Tag Archives: @kellyblanchat

Tandem Week 13 Update

WEEK 13 TANDEM PROJECT UPDATE:

We are happy to announce that the initial version of our near-polished UI is up and functioning on http://dhtandem.com/. This development means that you can now go to the site and walk through uploading files as well as review some early versions of our documentation.

Immediate next steps for our team include updating the text on the documentation pages to the more robust things we have patiently waiting in the wings while we finalize the connection of the front and back components of the app. We have been powering away at creating thorough documentation and user information to be present on the final site. This also includes our exploration of the Mother Goose corpus which is beginning to take shape (in part thanks to some TANDEM supporters and volunteers from the praxis class). Basically, we’re pushing our data set through various tools for discovery and analysis. These results will become incorporated in the Sample Data section on the TANDEM website, which is intended as an example of the apps potential, and as a learning tool for new users.

As we continue to work on bugs and high priority action items, such as fixing an error with zipping files that originated from a change in processing in this iteration, we are realizing areas that could use strengthening post-dhpraxis. Our function May 19th MVP is so close we can taste it.

The zipping problem mentioned above may be related to another problem, which only happens on the server and cannot be replicated in a development environment. What appears to happen follows: when a user starts a new project, TANDEM builds three folders on the server, one for the uploaded files, one for the final output which is subsequently zipped for download. The third folder is a staging or intermediate directory that can contains files after any pre-processing that is required. For example, PDF files must be converted to JPG for our image analysis software to work. Another example is that the text must be extracted into TXT files via an OCR step for NLTK to be able to consume the content.

These new folders appear to be created successfully, and their locations are saved to global variables in the program. However, when it comes time to write files to the newly created folders, it seems that the file are being written to a previously used set of folders. The problem is intermittent. To make diagnosis more difficult, the zip step sometimes zips the older folder which delivers content from multiple projects to the user. However, other times the zip step zips the new folder which is empty delivering an empty file to the user. At still other times, the files are all read and written properly.

Zipping issues aside, we are moving along. Given all the amazing progress we have made, it is not surprising that buzz for the launch is growing. (Also Jojo invites anyone and everyone she speaks to). With new details regarding presentations, we are ready to get this party started. The DH community at CUNY and in New York has been a part of these projects whether actively or abstractly, and it seems a grand opportunity to celebrate.

 

TANDEM Project Update 4.11.15

TANDEM Week 9 Presentation

TANDEM: A Brief Agenda

I. Review our project goals

  • Discuss new interested users (advertising, biodiversity cataloging)
  • Discuss output applications in “Mother Goose Counts”

II. Describe our development drive

  • Branches of Dev underway
    • UI/UX dynamic pages
    • Django framework
    • TANDEM tool python script

III. Explain our development steps

  • Two parallel paths were followed building Python “backend” code to run the analytics on the users’ input files
  • The paths were merged and tested on a laptop
  • The Python environment was then built on the server
  • A command line versionTANDEM will now run on the server using local server-based files.
  • @sreal19 will Demo TANDEM! (Fasten your seatbelts, folks!)

IV. Discuss next steps

  • What still needs doing hooking up front and back ends.
  • Getting polished examples of our output up along with clear links to available datavis resources.
  • Getting Kelly’s best practices documentation live.
  • Outreach (not just to beta testers, but to users who might not have considered these tools before — looking for education applications/journalism
  • Now is also the time to start considering the life beyond Praxis:
  • Grants for continuing work?
  • How much labor/manpower/development would be needed to move beyond MVP?
  • What does 1.0 look like?

Thanks for following and stay tuned for updates!

@dhTANDEM #picturebookshare

tufte retweet

 

 

TANDEM Project Update Week 5

TANDEM_big logo

Excitement!

Team TANDEM is working fast and furiously on all fronts. We’ve hit a few snags but all told, we feel like we’ve got a handhold on the mountains we’re climbing. Here’s a brief overview of the ups and downs of the week:

  • Our hope we might springboard off Lev’s tool proved somewhat castles in the air. Lev’s feature extractor was coded in a day. When they went to try to run it again later they couldn’t. Lev suggested we use OpenCV instead.
  • OpenCV seems to be a massive and constantly shifting morass of dependencies.
  • Jojo attended a couple of talks from Franco Moretti and spoke with him afterwards to see if anyone at Stanford was doing anything similar. While he acknowledged the validity of studying text as image, he seems to show no further interest. Bummer, but his loss.

The Details

In development we’ve got a working program for OCR and NLTK (Go Steve!), and we’re making strides in OpenCV (Go Chris!). Lev suggested that we have two different types of picture books for our test corpus — one that’s rich in color, another that’s more gray-scale with more text. These corpus variations will show the range of data values available to future users of TANDEM. Kelly’s working on scanning an initial test corpus now.

BookScanCenter_8

We also have our hosting set up with Reclaim thanks to Tim, as well as a forwarding email domain. Go ahead and send us an email to dhtandem@gmail.com.

In design/UI/UX Kelly has been working on variations of a brand identity, for color schemes, logo, web design elements… all of it (Go Kelly!). TANDEM_Circle GlyphsThe UI is primed to go now that we have hosting for TANDEM. Kelly is currently working on identifying the code for the specific UI elements desired, for an “ideal world” situation. The next steps for design/UI/UX are to pick a final brand image, and apply it to all our outreach initiatives.

In outreach, TANDEM had a good meeting with Lev on Wednesday. He seems to think we’re doing something other DHers aren’t quite doing. We’re not yet convinced that it’s not just because it’s crazy hard. Either way, we’re up for it. Otherwise, Jojo has been working it hard (Go Jojo!) on all outreach fronts. This week we received interest from Dr. Bill Gleason at Cotsen Children’s Library at Princeton, where they’re working on ABC book digitization and seem especially interested in our image analysis. This response is proof of relevance in the field.

In regards to social media, we now have a proper twitter handle, which we will admit happened in the middle of last week’s class thanks to some pressure from Digital HUAC already having one. You can follow us @dhTANDEM. More on Twitter: TANDEM had a couple really useful retweets (hurray Alex Gil, massively connected Columbia DHer!) that generated some traffic on our website (jetpack has us at 138 views so far, which is not a ton, but it’s a start!) and has won us some good DH followers — @NYCDH, @trameproject. We’ve transferred #picturebookshare to the @dhTANDEM account, and inviting our followers to participate, as well as use it as a means to suggest additional items for our test corpus.

THE MINIMUM VIABLE PRODUCT (MVP)

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MVP version #1

Because TANDEM is leveraging tools that already exist, one very basic minimum deliverable is that TANDEM makes OCR, NLTK, and OpenCV easy to use. Moreover, if TANDEM itself is not easy to use, there is no inherent advantage in using TANDEM over simply installing the existing tools and running them.

TANDEM as this minimum deliverable would solve the issue of having these tools in a web based environment, relieving users of the laborious headache of installing the component elements. Even after installing the component elements a user would likely have to write code to obtain the required output. TANDEM will shield the user from that need to be a programmer. At this minimum deliverable, TANDEM has not wrapped the three together into a single output.

MVP version #2

A second, more advanced minimum viable product would be to have a website on which a person could upload high resolution TIFF files, press a “run TANDEM” button, and receive a .CSV document containing the core (minimum) output.

The minimum output will consist of six NLTK values (average word length, word count, unique word count, word frequency (excluding stop words), bi-grams and tri-grams) and three image statistics for each input page provided by the user. We hope to expand the range of file types that we can support and to improve the quality of our OCR output, as well as build more elaborate modules for feature detection in in both text and illustrations. However,  we contend that demonstrating the comparative values of a couple corpora of picture books will prove that there is relevant information to be found across corpora with heavy image content.

MVP #3

We are shooting for a single featured MVP. A user comes to www.dhTANDEM.com and uploads a folder of image files following the printed instructions on the screen. They are prompted to hit an “analyze” button. After a few moments, a downloadable file is generated containing OCR-ed text, key data points from the OCR-ed text, and key feature descriptors from the overall image. This is purely for an early adopter looking to generate some useful data so that they can continue working on their story and/or data visualization.​

Concerns

Overall things are going swimmingly. But of course there are concerns. This weeks concerns range from:

  • Can we get the OpenCV to do what we need in the time we have available? This seems to be the element that people really want — the visuality of illustrated print.
  • Will be able to scale the project to process the number of pages we would need for users to get the results that would prove TANDEM’s value?

These are, of course, huge questions. But to put it all in perspective: Stephen Zwiebel told Kelly this week that DH Box was held together “by tape” at the time of the final project presentations, and that it has had a lot more time in the past 9 months to become stable. Not to say that we aren’t looking to have a (minimally viable) product come May, but it’s a good feeling to know where other groups were last year. Should we be sharing that widely with the class? Well, we just did. 🙂

THANKS FOR FOLLOWING @dhTANDEM!

a bicycle built by four, for two (text AND image)

 

TANDEM USE CASES

Publishing Case:

Chris is a Data Analyst for the Advertising department of XYZ Publishing. He has the banner ads from this year’s holiday campaign. He is interested in analyzing what generated the highest click-through rates for the company. Chris has previously downloaded and installed TANDEM to his desktop tool. Chris drag-and-drops his folder of ads onto the TANDEM interface. A progress bar appears. A .csv file is generated in the backend to store the output. The completion page gives Chris a downloadable CSV. Chris is directed to brief guides on how the data could possibly be used/visualized. Chris goes the basic route and enters excel to explore his data. He compares the data to the clickthrough rates in the ad server and notices a trend in the relationship between brightness and saturation, along with the number of words on the advertisement, and how many users clicked the ad. The brightest ads with 10 words or less had the highest click through rates. Chris is able to make an data-driven argument with the design team for brighter ads with minimal text in future campaigns.

Scholar Case:

Professor Plum is studying how advertising strategies have been affected by a significant historical event such as World War I. He has collected a corpus of print advertising materials spanning multiple product categories both before and after the event which is being studied. Plum wants to know what has changed and has developed theories regarding a number of features among which are the following questions:

  • Has the proportion of text to image changed? How?
  • Has the word usage changed? How?
  • Has the iconography changed? How?
  • How has the visual style changed? Are the different colors being used? Are the images more contrasty?

Using a tool outside of TANDEM, Professor Plum scans the materials into a digital format such JPG, TIFF, PDF or GIF. After the image files have been built, he downloads a copy of TANDEM from the Internet and installs it on his desktop computer. Plum launches TANDEM and starts the analysis process by inputting the name of the folder that contains  the electronic documents being studies. TANDEM outputs OCR, NLTK and FeatureExtractor data into a database, which can be saved.

Professor Plum can now use TANDEM (or some other visualization tool) to produce visualizations or tables on the parameters that are of particular interest to the scholar. Based on the results of these visualizations, Plum may make some adjustments to the settings in TANDEM to produce a more useful result. He may choose to export the results database to another application for further work or study.

Educator Case:

An early childhood educator, Yasya Berezovskiy, wants to study the effects of children’s literature on neurological development, exploring factors such as narrative, image representations, and lexiles (or word complexity/reading level) together. To date, Berezovskiy has worked with empirical evidence and collected fieldwork data.

Berezovskiy will be analyzing a number of children’s books with varying factors, ranging from author collections, time published, and theme.

Using TANDEM Berezovskiy can upload page images or entire works to process the work’s text in comparison to the visual information. Once complete, Berezovskiy can visualize the processed files in split screen, with the original image beside the visualized data. From there, Berezovskiy can choose to isolate individual elements to analyze, such as opacity, density, text to image ratio, text to color ratio, shape to text ratio, and more. Alternately, Berezovskiy can download the raw processed data to analyze using a separate visualization program.

The processed data will be complementary to other observational research being done by Berezovskiy’s colleagues. Without TANDEM, the evidence from the children’s books would have been only descriptive. Further, without TANDEM it would have taken Berezovskiy multiple programs and more effort.

Fairy Tale Nerd Case:

The user, a woman interested in creating a datavisualization for a pop lit site like Toast.net — let’s say Ella, wants to look at Victorian illustrated fairy tale collections. Ella wants to analyze captions for art plates in all available published works. She wants a computer to process all available picture books to give her more information on the content of a work based on its visual properties as well as its textual content. She wants to get a computer to pull all the words included in the illustrations, as well as the ratio of those words in relation to what is written in the story (Are they direct quotes? Are they distinct?). She goes to the TANDEM interface. There, she sees a simple description of what files the application will yield. It’s so understandable! All the fields are so well explained! She clicks the upload button, finds the files on her computer, uploads the picture book scans, and runs the application. Once the TANDEM program has run, another window appears offering a number of file types. Each file type has a scroll over description of its applications and recommended datavis links. Once she has selected, she can download the data file (CSV or …. …..).

Ella takes it to her favorite datavis site and goes wild with joy at the new capabilities and bases for comparison. All her dreams have been answered. Thanks, TANDEM!