=1036-2916}}</ref> Truman also mention the algorithm definition of information, developed by Solomonoff, Kolmogorov and with contributions from [[Gregory Chaitin]] but that has not been discussed in his article.<ref name=truman1 /> According to [[Stephen Meyer]], scientists usually distinguish two basic types of information: meaningful or functional information and so-called Shannon information<ref name=doubt>{{cite book|author=Meyer, Stephen C|authorlink=Stephen Meyer|title=Darwin's Doubt: The Explosive Origin of Animal Life and the Case for Intelligent Design|publisher=HarperOne|/HarperCollins Publishers|location=Seattle, WA|year=2013|page=164-168|isbn=978-0-06-207147-7}}</ref> (named after Claude Shannon, who developed statistical information theory). Shannon information is really not the same thing as meaningful information. Meaningful information, encoded into a language, can be measured statistically, per Shannon, but the measure is of the redundancy of the symbols, the so-called Shannon entropy,<ref group=nota>Shannon entropy is the average unpredictability in a random variable, which is equivalent to its information content.</ref> not a measure of the "information content", or meaning. Shannon, for example, can be uses to measure the "information content" of a set of random symbols that have no meaning.