Freebo@ND and library catalogues

Posted on August 19, 2017 in Freebo@ND by Eric Lease Morgan

Freebo@ND is a collection of early English book-like materials as well as a set of services provided against them. In order to use & understand items in the collection, some sort of finding tool — such as a catalogue — is all but required. Freebo@ND supports the more modern full text index which has become the current best practice finding tool, but Freebo@ND also offers a set of much more traditional library tools. This blog posting describes how & why the use of these more traditional tools can be beneficial to the reader/researcher. In the end, we will learn that “What is old is new again.”

An abbreviated history

lemons by ericA long time ago, in a galaxy far far away, library catalogues were simply accession lists. As new items were brought into the collection, new entries were appended to the list. Each item would then be given an identifier, and the item would be put into storage. It could then be very easily located. Search/browse the list, identify item(s) of interest, note identifier(s), retrieve item(s), and done.

As collections grew, the simple accession list proved to be not scalable because it was increasingly difficult to browse the growing list. Thus indexes were periodically created. These indexes were essentially lists of authors, titles, or topics/subjects, and each item on the list was associated with a title and/or a location code. The use of the index was then very similar to the use of the accession list. Search/browse the index, identify item(s) of interest, note location code(s), retrieve item(s), and done. While these indexes were extremely functional, they were difficult to maintain. As new items became a part of the collection it was impossible to insert them into the middle of the printed index(es). Consequently, the printed indexes were rarely up-to-date.

To overcome the limitations of the printed index(es), someone decided not to manifest them as books, but rather as cabinets (drawers) of cards — the venerable card catalogue. Using this technology, it was trivial to add new items to the index. Type up cards describing items, and insert cards into the appropriate drawer(s). Readers could then search/browse the drawers, identify item(s) of interest, note location code(s), retrieve item(s), and done.

It should be noted that these cards were formally… formatted. Specifically, they included “cross-references” enabling the reader to literally “hyperlink” around the card catalogue to find & identify additional items of interest. On the downside, these cross-references (and therefore the hyperlinks) where limited by design to three to five in number. If more than three to five cross-references were included, then the massive numbers of cards generated would quickly out pace the space allotted to the cabinets. After all, these cabinets came dominate (and stereotype) libraries and librarianship. They occupied hundreds, if not thousands, of square feet, and whole departments of people (cataloguers) were employed to keep them maintained.

With the advent of computers, the catalogue cards became digitally manifested. Initially the digital manifestations were used to transmit bibliographic data from the Library of Congress to libraries who would print cards from the data. Eventually, the digital manifestations where used to create digital indexes, which eventually became the online catalogues of today. Thus, the discovery process continues. Search/browse the online catalogue. Identify items of interest. Note location code(s). Retrieve item(s). Done. But, for the most part, these catalogues do not meet reader expectations because the content of the indexes is merely bibliographic metadata (authors, titles, subjects, etc.) when advances in full text indexing have proven to be more effective. Alas, libraries simply do not have the full text of the books in their collections, and consequently libraries are not able to provide full text indexing services. †

What is old is new again

flowersThe catalogues representing the content of Freebo@ND are perfect examples of the history of catalogues as outlined above.

For all intents & purposes, Freebo@ND is YAVotSTC (“Yet Another Version of the Short-Title Catalogue”). In 1926 Pollard & Redgrave compiled an index of early English books entitled A Short-title Catalogue of books printed in England, Scotland, & Ireland and of English books printed abroad, 1475-1640. This catalogue became know as the “English short-title catalogue” or ESTC. [1] The catalog’s purpose is succinctly stated on page xi:

The aim of this catalogue is to give abridged entries of all ‘English’ books, printed before the close of the year 1640, copies of which exist at the British Museum, the Bodleian, the Cambridge University Library, and the Henry E. Huntington Library, California, supplemented by additions from nearly one hundres and fifty other collections.

The 600-page book is essentially an author index beginning with likes of George Abbot and ending with Ulrich Zwingli. Shakespeare begins on page 517, goes on for four pages, and includes STC (accession) numbers 22273 through 22366. And the catalogue functions very much like the catalogues of old. Articulate an author of interest. Look up the author in the index. Browse the listings found there. Note the abbreviation of libraries holding an item of interest. Visit library, and ultimately, look at the book.

The STC has a history and relatives, some of which is documented in a book entitled The English Short-Title Catalogue: Past, present, future and dating from 1998. [2] I was interested in two of the newer relatives of the Catalogue:

  1. English short title catalogue on CD-ROM 1473-1800 – This is an IBM DOS-based package supposably enabling the researcher/scholar to search & browse the Catalogue’s bibliographic data, but I was unable to give the package a test drive since I did not have ready access to DOS-based computer. [3] From the bibliographic description’s notes: “This catalogue on CD-ROM contains more than 25,000 of the total 36,000 records of titles in English in the British Library for the period 1473-1640. It also includes 105,000 records for the period 1641-1700, together with the most recent version of the ESTC file, approximately 312,000 records.”
  2. English Short Title Catalogue [as a website] – After collecting & indexing the “digital manifestations” describing items in the Catalogue, a Web-accessible version of the catalogue is available from the British Library. [4] From the about page: “The ‘English Short Title Catalogue’ (ESTC) began as the ‘Eighteenth Century Short Title Catalogue’, with a conference jointly sponsored by the American Society for Eighteenth-Century Studies and the British Library, held in London in June 1976. The aim of the original project was to create a machine-readable union catalogue of books, pamphlets and other ephemeral material printed in English-speaking countries from 1701 to 1800.” [5]

As outlined above, Freebo@ND is a collection of early English book-like materials as well as a set of services provided against them. The source data originates from the Text Creation Partnership, and it is manifested as a set of TEI/XML files with full/rich metadata as well as the mark up of every single word in every single document. To date, there are only 15,000 items in Freebo@ND, but when the project is complete, Freebo@ND ought to contain close to 60,000 items dating from 1460 to 1699. Given this data, Freebo@ND sports an online, full text index of the works collected to date. This online interface is both field searchable, free text searchable, and provides a facet browse interace. [6]

market by ericBut wait! There’s more!! (And this is the point.) Because the complete bibliographic data is available from the original data, it has been possible to create printed catalogs/indexes akin to the catalogs/indexes of old. These catalogs/indexes are available for downloading, and they include:

  • main catalog – a list of everything ordered by “accession” number; use this file in conjunction with your software’s find function to search & browse the collection [7]
  • author index – a list of all the authors in the collection & pointers to their locations in the repository; use this to learn who wrote what & how often [8]
  • title index – a list of all the works in the collection ordered by title; this file is good for “known item searches” [9]
  • date index – like the author index, this file lists all the years of item publication and pointers to where those items can be found; use this to see what was published when [10]
  • subject index – a list of all the Library Of Congress subject headings used in the collection, and their associated items; use this file to learn the “aboutness” of the collection as a whole [11]

These catalogs/indexes are very useful. It is really easy to load these them into your favorite text editor and to peruse them for items of interest. They are even more useful if they are printed! Using these catalogues/indexes it is very quick & easy to see how prolific any author was, how many items were published a given year, and what the published items were about. The library profession’s current tools do not really support such functions. Moreover, and unlike the cool (“kewl”) online interfaces alluded to above, these printed catalogs are easily updated, duplicated, shareable, and if bound can stand the test of time. Let’s see any online catalog last more than a decade and be so inexpensively produced.

“What is old is new again.”

Notes/links

† Actually, even if libraries where to have the full text of their collection readily available, the venerable library catalogues would probably not be able to use the extra content. This is because the digital manifestations of the bibliographic data can not be more than 100,000 characters long, and the existing online systems are not designed for full text indexing. To say the least, the inclusion of full text indexing in library catalogues would be revolutionary in scope, and it would also be the beginning of the end of traditional library cataloguing as we know it.

[1] Short-title catalogue or ESTC – http://www.worldcat.org/oclc/846560579
[2] Past, present, future – http://www.worldcat.org/oclc/988727012
[3] STC on CD-ROM – http://www.worldcat.org/oclc/605215275
[4] ESTC as website – http://estc.bl.uk/
[5] ESTC about page – http://www.bl.uk/reshelp/findhelprestype/catblhold/estchistory/estchistory.html
[6] Freebo@ND search interface – http://cds.crc.nd.edu/cgi-bin/search.cgi
[7] main catalog – http://cds.crc.nd.edu/downloads/catalog-main.txt
[8] author index – http://cds.crc.nd.edu/downloads/catalog-author.txt
[9] title index – http://cds.crc.nd.edu/downloads/catalog-title.txt
[10] date index – http://cds.crc.nd.edu/downloads/catalog-date.txt
[11] subject index – http://cds.crc.nd.edu/downloads/catalog-subject.txt

Stories: Interesting projects I worked on this past year

Posted on August 9, 2017 in Uncategorized by Eric Lease Morgan

This is short list of “stories” outlining some of the more interesting projects I worked on this past year:

  • Ask Putin – A faculty member from the College of Arts & Letters acquired the 950-page Cyrillic transcript of a television show called “Ask Putin”. The faculty member had marked up the transcription by hand in order to analyze the themes conveyed therein. They then visited the Center for Digital Scholarship, and we implemented a database version of the corpus. By counting & tabulating the roots of each of the words for each of the sixteen years of the show, we were able to quickly & easily confirm many of the observations she had generated by hand. Moreover, the faculty member was able to explore additional themes which they had not previously coded.
  • Who’s related to whom – A visiting scholar from the Kroc Center asked the Center for Digital Scholarship to extract all of the “named entities” (names, places, & things) from a set of Spanish language newspaper articles. Based on strength of the relationships between the entities, the scholar wanted a visualization to be created illustrating who was related to whom in the corpus. When we asked more about the articles and their content, we learned we had been asked to map the Columbian drug cartel. While incomplete, the framework of this effort will possibly be used by a South American government.
  • Counting 250,000,000 words – Working with Northwestern University, and Washington University in St. Louis, the Center for Digital Scholarship is improving access & services against the set of literature called “Early English Books”. This corpus spans 1460 and 1699 and is very representative of English literature of that time. We have been creating more accurate transcriptions of the texts, digitizing original items, and implementing ways to do “scalable reading” against the whole. After all, it is difficult to read 60,000 books. Through this process each & every word from the transcriptions has been saved in a database for future analysis. To date the database includes a quarter of a billion (250,000,000) rows. See: http://cds.crc.nd.edu
  • Convocate – In conjunction with the Center for Civil and Human Rights, the Hesburgh Libraries created an online tool for comparing & contrasting human rights policy written by the Vatican and various non-governmental agencies. As a part of this project, the Center for Digital Scholarship wrote an application that read each & every paragraph from the thousands of pages of text. The application then classified each & every paragraph with one or more keyword terms for the purposes of more accurate & thorough discovery across the corpus. The results of this application enable the researcher to items of similar interest even if they employ sets of dispersed terminology. For more detail, see: https://convocate.nd.edu

Freebo@ND

Posted on July 24, 2017 in Freebo@ND by Eric Lease Morgan

This is the initial blog posting introducing a fledgling website called Freebo@ND — a collection of early English print materials and services provided against them. [1]

For the past year a number of us here in the Hesburgh Libraries at the University of Notre Dame have been working on a grant-sponsored project with others from Northwestern University and Washington University in St. Louis. Collectively, we have been calling our efforts the Early English Print Project, and our goal is to improve on the good work done by the Text Creation Partnership (TCP). [2]

“What is the TCP?” Briefly stated, the TCP is/was an organization set out to make freely available the content of Early English Books Online (EBBO). The desire is/was to create & distribute thoroughly & accurately marked up (TEI) transcriptions of early English books printed between 1460 and 1699. Over time the scope of the TCP project seemed to wax & wane, and I’m still not really sure how many texts are in scope nor where they can all be found. But I do know the texts are being distributed in two phases. Phase I texts are freely available to anybody. [3] Phase II texts are only available to institutions who sponsored the Partnership, but they too will be freely available to everybody in a few years.

Our goals — the goals of the Early English Print Project — are to:

  1. improve the accuracy (reduce the number of “dot” words) in the TCP transcriptions
  2. associate page images (scans/facsimiles) with the TCP transcriptions
  3. provide useful services against the transcriptions for the purposes of distant reading

While I have had my hand in the first two tasks, much of my time has been spent on the third. To this end I have been engineering ways to collect, organize, archive, disseminate, and evaluate our Project’s output. To date, the local collection includes approximately 15,000 transcriptions and 60,000,000 words. When the whole thing is said & done, they tell me I will have close to 60,000 transcriptions and 2,000,000,000 words. Consequently, this is by far the biggest collection I’ve ever curated.

My desire is to make sure Freebo@ND goes beyond “find & get” and towards “use & understanding”. [4] My goal is to provide services against the texts, not just the texts themselves. Locally collecting & archiving the original transcriptions has been relatively trivial. [5] After extracting the bibliographic data from each transcription, and after transforming the transcriptions into plain text, implementing full text searching has been easy. [6] Search even comes with faceted browse. To support “use & understanding” I’m beginning to provide services against the texts. For example, it is possible to download — in a computer-readable format — all the words from a given text, where each word from each text is characterized by its part-of-speech, lemma, given form, normalized form, and position in the text. Using this output, it is more than possible for students or researchers to compare & contrast the use of words & types of words across texts. Because the texts are described in both bibliographic as well as numeric terms, it is possible to sort search results by date, page length, or word count. [7] Additional numeric characteristics are being implemented. The use of “log-likelihood ratios” is a simple and effective way to compare the use of words in a given text with an entire corpus. Such has been implemented in Freebo@ND using a set of words called the “great ideas”. [8] There is also a way to create one’s own sub-collection for analysis, but the functionality is meager. [9]

I have had to learn a lot to get this far, and I have had to use a myriad of technologies. Some of these things include: getting along sans a fully normalized database, parallel processing & cluster computing, “map & reduce”, responsive Web page design, etc. This being the initial blog posting documenting the why’s & wherefore’s of Freebo@ND, more postings ought to be coming; I hope to document here more thoroughly my part in our Project. Thank you for listening.

Links

[1] Freebo@ND – http://cds.crc.nd.edu/

[2] Text Creation Partnership (TCP) – http://www.textcreationpartnership.org

[3] The Phase I TCP texts are “best” gotten from GitHub – https://github.com/textcreationpartnership

[4] use & understanding – http://infomotions.com/blog/2011/09/dpla/

[5] local collection & archive – http://cds.crc.nd.edu/freebo/

[6] search – http://cds.crc.nd.edu/cgi-bin/search.cgi

[7] tabled search results – http://cds.crc.nd.edu/cgi-bin/did2catalog.cgi

[8] log-likelihood ratios – http://cds.crc.nd.edu/cgi-bin/likelihood.cgi

[9] sub-collections – http://cds.crc.nd.edu/cgi-bin/request-collection.cgi

tei2json: Summarizing the structure of Early English poetry and prose

Posted on January 17, 2017 in Uncategorized by Eric Lease Morgan

This posting describes a hack of mine, tei2json.pl – a Perl program to summarize the structure of Early English poetry and prose. [0]

In collaboration with Northwestern University and Washington University, the University of Notre Dame is working on a project whose primary purpose is to correct (“annotate”) the Early English corpus created by the Text Creation Partnership (TCP). My role in the project is to do interesting things with the corpus once it has been corrected. One of those things is the creation of metdata files denoting the structure of each item in the corpus.

Some of my work is really an effort to reverse engineer good work done by the late Sebastian Rahtz. For example, Mr. Rahtz cached a version of the TCP corpus, transformed each item into a number of different formats, and put the whole thing on GitHub. [1] As a part of this project, he created metadata files enumerating what TEI elements were in each file and what attributes were associated with each element. The result was an HTML display allowing the reader to quickly see how many bibliographies an item may have, what languages may be present, how long the document was measured in page breaks, etc. One of my goals is/was to do something very similar.

The workings of the script are really very simple: 1) configure and denote what elements to count & tabulate, 2) loop through each configuration, 3) keep a running total of the result, 4) convert the result to JSON (a specific data format), and 5) save the result to a file. Here are (temporary) links to a few examples:

JSON files are not really very useful in & of themselves; JSON files are designed to be transport mechanisms allowing other applications to read and process them. This is exactly what I did. In fact, I created two different applications: 1) json2table.pl and 2) json2tsv.pl. [2, 3] The former script takes a JSON file and creates a HTML file whose appearance is very similar to Rahtz’s. Using the JSON files (above) the following HTML files have been created through the use of json2table.pl:

The second script (json2tsv.pl) allows the reader to compare & contrast structural elements between items. Json2tsv.pl reads many JSON files and outputs a matrix of values. This matrix is a delimited file suitable for analysis in spreadsheets, database applications, statistical analysis tools (such as R or SPSS), or programming languages libraries (such as Python’s numpy or Perl’s PDL). In its present configuration, the json2tsv.pl outputs a matrix looking like this:

id      bibl  figure  l     lg   note  p    q
A00002  3     4       4118  490  8     18   3
A00011  3     0       2     0    47    68   6
A00089  0     0       0     0    0     65   0
A00214  0     0       0     0    151   131  0
A00289  0     0       0     0    41    286  0
A00293  0     1       189   38   0     2    0
A00395  2     0       0     0    0     160  2
A00749  0     4       120   18   0     0    2
A00926  0     0       124   12   0     31   7
A00959  0     0       2633  9    0     4    0
A00966  0     0       2656  0    0     17   0
A00967  0     0       2450  0    0     3    0

Given such a file, the reader could then ask & answer questions such as:

  • Which item has the greatest number of figures?
  • What is average number of lines per line group?
  • Is there a statistical correlation between paragraphs and quotes?

Additional examples of input & output files are temporarily available online. [4]

My next steps include at least a couple of things. One, I need/want to evaluate whether or not save my counts & tabulations in a database before (or after) creating the JSON files. The data may be prove to be useful there. Two, as a librarian, I want to go beyond qualitative description of narrative texts, and the counting & tabulating of structural elements moves in that direction, but it does not really address the “aboutness”, “meaning”, nor “allusions” found in a corpus. Sure, librarians have applied controlled vocabularies and bits of genre to metadata descriptions, but such things are not quantitive and consequently allude statistical analysis. For example, using sentiment analysis one could measure and calculate the “lovingness”, “war mongering”, “artisticness”, or “philosophic nature” of the texts. One could count & tabulate the number of times family-related terms are used, assign the result a score, and record the score. One could then amass all documents and sort them by how much they discussed family, love, philosophy, etc. Such is on my mind, and more than half-way baked. Wish me luck.

Links

Synonymizer: Using Wordnet to create a synonym file for Solr

Posted on January 16, 2017 in Uncategorized by Eric Lease Morgan

This posting describes a little hack of mine, Synonymizer — a Python-based CGI script to create a synonym files suitable for use with Solr and other applications. [0]

Human language is ambiguous, and computers are rather stupid. Consequently computers often need to be explicitly told what to do (and how to do it). Solr is a good example. I might tell Solr to find all documents about dogs, and it will dutifully go off and look for things containing d-o-g-s. Solr might think it is smart by looking for d-o-g as well, but such is a heuristic, not necessarily a real understanding of the problem at hand. I might say, “Find all documents about dogs”, but I might really mean, “What is a dog, and can you give me some examples?” In which case, it might be better for Solr to search for documents containing d-o-g, h-o-u-n-d, w-o-l-f, c-a-n-i-n-e, etc.

This is where Solr synonym files come in handy. There are one or two flavors of Solr synonym files, and the one created by my Synonymizer is a simple line-delimited list of concepts, and each line is a comma-separated list of words or phrases. For example, the following is a simple Solr synonym file denoting four concepts (beauty, honor, love, and truth):

  beauty, appearance, attractiveness, beaut
  honor, abide by, accept, celebrate, celebrity
  love, adoration, adore, agape, agape love, amorousness
  truth, accuracy, actuality, exactitude

Creating a Solr synonym file is not really difficult, but it can be tedious, and the human brain is not always very good at multiplying ideas. This is where computers come in. Computers do tedium very well. And with the help of a thesaurus (like WordNet), multiplying ideas is easier.

Here is how Synonymizer works. First it reads a configured database of previously generated synonyms.† In the beginning, this file is empty but must be readable and writable by the HTTP server. Second, Synonymizer reads the database and offers the reader to: 1) create a new set of synonyms, 2) edit an existing synonym, or 3) generate a synonym file. If Option #1 is chosen, then input is garnered, and looked up in WordNet. The script will then enable the reader to disambiguate the input through the selection of apropos definitions. Upon selection, both WordNet hyponyms and hypernyms will be returned. The reader then has the opportunity to select desired words/phrase as well as enter any of their own design. The result is saved to the database. The process is similar if the reader chooses Option #2. If Option #3 is chosen, then the database is read, reformatted, and output to the screen as a stream of text to be used on Solr or something else that may require similar functionality. Because Option #3 is generated with a single URL, it is possible to programmatically incorporate the synonyms into your Solr indexing process pipeline.

The Synonymizer is not perfect.‡ For example, it only creates one of the two different types of Solr synonym files. Second, while Solr can use the generated synonym file, search results implement phrase searches poorly, and this is well-know issue. [1] Third, editing existing synonyms does not really take advantage of previously selected items; data-entry is tedious but not as tedious as writing the synonym file by hand. Forth, the script is not fast, and I blame this on Python and WordNet.

Below are a couple of screenshots from the application. Use and enjoy.

Synonymizer home

Synonymizer output

[0] synonymizer.py – http://dh.crc.nd.edu/sandbox/synonymizer/synonymizer.py

[1] “Why is Multi-term synonym mapping so hard in Solr?” – http://bit.ly/2iyYZw6

† The “database” is really simple delimited text file. No database management system required.

‡ Software is never done. If it were, then it would be called “hardware”.

Tiny road trip: An Americana travelogue

Posted on October 13, 2016 in Uncategorized by Eric Lease Morgan

This travelogue documents my experiences and what I learned on a tiny road trip including visits to Indiana University, Purdue University, University of Illinois / Urbana-Champagne, and Washington University In St. Louis between Monday, October 26 and Friday, October 30, 2017. In short, I learned four things: 1) of the places I visited, digital scholarship centers support a predictable set of services, 2) the University Of Notre Dame’s digital scholarship center is perfectly situated in the middle of the road when it comes to the services provided, 3) the Early Print Project is teamed with a set of enthusiastic & animated scholars, and 4) Illinois is very flat.

Lafayette Bloomington Greenwood Crawfordsville

Four months ago I returned from a pseudo-sabbatical of two academic semesters, and exactly one year ago I was in Tuscany (Italy) painting cornfields & rolling hills. Upon my return I felt a bit out of touch with some of my colleagues in other libraries. At the same time I had been given an opportunity to participate in a grant-sponsored activity (the Early English Print Project) between Northwestern University, Washington University In St. Louis, and the University Of Notre Dame. Since I was encouraged to visit the good folks at Washington University, I decided to stretch a two-day visit into a week-long road trip taking in stops at digital scholarship centers. Consequently, I spent bits of time in Bloomington (Indiana), West Lafayette (Indiana), Urbana (Illinois), as well as St. Louis (Missouri). The whole process afforded me the opportunity to learn more and get re-acquainted.

Indiana University / Bloomington

My first stop was in Bloomington where I visited Indiana University, and the first thing that struck me was how much Bloomington exemplified the typical college town. Coffee shops. Boutique clothing stores. Ethnic restaurants. And teaming with students ranging from fraternity & sorority types, hippie wanna be’s, nerds, wide-eyed freshman, young lovers, and yes, fledgling scholars. The energy was positively invigorating.

My first professional visit was with Angela Courtney (Head of Arts & Humanities, Head of Reference Services, Librarian for English & American Literature, and Director of the Scholars’ Commons). Ms. Courtney gave me a tour of the library’s newly renovated digital scholarship center. [1] It was about the same size at the Hesburgh Libraries’s Center, and it was equipped with much of the same apparatus. There was a scanning lab, plenty of larger & smaller meeting spaces, a video wall, and lots of open seating. One major difference between Indiana and Notre Dame was the “reference desk”. For all intents & purposes, the Indiana University reference desk is situated in the digital scholarship center. Ms. Courtney & I chatted for a long hour, and I learned how Indiana University & the University Of Notre Dame were similar & different. Numbers of students. Types of library collections & services. Digital initiatives. For the most part, both universities have more things in common than differences, but their digital initiatives were by far more mature than the ones here at Notre Dame.

Later in the afternoon I visited with Yu (Marie) Ma who works for the HathiTrust Research Center. [2] She was relatively new to the HathiTrust, and if I understand her position correctly, then she spends a lot of her time setting up technical workflows and the designing the infrastructure for large-scale text analysis. The hour with Marie was informative on both of our parts. For example, I outlined some of the usability issues with the Center’s interface(s), and she outlined how the “data capsules” work. More specifically, “data capsules” are virtual machines operating in two different modes. In one mode a researcher is enabled to fill up a file system with HathiTrust content. In the other mode, one is enabled to compute against the content and return results. In one or the other of the modes (I’m not sure which), Internet connectivity is turned off to disable the leaking of HathiTrust content. In this way, a HathiTrust data capsule operates much like a traditional special collections room. A person can go into the space, see the book, take notes with a paper & pencil, and then leave sans any of the original materials. “What is old is new again.” Along the way Marie showed me a website — Lapps Grid — which looks as if it functions similar to Voyant Tools and my fledgling EEBO-TCP Workset Browser. [3, 4, 5] Amass a collection. Use the collection as input against many natural language processing tools/applications. Use the output as a means for understanding. I will take a closer look at Lapps Grid.

Purdue University

The next morning I left the rolling hills of southern Indiana for the flatlands of central Indiana and Purdue University. There I facilitated a brown-bag lunch discussion on the topic of scalable reading, but the audience seemed more interested in the concept of digital scholarship centers. I described the Center here at Notre Dame, and did my best to compare & contrast it with others as well as draw into the discussion the definition of digital humanities. Afterwards I went to lunch with Micheal Witt and Amanda Visconti. Mr. Witt spends much of his time on institutional repostory efforts, specifically in regards to scientific data. Ms. Visconti works in the realm of the digital humanities and has recently made available her very interesting interactive dissertation — Infinite Ulysses. [6] After lunch Mr. Witt showed me a new library space scheduled to open before the Fall Semester of 2017. The space will be library-esque during the day, and study-esque during the evening. Through the process of construction, some of their collection needed to be weeded, and I found the weeding process to be very interesting.

University of Illinois / Urbana-Champagne

Up again in the morning and a drive to Urbana-Champagne. During this jaunt I became both a ninny and a slave to my computer’s (telephone’s) navigation and functionality. First it directed me to my location, but no parking places. After identifying a parking place on my map (computer), I was not able to get directions on how to get there. Once I finally found parking, I required my telephone to pay. Connect to remote site while located in concrete building. Create account. Supply credit card number. Etc. We are increasingly reliant (dependent) on these gizmos.

My first meeting was with Karen Hogenboom (Associate Professor of Library Administration, Scholarly Commons Librarian and Head, Scholarly Commons). We too discussed digital scholarship centers, and again, there were more things in common with our centers than differences. Her space was a bit smaller than Notre Dame’s, and their space was less about specific services and more about referrals to other services across the library and across the campus. For example, geographic information systems services and digitization services were offered elsewhere.

I then had a date with an old book, but first some back story. Here at Notre Dame Julia Schneider brought to my attention a work written by Erasmus and commenting on Cato which may be a part of a project called The Digital Schoolbook. She told me how there were only three copies of this particular book, and one of them was located in Urbana. Consequently, a long month ago, I found a reference to the book in the library catalog, and I made an appointment to see it in person. The book’s title is Erasmi Roterodami libellus de co[n]structio[n]e octo partiu[m]oratio[n]is ex Britannia nup[er] huc plat[us] : et ex eo pureri bonis in l[ite]ris optio and it was written/published in 1514. [7, 8] The book represented at least a few things: 1) the continued and on-going commentary on Cato, 2) an example of early book printing, and 3) forms of scholarship. Regarding Cato I was only able to read a single word in the entire volume — the word “Cato” — because the whole thing was written in Latin. As an early printed book, I had to page through the entire volume to find the book I wanted. It was the last one. Third, the book was riddled with annotations, made from a number of hands, and with very fine-pointed pens. Again, I could not read a single word, but a number of the annotations were literally drawings of hands pointing to sections of interest. Whoever said writing in books was a bad thing? In this case, the annotations were a definite part of the scholarship.

Manet lion art colors

Washington University In St. Louis

Yet again, I woke up the next morning and continued on my way. Along the road there were billboards touting “foot-high pies” and attractions to Indian burial grounds. There were corn fields being harvested, and many advertisements pointing to Abraham Lincoln stomping locations.

Late that afternoon I was invited to participate in a discussion with Doug Knox, Steve Pentecost, Steven Miles, and Dr. Miles’s graduate students. (Mr. Knox & Mr. Pentecost work in a university space called Arts & Sciences Computing.) They outlined and reported upon a digital project designed to aid researchers & scholars learn about stelae found along the West River Basin in China. I listened. (“Stelae” are markers, usually made of stone, commemorating the construction or re-construction of religious temples.) To implement the project, TEI/XML files were being written and “en masse” used akin to a database application. Reports were to be written agains the XML to create digital maps as well as browsable lists of names of people, names of temples, dates, etc. I got to thinking how timelines might also be apropos.

The bulk of the following day (Friday) was spent getting to know a balance of colleagues and discussing the Early English Print Project. There were many people in the room: Doug Knox & Steve Pentecost from the previous day, Joesph Loewenstein (Professor, Department of English, Director Of the Humanities Digital Workshop and the Interdisciplinary Project in the Humanities) Kate Needham, Andrew Rouner (Digital Library Director), Anupam Basu (Assistant Professor, Department of English), Shannon Davis (Digital Library Services Manager), Keegan Hughes, and myself.

More specifically, we talked about how sets of EEBO/TCP ([9]) TEI/XML files can be: 1) corrected, enhanced, & annotated through both automation as well as crowd-sourcing, 2) supplemented & combined with newly minted & copy-right free facsimiles from the original printed documents, 3) analyzed & reported upon through text mining & general natural language processing techniques, and 4) packaged up & redistributed back to the scholarly community. While the discussion did not follow logically, it did surround a number of unspoken questions, such as but not limited to:

  • Is METS a desirable re-distribution method? [10] What about some sort of database system instead?
  • To what degree is governance necessary in order for us to make decisions?
  • To what degree is it necessary to pour the entire corpus (more than 60,000 XML files with millions of nodes) into a single application for processing, and is the selected application up to the task?
  • What form or flavor of TEI would be used as the schema for the XML file output?
  • What role will an emerging standard called IIIF play in the process of re-distribution? [11]
  • When is a corrected text “good enough” for re-distribution?

To my mind, none of these questions were answered definitively, but then again, it was an academic discussion. On the other hand, we did walk away with a tangible deliverable — a whiteboard drawing illustrating a possible workflow going something like this:

  1. cache data from University of Michigan
  2. correct/annotate the data
  3. when data is “good enough”, put the data back into the cache
  4. feed the data back to the University of Michigan
  5. when data is “good enough”, text mine the data and put the result to back into the cache
  6. feed the data back to the University of Michigan
  7. create new facsimiles from the printed works
  8. combine the facsimiles with the data, and put the result to back into the cache
  9. feed the data back to the University of Michigan
  10. repeat

model

After driving through the country side, and after two weeks of reflection, I advocate a slightly different workflow:

  1. cache TEI data from GitHub repository, which was originally derived from the University of Michigan [12]
  2. make cache accessible to the scholarly community through a simple HTTP server and sans any intermediary application
  3. correct/annotate the data
  4. as corrected data becomes available, replace files in cache with corrected versions
  5. create copyright-free facsimiles of the originals, combine them with corrected TEI in the form of METS files, and cache the result
  6. use the METS files to generate IIIF manifests, and make the facsimiles viewable via the IIIF protocol
  7. as corrected files become available, use text mining & natural language processing to do analysis, combine the results with the original TEI (and/or facsimiles) in the form of METS files, and cache the result
  8. use the TEI and METS files to create simple & rudimentary catalogs of the collection (author lists, title lists, subject/keyword lists, date lists, etc.), making it easier for scholars to find and download items of interest
  9. repeat

The primary point I’d like to make in regard to this workflow is, “The re-distribution of our efforts ought to take place over simple HTTP and in the form of standardized XML, and I do not advocate the use of any sort of middle-ware application for these purposes.” Yes, of course, middle-ware will be used to correct the TEI, create “digital combos” of TEI and images, and do textual analysis, but the output of these processes ought to be files accessible via plain o’ ordinary HTTP. Applications (database systems, operating systems, content-management systems, etc.) require maintenance, and maintenance is done by a few & specialized number of people. Applications are often times “black boxes” understood and operated by a minority. Such things are very fragile, especially compared to stand-alone files. Standardized (XML) files served over HTTP are easily harvestable by anybody. They are easily duplicated. They can be saved on platform-independent media such as CD’s/DVD’s, magnetic tape, or even (gasp) paper. Once the results of our efforts are output as files, then supplementary distribution mechanisms can be put into place, such as IIIF or middleware database applications. XML files (TEI and/or METS) served over simple HTTP ought be the primary distribution mechanism. Such is transparent, sustainable, and system-independent.

Over lunch we discussed Spenser’s Faerie Queene, the Washington University’s Humanities Digital Workshop, and the salient characteristics of digital humanities work. [13] In the afternoon I visited the St. Louis Art Museum, whose collection was rich. [14] The next day, on my way home through Illinois, I stopped at the tomb of Abraham Lincoln in order to pay my respects.

Lincoln University Matisse Arch

In conclusion

In conclusion, I learned a lot, and I believe my Americana road trip was a success. My conception and defintion of digital scholarship centers was re-enforced. My professional network was strengthened. I worked collaboratively with colleagues striving towards a shared goal. And my personal self was enriched. I advocate such road trips for anybody and everybody.

Links

[1] digital scholarship at Indiana University – https://libraries.indiana.edu/services/digital-scholarship
[2] HathiTrust Research Center – https://analytics.hathitrust.org
[3] Lapps Grid – http://www.lappsgrid.org
[4] Voyant Tools – http://voyant-tools.org
[5] EEBO-TCP Workset Browser – http://blogs.nd.edu/emorgan/2015/06/eebo-browser/
[6] Infinite Ulysses – http://www.infiniteulysses.com
[7] old book from the UIUC catalog – https://vufind.carli.illinois.edu/vf-uiu/Record/uiu_5502849
[8] old book from the Universal Short Title Catalogue – http://ustc.ac.uk/index.php/record/403362
[9] EEBO/TCP – http://www.textcreationpartnership.org/tcp-eebo/
[10] METS – http://www.loc.gov/standards/mets/
[11] IIIF – http://iiif.io
[12] GitHub repository of texts – https://github.com/textcreationpartnership/Texts
[13] Humanities Digital Workshop – https://hdw.artsci.wustl.edu
[14] St. Louis Art Museum – http://www.slam.org

Blueprint for a system surrounding Catholic social thought & human rights

Posted on August 30, 2016 in Uncategorized by Eric Lease Morgan

This posting elaborates upon one possible blueprint for comparing & contrasting various positions in the realm of Catholic social thought and human rights.

We here in the Center For Digital Scholarship have been presented with a corpus of documents which can be broadly described as position papers on Catholic social thought and human rights. Some of these documents come from the Vatican, and some of these documents come from various governmental agencies. There is a desire by researchers & scholars to compare & contrast these documents on the paragraph level. The blueprint presented below illustrates one way — a system/flowchart — this desire may be addressed:

blueprint

The following list enumerates the flow of the system:

  1. Corpus creation – The system begins on the right with sets of documents from the Vatican as well as the various governmental agencies. The system also begins with a hierarchal “controlled vocabulary” outlined by researchers & scholars in the field and designed to denote the “aboutness” of individual paragraphs in the corpus.
  2. Manual classification – Reading from left to right, the blueprint next illustrates how subsets of document paragraphs will be manually assigned to one more more controlled vocabulary terms. This work will be done by people familiar with the subject area as well as the documents themselves. Success in this regard is directly proportional to the volume & accuracy of the classified documents. At the very least, a few hundred paragraphs need to be consistently classified from each of the controlled vocabulary terms in order for the next step to be successful.
  3. Computer “training” – Because the number of paragraphs from the corpus is too large for manual classification, a process known as “machine learning” will be employed to “train” a computer program to do the work automatically. If it is assumed the paragraphs from Step #2 have been classified consistently, then it can also be assumed that the each set of similarly classified documents will have identifiable characteristics. For example, documents classified with the term “business” may often include the word “money”. Documents classified as “government” may often include “law”, and documents classified as “family” may often include the words “mother”, “father”, or “children”. By counting & tabulating the existence & frequency of individual words (or phrases) in each of the sets of manually classified documents, it is possible to create computer “models” representing each set. The models will statistically describe the probabilities of the existence & frequency of words in a given classification. Thus, the output of this step will be two representations, one for the Vatican documents and another for the governmental documents.
  4. Automated classification – Using the full text of the given corpus as well as the output of Step #3, a computer program will then be used to assign one or more controlled vocabulary terms to each paragraph in the corpus. In other words, the corpus will be divided into individual paragraphs, each paragraph will be compared to a model and assigned one more more classification terms, and the paragraph/term combinations will be passed on to a database for storage and ultimately an indexer to support search.
  5. Indexing – A database will store each paragraph from the corpus along side metadata describing the paragraph. This meta will include titles, authors, dates, publishers, as well as the controlled vocabulary terms. An indexer (a sort of database specifically designed for the purposes of search) will make the content of the database searchable, but the index will also be supplemented with a thesaurus. Because human language is ambiguous, words often have many and subtle differences in meaning. For example, when talking about “dogs”, a person may also be alluding to “hounds”, “canines”, or even “beagles”. Given the set of controlled vocabulary terms, a thesaurus will be created so when researchers & scholars search for “children” the indexer may also return documents containing the phrase “sons & daughters of parents”, or another example, when a search is done for “war” documents (paragraphs) also containing the words “battle” or “insurgent” may be found.
  6. Searching & browsing – Finally, a Web-based interface will be created enabling readers to find items of interest, compare & contrast these items, identify patterns & anomalies between these items, and ultimately make judgments of understanding. For example, the reader will be presented with a graphical representation of controlled vocabulary. By selecting terms from the vocabulary, the index will be queried, and the reader will be presented with sortable and groupable lists of paragraphs classified with the given term. (This process is called “browsing”.) Alternatively, researchers & scholars will be able to enter simple (or complex) queries into an online form, the queries will be applied to the indexer, and again, paragraphs matching the queries will be returned. (This process is called “searching”.) Either way, the researchers & scholars will be empowered to explore the corpus in many and varied ways, and none of these ways will be limited to any individuals’ specific topic of interest.

The text above only outlines one possible “blueprint” for comparing & contrasting a corpus of Catholic social thought and human rights. Moreover, there are at least two other ways of addressing the issue. For example, it it entirely possible to “simply” read each & every document. After all, that is they way things have been done for millennium. Another possible solution is to apply natural language processing techniques to the corpus as a whole. For example, one could automatically count & tabulate the most frequently used words & phrases to identify themes. One could compare the rise & fall of these themes over time, geographic location, author, or publisher. The same thing can be done in a more refined way using parts-of-speech analysis. Along these same lines there are well-understood relevancy ranking algorithms (such as term frequency / inverse frequency) allowing a computer to output the more statistically significant themes. Finally, documents could be compared & contrasted automatically through a sort of geometric analysis in an abstract and multi-dimensional “space”. These additional techniques are considerations for a phase two of the project, if it ever comes to pass.

How not to work during a sabbatical

Posted on July 19, 2016 in Uncategorized by Eric Lease Morgan

This presentation — given at Code4Lib Midwest (Chicago, July 14, 2016) — outlines the various software systems I wrote during my recent tenure as an adjunct faculty member at the University of Notre Dame. (This presentation is also available as a one-page PDF handout designed to be duplex printed and folded in half as if it were a booklet.)

  • viewHow rare is rare? – In an effort to determine the “rarity” of items in the Catholic Portal, I programmatically searched WorldCat for specific items, counted the number of times it was held by libraries in the United States, and recorded the list of the holding libraries. Through the process I learned that most of the items in the Catholic Portal are “rare”, but I also learned that “rarity” can be defined as the triangulation of scarcity, demand, and value. Thus the “rare” things may not be rare at all.
  • Image processing – By exploiting the features and functions of an open source library called OpenCV, I started exploring ways to evaluate images in the same way I have been evaluating texts. By counting & tabulating the pixels in an image it is possible to create ratios of colors, do facial recognition, or analyze geometric composition. Through these processes is may be possible to supplement art history and criticism. For example, one might be able to ask things like, “Show me all of the paintings from Picasso’s Rose Period.”
  • Library Of Congress Name Authorities – Given about 125,000 MARC authority records, I wrote an application that searched the Library Of Congress (LOC) Name Authority File, and updated the local authority records with LOC identifiers, thus making the local authority database more consistent. For items that needed disambiguation, I created a large set of simple button-based forms allowing librarians to choose the most correct name.
  • MARC record enrichment – Given about 500,000 MARC records describing ebooks, I wrote a program that found the richest OCLC record in WorldCat and then merged the found record with the local record. Ultimately the local records included more access points and thus proved to be more useful in a library catalog setting.
  • OAI-PMH processing – I finally got my brain around the process of harvesting & indexing OAI-PMH content into VUFind. Whoever wrote the original OAI-PMH applications for VUFind did a very good job, but there is a definite workflow to the process. Now that I understand the workflow it is relatively easy ingest metadata from things like ContentDM, but issues with the way Dublin Core is implement still make the process challenging.
  • EEBO/TCP – Given the most beautiful TEI mark-up I’ve ever seen, I have systematically harvested the Early English Books Online (EEBO) content from the Text Encoding Initiative (TCP) and done some broad & deep but also generic text analysis subsets of the collection. Readers are able to search the collection for items of interest, save the full text to their own space for analysis, and have a number of rudimentary reports done against the result. This process allows the reader to see the corpus from a “distance”. Very similar work has been done against subsets of content from JSTOR as well as the HathiTrust.
  • VIAF Lookup – Given about 100,000 MARC authority records, I wrote a program to search VIAF for the most appropriate identifier and associate it with the given record. Through the process I learned two things: 1) how to exploit the VIAF API, and 2) how to exploit the Levenshtein algorithm. Using the later I was able to make automated and “intelligent” choices when it came to name disambiguation. In the end, I was able to accurately associate more than 80% of the authority names with VIAF identifiers.

My tenure as an adjunct faculty member was very much akin to a one year education except for a fifty-five year old. I did many of the things college students do: go to class, attend sporting events, go on road trips, make friends, go to parties, go home for the holidays, write papers, give oral presentations, eat too much, drink too much, etc. Besides the software systems outlined above, I gave four or five professional presentations, attend & helped coordinate five or six professional meetings, taught an online, semester-long, graduate-level class of on the topic of XML, took many different classes (painting, sketching, dance, & language) many times, lived many months in Chicago, Philadelphia, and Rome, visited more than two dozen European cities, painted about fifty paintings, bound & filled about two dozen hand-made books, and took about three thousand photographs. The only thing I didn’t do is take tests.

JSTOR Workset Browser

Posted on June 30, 2015 in Uncategorized by Eric Lease Morgan

Given a citations.xml file, this suite of software — the JSTOR Workset Browser — will cache and index content identified through JSTOR’s Data For Research service. The resulting (and fledgling) reports created by this suite enables the reader to “read distantly” against a collection of journal articles.

The suite requires a hodgepodge of software: Perl, Python, and the Bash Shell. Your milage may vary. Sample usage: cat etc/citations-thoreau.xml | bin/make-everything.sh thoreau

“Release early. Release often”.

Early English love was black & white

Posted on June 15, 2015 in Uncategorized by Eric Lease Morgan

Apparently, when it comes to the idea of love during the Early English period, everything is black & white.

Have harvested the totality of the EEBO-TCP (Early English Books Online – Text Creation Partnership) corpus. Using an extraordinarily simple (but very effective) locally developed indexing system, I extracted all the EEBO-TCP identifiers whose content was cataloged with the word love. I then fed these identifiers to a suite of software which: 1) caches the EEBO-TCP TEI files locally, 2) indexes them, 3) creates a browsable catalog of them, 4) supports a simle full text search engine against them, and 5) reports on the whole business (below). Through this process I have employed three sets of “themes” akin to the opposite of stop (function) words. Instead of specifically eliminating these words from the analysis, I specifically do analysis based on these words. One theme is “big” names. Another theme is “great” ideas. The third them is colors: white, black, red, yellow, blue, etc. Based on the ratio of each item’s number of words compared the number of times specific color words appear, I can generate a word cloud of colors (or colours) words, and you can “see” that in terms of love, everything is black & white. Moreover, the “most colorful” item is entitled The whole work of love, or, A new poem, on a young lady, who is violently in love with a gentleman of Lincolns-Inn by a student in the said art. — a charming, one-page document whose first two lines are:

LOVE is a thing that’s not on Reaſon laid,
But upon Nature and her Dictates made.

The corpus of the EEBO-TCP is some of the cleanest data I’ve ever seen. The XML is not only well-formed, but conforms the TEI schema. The metadata is thorough, (almost) 100% complete, (usually) consistently applied. It comes with very effective stylesheets, and the content is made freely easily available in a number of places. It has been a real joy to work with!

General statistics

An analysis of the corpus’s metadata provides an overview of what and how many things it contains, when things were published, and the sizes of its items:

  • Number of items – 156
  • Publication date range – 1493 to 9999 (histogram : boxplot)
  • Sizes in pages – 1 to 606 (histogram : boxplot)
  • Total number of pages – 12332
  • Average number of pages per item – 79

Possible correlations between numeric characteristics of records in the catalog can be illustrated through a matrix of scatter plots. As you would expect, there is almost always a correlation between pages and number of words. Are others exist? For more detail, browse the catalog.

Notes on word usage

By counting and tabulating the words in each item of the corpus, it is possible to measure additional characteristics:

Perusing the list of all words in the corpus (and their frequencies) as well as all unique words can prove to be quite insightful. Are there one or more words in these lists connoting an idea of interest to you, and if so, then to what degree do these words occur in the corpus?

To begin to see how words of your choosing occur in specific items, search the collection.

Through the creation of locally defined “dictionaries” or “lexicons”, it is possible to count and tabulate how specific sets of words are used across a corpus. This particular corpus employs three such dictionaries — sets of: 1) “big” names, 2) “great” ideas, and 3) colors. Their frequencies are listed below:

The distribution of words (histograms and boxplots) and the frequency of words (wordclouds), and how these frequencies “cluster” together can be illustrated:

Items of interest

Based on the information above, the following items (and their associated links) are of possible interest:

  • Shortest item (1 p.) – Now she that I louyd trewly beryth a full fayre face hath chosen her … (TEI : HTML : plain text)
  • Longest item (606 p.) – Psyche, or, Loves mysterie in XX canto’s, displaying the intercourse betwixt Christ and the soule / by Joseph Beaumont … (TEI : HTML : plain text)
  • Oldest item (1493) – This tretyse is of loue and spekyth of iiij of the most specyall louys that ben in the worlde and shewyth veryly and perfitely bi gret resons and causis, how the meruelous [and] bounteuous loue that our lord Ihesu cryste had to mannys soule excedyth to ferre alle other loues … Whiche tretyse was translatid out of frenshe into englyshe, the yere of our lord M cccc lxxxxiij, by a persone that is vnperfight insuche werke … (TEI : HTML : plain text)
  • Most recent (9999) – Ovid’s Art of love; in three books: : together with his Remedy of love: / translated into English verse, by several eminent hands: ; to which are added, The court of love, The history of love, and Armstrong’s Oeconomy of love. (TEI : HTML : plain text)
  • Most thoughtful item – A sermon directing what we are to do, after strict enquiry whether or no we truly love God preached April 29, 1688. (TEI : HTML : plain text)
  • Least thoughtful item – Amoris effigies, sive, Quid sit amor? efflagitanti responsum (TEI : HTML : plain text)
  • Biggest name dropper – Wit for money, or, Poet Stutter a dialogue between Smith, Johnson, and Poet Stutter : containing reflections on some late plays and particularly, on Love for money, or, The boarding school. (TEI : HTML : plain text)
  • Fewest quotations – Mount Ebal, or A heavenly treatise of divine love Shewing the equity and necessity of his being accursed that loves not the Lord Iesus Christ. Together with the motives meanes markes of our love towards him. By that late faithfull and worthy divine, John Preston, Doctor in Divinitie, chaplaine in ordinary to his Majestie, master of Emmanuel Colledge in Cambridge, and sometimes preacher of Lincolnes Inne. (TEI : HTML : plain text)
  • Most colorful – The whole work of love, or, A new poem, on a young lady, who is violently in love with a gentleman of Lincolns-Inn by a student in the said art. (TEI : HTML : plain text)
  • Ugliest – Eubulus, or A dialogue, where-in a rugged Romish rhyme, (inscrybed, Catholicke questions, to the Protestaut [sic]) is confuted, and the questions there-of answered. By P.A. (TEI : HTML : plain text)