A covered gift for Christmas

Wait a minute! What is Eaton’s? Who is Eaton? For those of us that are not Canadian or don’t know much about history of Canada, those are the first questions we must answer. At least, this was my case.

Thanks to Wikipedia, now I know Timothy Eaton founded Eaton’s in 1869 in Toronto, Eaton’s became was once Canada’s largest deparment store retailer and its catalogue was found in the homes of most Canadians.

Once I laid the groundwork, I chose my books from the Eaton’s Fall and Winter catalogue from 1913-14. I wish I could have got a pic of the cover, but I did not find it either Archive.org or Google Books, or Hathi Trust or Gutenberg Project. Or Google Images. There are many others Eaton’s catalogue but not just the Fall and Winter from 1913-14, number 108.

My books were selected from Books for young people section.

I tried to search for old but quality editions. There they go:

1) The illustrated natural history, John George Wood

Fig.01 Wood's illustrated natural history

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

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2) Robinson Crusoe, Danie Defoe

Fig.02 Robinson Crusoe

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Gutenberg Project
Overview | Full-text

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3) Through the looking glass and what Alice found there, Lewis Carrol

Fig.03 Through the looking glass and what Alice found there

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

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4) Fairy Tales, Hans Christian Andersen

Fig.04 Andersen's Fairy tales

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

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5) Alice’s adventures in Wonderland, Lewis Carrol

Fig.05 Alice's adventures in Wonderland

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

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6) Black beauty, Anna Sewell

Fig.06 Black beauty

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

7) A child’s garden of verses, Robert Louis Stevenson

Fig.07 A child's garden of verses

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

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8 ) Gulliver’s Travels, Jonathan Swift

Fig.08 Gulliver's travels

Archive.org
Overview | Full-text

Google Books
Overview | Full-text

Hathi Trust
Overview | Full-text

Gutenberg Project
Overview | Full-tex

9) Mother Goose’s rhymes jingles and fairy tales

Fig.09 Mother Goose's rhymes jingles and fairy tales

University of Florida, Digital Collections
Overview | Full-text

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10) A child’s story of the Bible, Mary Artemisia Lathbury

Fig.10 A child's story of the Bible

Archive.org
Overview | Full-text

Gutenberg Project
Overview | Full-tex

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11) A child’s life of Christ, Mary Artemisia Lathbury

Fig.11 A child's life of Christ

Archive.org
Overview |Full-text

Hathi Trust
Overview | Full-text

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12) Animal stories for little people, James Hartwell

Fig.12 Animal stories for little people

Amazon

Ebay

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During this search, I drew some conclusions:

It’s amazing that there are lots of old books, digitized and free. Although, on the other hand, it’s strange the issue of copyright: some editions have free full-text, however, others editions of the same book have copyright.

There are some interesting features in this websites. For example, Both Archive.org and Hathi Trust allow to sort by date. Hathi Trust also let you search only full view books.

Urls are other curious point. Gutenberg Project have very simple urls as long as Google Books have extremly complex and long ones (even its permalinks).

These four sites are basic to look for digitized content. If your search doesn’t success here, it rarely will success on other sites. There were two books I could not find here: Mother Goose’s rhymes jingles and fairy tales (that I found in the Digital Collection of the University of Florida) and Animal stories for little people (in sale on Amazon and eBay).

It was impossible to find out the author of Mother Goose’s rhymes jingles and fairy tales.

Some overviews include a QR-code of the books.

The first time I heard of these project was in a Digital History class but now it’s the first time I use them. I’m delighted. They are carrying out a hard work but it is worth. I will browse them for future researches for sure!

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Getting Started with Alaska: A Guide to Online Resources

Fig.01 Alaska

[This post was written by myself and corrected by my workmate and friend Camelia.]

GENERAL INFORMATION

Alaska is my favourite singer. Although she was born in Mexico City she has lived in Spain since she was 10. I grew up in my native Spain under her influence which has forever defined my musical tastes. I was also fortunate enough to attend six of her concerts. I have chosen Alaska for this project because I admire her and I feel we have a few dates in common:

  • Alaska sings “Jason y tú”, Alice Cooper’s “He’s back” cover, a song about the main character of Friday the 13th. This film is special to me because it premiered on the 13th of June 1980, exactly the same day I was born.
  • Alaska was also born on the 13th of June (although some years before).
  • Alaska got married on the 27th of May 2011, exactly the same day I did. (I came to know this a few weeks later.)

Biography

Fig.02 Alaska

Olvido Gara Jova, mostly known as Alaska, is a Spanish singer who was born in Mexico City in 1963. When she was 10, she went to live to Spain and at 14 she began her musical career. She became a symbol of the Movida madrileña and now she combines her artistic work with her studies on History. Her first band was called Kaka de Luxe (1977) and she didn’t sing, just played the guitar. This punk band was composed by Alaska, Carlos Berlanga (son of the Spanish film director Luis García Berlanga) and Nacho Canut, among others, and was the seed of the Movida madrileña. One year later Kaka de Luxe separated and Alaska, Carlos, Nacho and others formed Alaska y Los Pegamoides (1978). Then, they were considered one of the most important bands in Spain. At the end of 1982, they separated again and in 1983, once again, Alaska, Carlos and Nacho (and only they three) formed Alaska y Dinarama, even more important than the last, until 1989. From 1990 up to today, Alaska sing in Fangoria, the band formed by her and Nacho.

Fig.03 Punk

Here you can find out interesting things about Alaska’s life:

Discography

Kaka de Luxe (1977-78)

Fig.04 Kaka de Luxe

Kaka de Luxe (1978)

Las canciones malditas (1983)


“Rosario”, Kaka de Luxe, Kaka de Luxe:
http://www.youtube.com/watch?v=AilLqUe__L8

Alaska y Los Pegamoides (1978-1983)

Fig.05 Alaska y Los Pegamoides

Grandes éxitos (1982)

Alaska y Los Pegamoides (1983)


“Bailando”, Alaska y Los Pegamoides, Grandes éxitos:
http://www.youtube.com/watch?v=R2EnbNk4wIc

Alaska y Dinarama (1983-1989)

Fig.06 Alaska y Dinarama

Canciones profanas (1983)

Deseo carnal (1984)

No es pecado (1986)

Diez (1988)

Fan fatal (1989)


“A quién le importa”, Alaska y Dinarama, No es pecado:
http://www.youtube.com/watch?v=adMdjZAGC5g

Fangoria (1990-today)

Fig.07 Fangoria

Salto mortal (1990)

Un día cualquiera en Vulcano (2003)

Interferencias (1998)

Una temporada en el infierno (1999)

Naturaleza muerta (2001)

 

Arquitectura efímera (2004)

El extraño viaje (2006)

Absolutamente (2009)

El paso trascendental del vodevil a la astracanada (2010)

“Electricistas”, Fangoria, Una temporada en el infierno:
http://www.youtube.com/watch?v=3Y35fPO7RLU

As a soloist

Fig.08 Alaska como solista

La bola de cristal (1985)

“Abracadabra”, Alaska, La bola de cristal:
http://www.youtube.com/watch?v=aa-NtA22sHc

Bibliography

Alaska is the author of “Transgresoras”, a book about the most important women in History that she admires, from Cleopatra, Eleanor of Aquitaine, to Dian Fossey.
Alaska herself is the target of two biographies: “Alaska”, written by Mario Vaquerizo (her husband) and “Alaska y otras historias de la movida”, by Rafa Cervera.

Transgresoras, Olvido Gara Jova (Alaska)

Amazon:
http://www.amazon.es/Transgresoras-Libros-Singulares-Alaska/dp/8427029772/ref=sr_1_3?ie=UTF8&qid=1323647084&sr=8-3

Alaska, Mario Vaquerizo

Amazon:
http://www.amazon.es/Alaska-Mario-Vaquerizo/dp/8479744553/ref=sr_1_1?ie=UTF8&qid=1323647157&sr=8-1

Alaska y otras historias de la movida, Rafa Cervera

Amazon:
http://www.amazon.es/Alaska-y-otras-historias-movida/dp/8401378087/ref=sr_1_1?ie=UTF8&qid=1323647229&sr=8-1

 

Filmography

Fig.09 Alaska and Pedro Almodóvar (old)

Fig.10 Alaska and Pedro Almodóvar (new)

Alaska is a multifaceted artist. Besides singing, she is a radio host and appears on TV shows (the last one was “Alaska y Mario” on MTV Spain). She also acted in several movies. Her most important role was “Bom” in “Pepi, Luci, Bom y otras chicas del montón”, Pedro Almodóvar’s first film. (This scene may offend your sensibility. It is subtitled in English. The original sound is unsyncronous with the picture:)
http://www.youtube.com/watch?v=xSch7pVDqHo

 

 

Pepi, Luci, Bom y otras chicas del montón, Pedro Almodóvar

 

Other information

Fig.11 Alaska - Gioconda

Alaska borrowed her name from Lou Reed’s “Caroline Says II”. She was influenced by David Bowie (another idol of mine) and the glam. She has actively fought in favour of homosexual rights. Alaska considers herself an advocate for animals and, more explicitly, anti-bullfighting. She supports drugs legalization and has openly admitted to be anti-religion. She is interested in medieval history and is currently studing an undergraduate degree in History.

Fig.12 Alaska - Virgin

Fig.13 Bartlaska and The Simpsonoides

 

 

 

 

 

 

 

 

 

 

All these personal web pages and blogs contain very interesting information. However, they often tend to be subjective. The most unbiased information can be found on Wikipedia. Crowdsourcing avoids personal opinions.
http://es.wikipedia.org/wiki/Alaska_%28cantante%29

Fig.14 Alaska anti-bullfighting

From now on, this post will also be an important reference of Alaska (in English!).

ALASKA’S LOOK

Fig.15 Alaska's looks

Hey girls, if you have liked Alaska’s style, there is a website gives you some steps in order to look like her:
http://magentamadness.blogspot.com/2009/11/look-alaska.html

OTHER SOURCES

Alaska’s Facebook page:
https://www.facebook.com/pages/Alaska/32998704065

Fangoria’s web page:
http://www.fangoria.es/

Alaska and Mario (her husband)’s blog:
http://blogs.libertaddigital.com/alaska-y-mario/

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How would a historian tag my blog?

Tagging blog’s posts is a good practise of bloggers. It is an easy way to classify contents, which helps readers to search for information. I created this blog for Digital History class but I have not either categorized or tagged. This class is leaded by a historian mainly for historians. How could I be sure of choosing the proper historian tags? How would a historian tag my blog? In this post, I present my experiment.

The idea is to study how historians tag their own blogs and apply their tags to my blog. For this, it is necessary to analyze historians post contents, my own posts and deduce what of their tags are relevant to my blog. Let’s go!

The first step was to look for appropiate blogs. I thought that I should use at least two tagged blogs. My first option was Bill Turkel’s blog, williamjturkel.net/updates/, but Bill does not usually tag this blog, so I had to search Google “digital history blog”. I found one called Digital History Hacks (2005-08) and yeah!, it is another (older) Bill’s blog (casualty?). I decided that the second blog should be one of my classmates’. I explored all their blogs and the only one full of tags was Dave’s. So Backwards with Time was my second choice.

Once I had my two blogs, the second step was to select their posts. 20 posts would be enough: 15 from Bill’s and 5 from Dave’s. For each post, I extracted the 10 most frequent words (I call this set keywords) and associated them to the tags supplied by the bloggers. I used Wordle to achieve it. Wordle is an online tool that read a text and show its word cloud.

Fig.1 Word cloud

Wordle also offer a tool to count words and sort by frequency. I had to discard some common words and select the important ones. For the example in Fig.1, I set up the next keywords: {physical, past, machine, fabrication, spaces, historians, history, digital, humanist, computer} for one of the Bill’s posts. And the tags supplied by Bill were: {bricolage, DIY, fabrication, hacking, physical computing}. Here is the complete set of posts along with extracted keywords and blogger’s tags. And here are my posts (remember that my blog has no tags, that is the reason for this experiment):

a)
https://antoniojimenezmavillard.wordpress.com/2011/10/31/a-new-scarcity/
Keywords: web, information, knowledge, machine, data, semantic, historians, abundance, technologies, computer.

b)
https://antoniojimenezmavillard.wordpress.com/2011/10/16/neither-field-nor-fad-nor-fashion/
Keywords: digital, history, internet, technologies, field, future, fashion, research, world, past.

c)
https://antoniojimenezmavillard.wordpress.com/2011/10/02/what-is-real/
Keywords: life, real, world, virtual, Internet, users, cyberspace, facebook, examples, friends.

d)
This entry corresponds to this post, which did not exist when I did the experiment. However, I knew the issue of it and I added some keywords according to my own criterion.
Keywords: blog, data, historians, online, programming, tag.

The third step was to apply some Artificial Intelligence technique to deduce the tags for my posts by basing on their keywords and keywords and tags from the posts before. This collection of 20 posts is called training set in Machine Learning field. The technique would be the ID3 algorithm. This algorithm can deduce the value of an attribute from other attributes. That is, ID3 works with a set of examples (training set). Each example has attributes and one of them is the target (that we want to learn about). In the training set all the information is provided. For example, Fig.2 shows “real facts” about what days a team played ball.

Fig.2 Example of training set

What will happen the day D15 and others? ID3 can deduce whether the team will play or will not by basing on the outlook, temperature, humidity and wind of that day. For that, ID3 builds a decision tree* (Fig. 3):

Fig.3 Decision tree

Or expressed in rule format*:

  • IF outlook = “sunny” AND humidity = “high” THEN play ball = “no”
  • IF outlook = “sunny” AND humidity = “normal” THEN play ball = “yes”
  • IF outlook = “overcast” THEN play ball = “yes”
  • IF outlook = “rain” AND wind = “strong” THEN play ball = “no”
  • IF outlook = “rain” AND wind = “weak” THEN play ball = “yes”

* In order to build the smallest tree (the simpliest rules) it is necessary to choose on top the tree the “best” attributes, that is, the attributes with the least entropy (entropy gives an idea of homogeneity).

The pseudocode of ID3 can be found here.

My goal was to apply ID3 in order to teach the computer the rules to, given the training set of posts, learn when a tag appears in a post and when not (I mean, its classification). In this experiment, an example is a post, an attribute is a keyword and the target is a tag.

First of all, I had to set up the total set of keywords: the intersection of my own keywords and historians’ ones (19 in total): {blog, computation, data, digital, examples, historians, history, information, knowledge, past, reality, research, users, virtual, web, world, online, programming, tag}. It is necessary to say that some keywords with similar meanings were fusioned into one (for instance, computer and computation). Secondly, I had to choose what tags from training set were relevant to my blog (I mean, the most likely tags applicable to my posts). I selected these 30: {browser, computational history, data mining, digital, digital history, diy, entropy, google, history, html, interdisciplinarity, machine learning, markup language, ocr, online research, physical computing, programming, reality, representation, search, search engines, teaching, technology, text mining, thing knowledge, turing test, virtual reality, web resources, wikipedia, wikis}.

At this point, I had 20 posts, 19 keywords and 30 tags. For each post, which is the correspondence between its keywords and its tags?

Fig.4 Training set

The training set is displayed in Fig.4. For each post, a “” (“yes“) means that the post has the keyword and “no“, the opposite. The fourth step was to programme the ID3 algorithm and represent this information properly. I had to add a last column with the tag I wanted to learn and give the values for each historian’s blog. I repeated the process 30 times (one for each tag)! The programming language I best know is Java, and I found an implementation of ID3 in this language, so the only thing I needed was to create a project in Eclipse, provide the training set in a proper format and run the application. As an example, here is the rule to learn when a post have to be tagged/classified as “history”:

  • IF knowledge = “no” AND world = “no” THEN history = “no”
  • IF knowledge = “no” AND world = “yes” AND digital = “yes” THEN history = “no”
  • IF knowledge = “no” AND world = “yes” AND digital = “no” THEN history = “yes”
  • IF knowledge = “yes” THEN history = “yes”

That means, “if keyword knowledge belongs to the post, then the post is tagged with history; in other case, if knowledge doesn’t belong, but world does and digital doesn’t, then the post is tagged with history too”. This rule expresses the idea that (traditional) history is linked to knowledge and world, but not to digital. On the other hand, the rule that learn digital history set that this tag is related in some sense to online, history, digital, knowledge, historians and web (this rule is too complex to be shown).

The fifth step is, for all rules learned, to check if my posts satisfy them. According to the example above, the post titled A new scarcity has the tag history. Actually, is the only post where I mention History in the past and compare it with current methods of doing History. I did this step manually, i.e., I analyzed every rule and checked if the tag was suitable for each of my posts.

Results

The result was a set of learned tags* for my posts. My blog was originally untagged but now it has its own tags!

a)
https://antoniojimenezmavillard.wordpress.com/2011/10/31/a-new-scarcity/
Keywords: web, information, knowledge, machine, data, semantic, historians, abundance, technologies, computer.
Tags: browser, data mining, digital history, google, history, html, interdisciplinarity, machine learning, markup language, technology, text mining, virtual reality, web resources.

b)
https://antoniojimenezmavillard.wordpress.com/2011/10/16/neither-field-nor-fad-nor-fashion/
Keywords: digital, history, internet, technologies, field, future, fashion, research, world, past.
Tags: digital history, google, online research, search engines, teaching, technology, virtual reality, web resources, wikipedia.

c)
https://antoniojimenezmavillard.wordpress.com/2011/10/02/what-is-real/
Keywords: life, real, world, virtual, Internet, users, cyberspace, facebook, examples, friends.
Tags: digitial, digital history, history, online research, reality, virtual reality.

d)
This entry corresponds to this post, which did not exist when I did the experiment. However, I knew the issue of it and I added some keywords according to my own criterion.
Keywords: blog, data, historians, online, programming, tag.
Tags: data mining, digital history, entropy, machine learning, ocr, programming, text mining, turing test, wikis.

*green = suitable tag
*red = unsuitable tag

Conclusions

This experiment has shown some interesting results to me:

  1. About 75% of tags are suitable with the post content.
  2. Every posts were tagged as “digital history” (good… after all, this is a blog for Digital History class).
  3. A new scarcity was tagged with so relevant tags like “google“, “markup language” (let’s remind that this post mentions XML) or “web resources“.
  4. Neither field nor fad nor fashion was classified as “online research“, “search engines” or “web resources“.
  5. “What is real?” was tagged with coherent tags such as “reality” or “virtual reality” (just the topics of this post).
  6. This post has been tagged with “data mining“, “entropy” (remember that entropy was not a keyword of this post and even so, it has been correctly classified), “machine learning“, “programming“, “text mining” or “turing test” (a test of a machine’s ability to exhibit intelligent behaviour).

These results may not be perfect and the methodology followed is far from scientific method. However, it is a good approach. And this prove one more time the power of Artificial Intelligence, in this case, Machine Learning and ID3 algorithm.

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A new scarcity

The World Wide Web (WWW) has grown exponentially since 1989, when its inventor, Tim Berners-Lee, created a system of hipertextual documents linked and accessible through the Internet. They were called web pages (or just webs) [1]. Between 1993 and 1995, the number of web servers (the computers that house websites) jumped from 130 to 22,000 [2]. Gulli and Signorini estimated that the Web had more than 11.5 billion pages in 2005 [3]. According to Internet Archive’s website (www.archive.org/about/faqs.php), its historical record of the web contains approximately one petabyte (1,024 terabytes) of data and is growing ate the rate of 20 terabytes per month [4].

Thanks to the great development the Web has experimented since its origin, some aspects of daily life have changed heavily, for example, personal communication, business or research. This revolution is transforming the world by leading it to Information Society. And it is still changing towards Knowledge Society and Knowledge Economy, where knowledge is considered the main asset of economy dinamics. For this reason, business and research will likely succeed if they manage projects based on knowledge/information.

Historians are taking advantage of current technology. Museums and archives are digitizing their material to both preserve and extend user access to cultural heritage content. Some of these projects are Project Gutenberg, Million Book Project, Internet Archive, Bibliotheca Alexandrina, Amazon, Google Books or Open Content Alliance [4]. Not so long ago, historians worried about the small numbers of people they could reach, pages of scholarship they could publish, primary sources they could introduce to their students, and documents that had survived from the past. Digital technology has removed many of these limits [5]. Now they are living a transition from scarcity to abundance.

Still, the astonishingly rapid accumulation of digital data (obvious to anyone who uses the Google search engine and gets 300,000 hits) should make us consider that future historians may face information overload [5]. Information overload, also called infoxication (information + intoxication), is not an issue that just concerns to archivists, librarians and journalists. Internet is able to intoxicate every single user with its huge amount of knowledge. Too much information is not always the best. In fact, it tends to generate confusion. I have myself lots of resources available when I need to search information: Google,Wikipedia, UWO Library Catalogue (alpha.lib.uwo.ca/), databases (SpringerLink, IEEE, etc) and so on. Sometimes, you do not know where to start.

Information overload is not a new concept. It has been a preoccupation since the Middle Ages [6]. Immanuel Kant warned that “pure information without selection criteria is blind. Francis Bacon and Karl Popper added that “Nature will be mute while we do not learn to make it talk with both relevant and purposeful questions” [7]. By the way, this latter cite reminds me certain similitude between Nature and how we have to behave in relation to a search engine in order to extract useful information from the Web.

The struggle to incorporate the possibilities of new technology into the ancient practice of history has led, most importantly, to questioning the basic goals and methods of historians’ craft. And they should continue taking steps individually and within their professional organizations to embrace the culture of abundance made possible by digital media [5]. However, such abundance of information can cause users to have difficulty finding relevant and interesting content [8]. We, computer scientists, are familiar with this problem. As far as I am concerned, meaning of scarcity is currently changing from “a lack of quantity to “a lack of quality. That is, “lack of useful content”. Historians need tools that help them deal with such abundance of information. It is necessary to find the float in the sea of knowledge, to find the needle in the haystack.

The main obstacle to provide better results to users is the Web itself. Its content is not undertandable by machines (only by humans). In other words, the Web does not incorporate mechanisms that allow automated processing of information. In order to overcome this problem, the solution more broadly supported all over the world is to represent the Web content in a formal way (processable by machines) and to use techniques based on Artificial Intelligence to take advantage of this sound representation. This plan to revolutionize the Web is called Semantic Web (semanticweb.org/wiki/Main_Page).

The Semantic Web is an attempt to enrich web pages so that machines can cooperate to perform inferences in the way that people do. The underlying idea is to give information a well-defined meaning specifically in order to enable interaction among machines [4]. When Tim Berners-Lee created the Web, his original idea was not the Web as we know today. His idea was the Semantic Web. He explains his own concept [1]:

“The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web, a web of data that can be processed directly or indirectly by machines.”

That is, information is organized in a way machines can interpret its meaning, like in a database. For example,

<?xml version=”1.0″ encoding=”ISO-8859-1″?>
<book>
<title> The Neverending Story </title>
<author> Michael Ende </author>
<year> 1979 </year>
</book>

A standard for describing books and other resources is the Dublin Core Metadata Standard (dublincore.org/). Information structured this way will enable questions such as “Who wrote The Neverending Story”. Notice that simple questions like this or like “Qué es La Historia Interminable” (in Spanish) can be currently answered by Google. In the future, every kind of question will be answered by semantic tools, no matter how complex it is.

Computer scientists are working hard to develop this technology and the tools that let researchers organize knowledge and extract it from structured information. There are lots of interesting applications. For instance, a tool for Medieval document XML markup. Its authors present a novel tool-suite supporting the working historian in the transcription of original medieval charters into a machine-readable form (XML) [9]. The Catalogus Professorum Lipsiensis is an application of an adaptive, semantics-based knowledge engineering approach for the development of a prosopographical knowledge base on the Web, which enable historians to collect, structure and publish prosopographical knowledge . The resulting knowledge base contains information about more than 14.000 entities and is tightly interlinked with the emerging Web of Data [10]. The Timeline tool (www.simile-widgets.org/timeline/) is basically an API for visualizing historic events. All you need is to mark up your data in XML [11]. Exhibit (www.simile-widgets.org/exhibit/) is a lightweight structured data publishing framework that lets you create web pages with support for sorting, filtering, and rich visualizations. The only web technology you need is HTML and, optionally, some CSS and Javascript code [11].

Historians should embrace these new tools to isolate the relevant data from the abundance, to find the needle in the haystack.

The needle in the haystack

The needle in the haystack

References
[1] T. Berners-Lee, Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web, Harper, San Francisco, USA, 1999
[2] D. J. Cohen and R. Rosenzweig, Digital History: A Guide to Gathering, Preserving, and Presenting the Past on the Web, University of Pennsylvania Press, Philadelphia, USA, 2006
[3] A. Gulli and A. Signorini, The Indexable Web is More than 11.5 Billion Pages, ACM, Chiba, Japan, 2005
[4] I. H. Witten, M. Gori and T. Numerico, Web Dragons: Inside the Myths of Search Engine Technology, Morgan Kaufmann, San Francisco, USA, 2007
[5] R. Rosenzweig, Scarcity or Abundance? Preserving the Past in a Digital Era, American Historical Review vol. 108 n. 3, pp. 735-762, 2003
[6] La Infoxicación en el Siglo XVI, 2007 [http://www.documentalistaenredado.net/495/la-infoxicacion-en-el-siglo-xvi/]
[7] X. Rubert de Ventós, La Red del Pescador, 2008 [http://www.elpais.com/articulo/opinion/red/pescador/elpepiopi/20080706elpepiopi_5/Tes]
[8] H. Cramer et al., The Effects of Transparency on Trust in and Acceptance of a Content-Based Art Recommender, User Model User-Adap Inter vol. 18 n. 5, pp. 455-496 , Springer, 2008.
[9] B. Burkard , G. Vogeler and S. Gruner, Informatics for Historians: Tools for Medieval Document XML Markup, and their Impact on the History-Sciences, Journal of Universal Computer Science vol. 14 n. 2, pp. 193-210 , 2007
[10] T. Riechert et al., Knowledge Engineering for Historians on the Example of the Catalogus Professorum Lipsiensis, ISWC’10 Proceedings of the 9th international semantic web conference on The semantic web vol. 2, Springer, 2010
[11] S. Fischer, History Museums and the Semantic Web, 2007 [http://publichistorian.wordpress.com/2007/01/16/history-museums-and-the-semantic-web/]

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Neither field nor fad nor fashion

“Is Digital History a field, a fad or a fashion?” This was one of the topics argued in class.

As I read in Interchange: The Promise of Digital History, digital history was defined as “anything (research method, journal article, monograph, blog, classroom exercise) that uses digital technologies in creating, enhancing, or distributing historical research and scholarship”. “Technologies” refers to “technologies of the computer, the Internet network, and software systems”, as William G. Thomas pointed out.

Why is not digital history a field? Throughout history, technology has entered our lives. From the wheel to computers, technologies have become our lives easier. Particularly, inventions like the printing press or the Internet have revolutionize our History and the way (and speed) it is told. However, such inventions do not tell a new History but History. Technology has changed our world and our history, but they have not created new ones. In this sense, Internet and digital technologies must be seen as transversal tools in the service of existing disciplines.

The European Printing Press, 15th century

Why is not digital history a fad or a fashion? Daniel J. Cohen and Roy Rosenzweig assert: “The past was analog. The future is digital. Tomorrow’s historians will glory in a largely digital historical record, which will transform the way they research, present, and even preserve the past.” (Digital History: A Guide to Gathering, Preserving, and Presenting the Past on the Web). I should say that future has already arrived. Alex de la Iglesia (former president of Spanish Film Academy) said in the speech he pronounced due to the 25th anniversary of Goya Awards (our “Spanish Oscar”) that “Internet no es el futuro, como algunos creen. Internet es el presente.” (“Internet is not the future, as some people believe. Internet is the present.”). I cannot imagine a world without electric light bulb or telephone. Obviously, when something works, it lasts forever.

So what is digital history? It is just History when it “makes use of sources in digital form” (my teacher, William J. Turkel).

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“What is real?”

That was the question a classmate asked in class two weeks ago. Blown to Bits use expressions like “real life” and “cyberspace” to differenciate between our everyday life and our life on the Internet. But, is there any difference between these two worlds?

Cyberspace is not a dream. Internet is composed by millions of computers interconnected. And, of course, they are reals. Well-known ones and zeros are electrical signals that are transmitted by cables or waves. It seems obvious because all these things are physical objects. But what happens “inside the Internet”, beyond the material? Let’s see some examples:

  • Messenger (and similars) allow users to be connected. They can chat and set up videocalls. Friends are sometimes far away from each other and this is one possible way of keeping in touch. Is this a fake communication? I don’t think so.
  • Lots of lonley souls have met on chats or specialized webs and now they are happy couples. First time they met face to face, they already knew each other in a certain sense.
  • Facebook let users share photos and comment them. Friends plan events that come true in “real life”. Even there are people who claim that “if it is not on Facebook, it never happend”.
  • Second Life is a project where users can create a customized avatar which lives in a “virtual world”. But this world is not as virtual as it looks. People can interact like in real world. They can socialize and trade. Companies such as Sony, Coca Cola or Microsoft (among many others) have set up business and they insert ads everywhere. US dollars can be interchanged in virtual dollars.
  • A lot of virtual shops sell books, clothes, videogames… and the purchased articles arrive our homes! Check your bank account and realize the cruel reality.

These examples prove that cyberspace is not a fantasy. It is as real as “real life”. Then, why is there this artificial difference between the two realities? The key is survival. Virtual world is dispensable: you do not need chating, buy online or public a photo (although you will stay behind because life is, in fact, digital). Unlike cyberspace, we have to survive in our daily lives: you have to study, you have to work, you have to earn money, you have to eat, you need human contact…

These facts make this life become the real life, the life that has always existed. But, nowadays, what is real? Everything.

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My first post

This is my first post!

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