Publishing, Positioning, and Fixity

LAPIS Posts

The continuation of this blog will focus of the modules Libraries and Publishing in an Information Society (LAPIS). Future posts will likely be an examination of class notes and analysis of any outside reading undertaken for this part of the #citylis course.

Benjamin on Intellectuals

Walter Benjamin’s “The Author as Producer” served as the main text for the first session of the term. Various points were addressed including the understanding of an intellectual’s position within the means of production of their works. Benjamin (p.92) expressed the issues surrounding the introduction of intellectuals into the struggle of the proletariat:

The metamorphosis of the political struggle from a drive to make a political commitment into an object of contemplative pleasure, from a means of production into an article of consumption, is characteristic of this literature.

Benjamin stated that, if the intellectual is unwilling to recognise his or her position, then he or she will not make the necessary connections with the proletariat. While originally a piece on publishing and Marxist politics, the need for authors to position themselves within the social context of their time and realise their own bias and privilege still rings true today.

Fixity and E-Books

Benjamin cricised those producers who place too much emphasis on content rather than form. The class discussion regarding content and form of e-books reminded me of my research for a paper on Gutenberg’s printing press and its influences on the LIS professions. Specifically, I recalled Elizabeth Eisenstein’s term “typographical fixity”. Simply defined, the term means the permanence of an original written work. Before the printing press, many classical works had been lost, but, with the introduction of the press, massive amounts of copies were created and disseminated lessening the chances that a work would be lost forever.

With the introduction of e-books, authors and publishers can easily edit and update the books as they wish, and customers can choose to receive or reject these changes. Each time a person turns on their Kindle, they may encounter a new version of a published work. Thus, fixity no longer exists due to the original work vanishing from the electronic readers. A multitude of updates can be performed, which leads to each new incarnation being perceived as a new work just as each edition of a past book is considered a separate creation. In his post “Words in stone and in the wind”, Nicholas Carr explored in further detail the loss of fixity in relation to editions, permanence, and completion of works. Here I will close with a quote from Carr (2012) in which he describes the impact of technology on print culture:

The permanence of a book is not just a function of technology, of course. Many other factors – laws, commercial interests, reader preferences and habits – also exert an important influence. But technology matters, and it seems likely that we’ll be celebrating, and rueing, the consequences of today’s epochal shift from printing to electronic publishing for centuries to come.

References and Further Reading

Adams, E., 2010. Content and Form Aren’t Equal: A Discussion with Ernesto Priego. [online] Phoenicia Publishing. Available at: [Accessed 5 Feb. 2015].
Benjamin, W., 1970. The Author as Producer. New Left Review, (62), pp.83–96.
Carr, N., 2012. Words in stone and on the wind. ROUGH TYPE. Available at: [Accessed 3 Feb. 2015].
Coetzee, J.M., 2015. The evolution of Walter Benjamin’s masterpiece. [online] the Guardian. Available at: [Accessed 2 Feb. 2015].
Eisenstein, E.L., 2005. The printing revolution in early modern Europe. Second ed. New York: Cambridge University Press.

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An End Has a Start: DITA Blog Completion

Blog Completion

Throughout the Digital Information Technologies and Architectures module, I have tackled my nerves revolving around blogging and presented what I hope to be an overview of things during the journey from bits to websites. Readers will note that no drastic alterations occurred to the information architecture of the blog. Based on user feedback and personal usage, the blog has carried out its intended purpose to be both user friendly and aesthetically pleasing. I have stayed true to the information architecture concepts of “findability” and proper organisation in my blog. Throughout the rest of the course, I plan to continue this blog since the benefits of writing up my personal notes here have been significant. Also, this experience has inspired me to begin another blog as well!

To illustrate the main themes of Studies in DITA, I created the following text analysis visualisation for the completion of the blog:

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Module Thoughts

From addressing the basics of information architectures to the development of the Semantic Web, my classmates and I embarked upon a voyage to better understand the use and management of digital data. The knowledge the module has fostered will surely follow us into our careers.

The topics discussed ensure we have the information and tools to be on the cutting edge of what is occurring in many disciplines. We examined patrons’ natural language searching tendencies in relation to information retrieval which led to me addressing my past experiences instructing information literacy classes. After the class on APIs, I investigated the importance of APIs to businesses. By understanding and implementing of altmetrics in our evaulation of search results, we (as information professionals) can discover aspects such as popularity of certain articles. Through text and data mining, we can speed up the process of analysing the massive amounts of digital texts accumulating as the Web grows and apply various tools such as Voyant to dig deeper into the texts. Another skill we developed is the ability to comprehend and inspect basic markup languages. Before this module I had only a basic understanding of HTML, now I can confidently evaluate the contents of more complex systems such as an XML tree or RDF data model. Hopefully, I have conveyed the valuable knowledge gained through the course of this blog.

Information Professionals Today

Overall, the DITA module has expanded my skills and broadened my view of what information professionals are qualified to do upon the completion of the #citylis course. With that in mind, I’d like to close this post with a quote from David Bawden and Lyn Robinson’s Introduction to Information Science (2012, pp. 157):

Researchers and practitioners in the information sciences can be designers, as well as users, of technology systems, particularly in HCI and information architecture, as well as in the obviously relevant applications in the organization and retrieval of information.

Reference

Bawden, D. and Robinson, L. 2012. Introduction to Information Science. London: Facet Publishing.

Reviving It with Close Inspection: Data Mining, the Old Bailey, and CKCC

Searching and the Old Bailey API

On the Old Bailey Online website, users scour the criminal proceedings of the Old Bailey court from 1674 to 1913. Basic patrons find results using the original search while researchers will prefer querying the API for more in-depth textual analysis. With the use of the API Demonstrator, “…result sets can then be explored – either through modifying the query (undrilling), or through breaking down the results by any of the available sub-categories of tagged data, and by all words in each trial.” Thanks to the Datamining with Criminal Intent project, researchers can export their results from the Old Bailey Online to Zotero and Voyant Tools and conduct further analysis.

Below is an example of one of the searches I have conducted:

Old Bailey API

Note the features to the right of the image labelled “undrill” and “drill” which I engaged. The image below shows the changes.

Old Bailey API 2

Voyant Tools and the Old Bailey API

Looking to the right of the screen, researchers will have the option to “Send to Voyant” for further analysis. Voyant Tools has many advantages like the ability to remove common words from various languages, count the occurrences of a particular word, view word trends over the whole of the text, and place the words found in their context quickly.

While visualisation tools provide researchers with a concise way of presenting and explaining a large collection of data, caution is necessary when making assumptions based on the analysis derived. However, resulting incorrect information may begin even before the visualisations are created. In the final white paper for the Datamining with Criminal Intent project, the researchers touched on this point stating the results may reflect “…the prejudices the user brings to each search and those applied by the team that provided the XML markup when the digital archive was first created.” (Cohen 2011)

Text Mining for the Old Bailey Online and Circulation of Knowledge and Learned Practices in the 17th-century Dutch Republic (CKCC)

For a comparison of analysis with the Old Bailey, I have chosen the CKCC project based partially on the contrasts between the projects but also due to my past historical studies of the 17th Century Dutch Republic. Upon review, I have found the CKCC employed the following data analysis methodologies: topic modeling, keyword analysis, natural language processing (NLP), spelling normalisation, named entity (NER), and visualisations. The most striking difference between this project and the Old Bailey project is the user participation aspect. While the CKCC had clear questions for researchers to consider when looking into the data, the Old Bailey seemed to equip the users with researchers run wild within the API and see what they can discover. Since the CKCC project is still in progress, access is not granted to outside researchers and scholars. Upon the completion of the project, the goal is to have a collection of openly accessible historical documents.

References

CKCC. 2014. Methodology- CKCC. [Online]. [Accessed 29 November 2014]. Available from: http://ckcc.huygens.knaw.nl/?page_id=13/

CKCC. 2014. Research Questions- CKCC. [Online]. [Accessed 29 November 2014]. Available from: http://ckcc.huygens.knaw.nl/?page_id=75

Cohen, Dan, et al. (2011). “Data mining with criminal intent.” Final white paper. [pdf]. [Accessed 29 November 2014]. Available from: http://criminalintent.org/wp-content/uploads/2011/09/Data-Mining-with-Criminal-Intent-Final1.pdf

Voyant Tools. 2014. Voyant Tools: Reveal Your Texts. [Online]. [Accessed 30 November 2014]. Available from: http://voyant-tools.org/

Zotero. 2014. Home. [Online]. [Accessed 30 November 2014]. Available from: https://www.zotero.org/

Ch-Ch-Ch-Ch-Changes: Text Analysis and the Digital Age

Text Analysis

Johnny Holloway (2007) defines text analysis as: “a variety of social science research methods designed to ascertain meaning and bring structure to large amounts of unstructured information derived from different acts of communication embodied in written language.” In order to better understand the concept of text analysis, here is a list provided by Duke University Libraries (no date) as an overview of the basics:

  • Word frequency (lists of words and their frequencies)
  • Collocation (words commonly appearing near each other)
  • Concordance (the contexts of a given word or set of words)
  • N-grams (common two-, three-, etc.- word phrases)
  • Entity recognition (identifying names, places, time periods, etc.)
  • Dictionary tagging (locating a specific set of words in the texts)

With these basics in mind, I will give a brief overview of the acceptance in academia and in this past week’s DITA lab.

Acceptance in Academia

So, what can researchers gain from text analysis? Matthew L. Jockers (2014: vii) addresses questions regarding whether his text analyses will bring new knowledge into the world by responding: “…not everything that text analysis reveals is a breakthrough discovery. A good deal of computational work is specifically aimed at testing, rejecting, or reconfirming the knowledge that we think we already possess.” He goes on to describe his text analyses of Moby Dick and using the results to support an already existing hypothesis which explained the book as “…a statistical mutant among a corpus of 1,000 other nineteenth century American novels.” (Jockers, 2014: viii) The importance of such work should not be overlooked as a large section of academic research exists to reinforce pre-existing theories.

Text Analysis and DITA

During the DITA lab session, my classmates and I explored text analysis ourselves using the tools Wordle and Voyant to create word clouds and easily analyse the date inputted. While Wordle is useful for identifying words most frequently occurring in a text, Voyant delivers additional tools which provide an overall better user experience and text analysis. Thus, all examples in this post will be pulled from that website.

The first visualisation I created (which has been updated since the lab session) was for the #HighgateCemetery tweets I have been gathering with TAGS. Please recognise that when employing these tools, it is best to use the options to remove all common words in the language of the text entered; these are known as stop words. Looking at the image below, the larger words were used more frequently than the smaller ones in the Tweets. Frequent tweeters using the hashtag will have there Twitter handles noted in the word cloud.

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The Voyant text analysis of the journal and article titles from the “history of ideas” altmetrics data (see blog post) formed the most interesting of the ones I created. Voyant enabled me to analyse the number of times a word appeared as well as the placement of the word. Selecting the word “history” under “Words in the Entire Corpus” shows me the word count and shows the trend analysis in the article titles. While the word “history” will be frequent due to the search being “history of ideas”, this gives a basic understanding of how Voyant allows researchers to understand research trends.

voyant

The possibility of frequent use of specific words also drove me to create a visualisation for this blog. The results are below.

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Changes in Text Analysis

For over a decade, the traditional methods of text analysis have greatly altered with the progress of digital technologies. Instead of performing text analyses by hand as done previously, researchers now use online tools such as Wordle and Voyant to explore documents. With these new methods, text analysis is catching up with the ever-growing pile of information published online.

References

Duke University Libraries [no date]. Introduction to Text Analysis . [Online]. [Accessed 22 November 2014]. Available from: http://guides.library.duke.edu/text_analysis

Holloway, J 2007, ‘Text Analysis’, in Neil J. Salkind, & K Rasmussen (eds), Encyclopedia of Measurement and Statistics, Sage Publications, Inc., Thousand Oaks, CA, p. 1000, [Accessed 22 November 2014], Available from: http://0-dx.doi.org.wam.city.ac.uk/10.4135/9781412952644.n454.

Jockers, M.L. 2014. Text Analysis with R for Students of Literature. [Online]. New York: Spring International Publishing. [Accessed 22 November 2014]. Available from: http://link.springer.com/book/10.1007%2F978-3-319-03164-4

Don’t You Know You’re Queen: Measuring Scholarly Impact through Altmetrics

Introduction to Altmetrics

Altmetrics (or alternative metrics) examine the impact of scholarly works through online channels. Previously, citations acted as the primary measure of impact. As digital technology progressed with the introduction of social media platforms such as Google+ and Twitter, both scholars and the public took to these services to promote research they found useful. Thus, the value of a scholar’s work has acquired new venues in which it is judged, discussed, and measured.

Altmetric Explorer

Various online tools provide researchers with access to altmetrics on their works. For this week’s DITA session, our class has used Altmetric‘s Altmetric Explorer. Through the service, users narrow down keyword search results through a range of filters including the journals the articles appeared in, the web services on which the articles were mentioned, and the publishing date range. Once completed, users can save the results under “My workspaces” and/or export the results to Excel to create a report. During my personal use of The Altmetric Explorer, I have produced a number of reports on subjects from King Richard III to free will.

Analysis of the results from my King Richard III search display four articles in the past six months have been promoted on the websites Altmetric’s API incorporates. One will notice the donut-like shape beside each article title, the number in the center marks the times the articles was shared or mentioned, while the individual colors on the donuts represent the services on which the articles were shared or mentioned. Thus, users can analyse the popularity of the articles easily.

alt 4

Criticisms of Altmetrics Data

As with any web service, there are bound to be issues. In Beyond Bibliometrics, Jason Priem summarises the main criticisms of altmetrics stating the “…concerns have tended to focus on three areas: a lack of theory, ease of gaming, and bias.” (Priem, 2014, p277) He addresses the first concern by noting that, while it is important, a new theory should not be a condition for the creation of a new field of study. Attempts at gaming the system in order to inflate the impact measures of one’s work is a valid concern in the processing of altmetrics data; however, Priem believes that over time the system’s ability to assess the content of its results will improve (Priem, 2014, p278). Acknowledging that a bias can occur within altmetrics data collection, Priem writes that “…a field like digital humanities, where anecdotal reports suggest a majority of scholars use Twitter, will of course generate different numbers of tweets compared with a more technologically conservation disciple.”(Priem, 2014, p279)

Conclusion

In conclusion, altmetrics are an invaluable tool for scholars to assess the impact of their work. Despite issues with data collection, the benefits of altmetrics largely outweighs the problems. As the use of altmetrics becomes more prevalent, so too will the awareness of scholars and the public of how simply sharing one link can influence further research.

References

Altmetric, Altmetric Explorer. Available from: http://www.altmetric.com/. [14 November 2014].

Priem, J., 2014. Altmetrics. In: B. Cronin and C.R. Sugimoto, ed. 2014. Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact. Cambridge: The MIT Press. Ch.14

When They Love You (And They Will): Research and Marketing through TAGS

Introduction to TAGS

In the world of the microblogging platform Twitter, hashtags are king for metadata collectors. They connect communities of people such as current and former #citylis students with their instructors and fellow classmates which enables the flow of information and knowledge between members. Also, the backchannels created by these community hashtags are invaluable to researchers who wish to track Tweets and their metadata during various conferences and events.

Researchers collect this data through a variety of programs. Our DITA class explored one created by Martin Hawksey. My #citylis classmates and I explored Hawksey’s TAGS which is a self-described “free Google Sheet template which lets you setup and run automated collection of search results from Twitter.” The template allows users to collect Tweets on a specific hashtag from eight days prior to the creation of the spreadsheet onward. Also, hourly updates can be scheduled easily. As seen in the summary page for my #HighgateCemetery spreadsheet, information is tabulated to assist researchers with basic questions about the small dataset.

TAGS Summary Highgate Cemetery

Two of the most useful aspects of TAGS are located in the bottom right-hand corner of the summary page: TAGSExplorer and TAGS Archive. TAGSExplorer (seen below) offers researchers a way to visualise the connections between the Twitter users incorporating a certain the hashtag in their Tweets.

TAGSExplorer

On the other hand, the TAGS Archive allows researchers to search their assembled Tweets for distinct keywords or phrases:

TAGS Archive

#HighgateCemetery and TAGS

For my TAGS spreadsheet, I examined the usage of #HighgateCemetery due to my curiosity about public interest in the historic site. Thus far, the Tweets gathered reflect a modest use of the hashtag since 23 October 2014 as seen in the summary page provided above. The majority of Tweets come from visitors to the cemetery.

The collection of this data leads to the question of possible benefits for Highgate Cemetery and its supporters. Through the analysis of the users who included #HighgateCemetery in their Tweets, one can determine if it was retweeted or favorited by any followers of the user. Questions concerning the popularity of the cemetery and ways in which one can increase the Tweets with #HighgateCemetery then arise. Social media marketing strategies such as including a reference to the Twitter hashtag on visitor literature for the cemetery could go a long way to increasing the social media visibility of the site. The conversations examined through the TAGS spreadsheet could also hold information for possible improving visitor experience at the cemetery and events for the cemetery.

Sharing of Twitter Metadata Collection

DITA instructor Dr. Ernesto Priego expresses in a May 2014 blog post that “…there is a wealth of data out there that, within the limitations imposed by the Twitter API and the archival methods we have at our disposal, can be saved and made accessible before it disappears.” He encourages researchers to make available their collected data for additional research and reuse. Otherwise, much of the data gathered will be lost to history.

Conclusions

Based on my findings, both researchers and heritage sites would benefit highly from the use of Twitter archiving services such as TAGS. The amassing information from services such as Twitter provide special insight to various communities and users which otherwise might be inaccessible. However, it is of the utmost importance to remember that the data protection rights of users must always come first, and the ethical use of all accumulated data should be a priority.

There’s Not an App for That: Treating Highgate Cemetery as an Archive

20141029_144201Highgate Cemetery is the resting place for some of the world’s most renowned philosophers, artists, and writers. The likes of Herbert Spencer, Karl Marx, and Douglas Adams are among the buried, but the contributions of many others here are forgotten.

 

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A notable aspect of the East map for Highgate Cemetery is the imbalanced gender ratio of those represented. Of the eight-nine entombed persons mentioned, only nine were women, the most famous being Victorian novelist George Eliot. Some might argue that perhaps there are not as many notable women buried within the cemetery, but I disagree entirely. The contributions of women such as German author Alice M. Ekert-Rotholz and fashion artist Hilary Joyce Bradshaw deserve to be remembered. Efforts should also be made in researching the backgrounds of the women listed only as wives of the men with whom they are buried.

So, how do we make information regarding the overlooked people buried at Highgate Cemetery available to the public? An idea may be pulled from the free iPhone app Welford Road Cemetery Trail. According to an article posted on De Montfort University Leicester (DMU)’s website:

The app has been created by computer and app design specialists at De Montfort University’s Digital Building Heritage Group for the Friends of Welford Road Cemetery group as one of 11 projects funded by a £71,671 Connected Communities research grant from the Arts & Humanities Research Council.

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Perhaps, this is an example Highgate Cemetery should follow. Since the cemetery is not maintained or funded by a local council, fundraising efforts will be required for the creation of such an application. The fees for special events could be increased as well as the entrance fee for the East Cemetery with a note that additional donations would go toward the creation of an smartphone application.

 

 

20141029_143656This undertaking will not be for the faint of heart since there are approximately 170,000 people entombed in 53,000 graves, volunteers in the Friends of Highgate Cemetery and members of the community might find this a worthwhile project. Crowd-sourcing information could begin with websites like Find A Grave, and from there researchers and possibly students would volunteer to assist with the project starting with Camden Local Studies and Archives Centre.

The additional information provided to patrons will encourage return visits with the added material available within the app. With Highgate Cemetery existing as an important historical landmark and an outdoor archive, people will rally around the preservation and dissemination of the information held there.

*A nod must be given to DITA professor Ernesto Priego. Some of the ideas expressed here are a fleshing out of our discussions during the class visit to Highgate Cemetery.