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Professor Melissa Terras is Director of UCL Centre for Digital Humanities, and Professor of Digital Humanities in the Department of Information Studies at University College London. She’s visiting Australia now and is one of the featured speakers at eResearch Australasia 2014. She’ll also be giving a talk on the Great Parchment Book project while she’s in Melbourne. You can come along to see this talk at:
9:30 a.m., Friday 31st October, Linkway, 4th Floor John Medley Building, The University of Melbourne
Professor Terras has generously answered some questions for us at the Research Bazaar about her work and shared some of her thoughts about the Digital Humanities.
ResBaz: Your own background includes both Classics and engineering. How were you able to pursue both interests? Was it easy to combine them or did you feel pushed to specialise in one at the expense of the other?
MT: I certainly wasn’t pushed - I was following opportunities that arose. I did art history and english lit at Glasgow University, and my MA dissertation (in scotland, you do 4 year undergrad degrees) was in Classical Art. We got the chance to do it online - this was 1998, just as the WWW was really expanding, and it was the first time that course had run - as a multimedia presentation. I loved it, and something went “ding! computing!” and I did an MSc conversion course in computing science after that, then onto Oxford to do a doctorate in Engineering Science, looking at image processing and artificial intelligence to try and read damaged ancient documents. It was a natural progression for me - combining my love of culture and heritage, with a more natural ability and affinity with computational systems. I feel incredibly lucky to have been working in that space ever since - and I also am thankful for funding opportunities that arose at the time to allow me to undertake that path.
ResBaz: You’re active on Twitter and have a personal blog. How does your social media activity complement your roles at University College London? What do you like best about engaging online?
MT: I learn so much from twitter, especially. It suits my magpie nature, hearing a lot of what is going on, all over the world, in real time, in my discipline. It has speeded up the conversation, for sure! no longer do you have to wait 2 years for things to come out in publication to know about it. I’ve made great contacts, and friendships through it. And occasionally, when you get stuck, you can just ask, and people help! The quid pro quo is that you help others too. In general, its been a very positive experience, and its a platform I’m quite heavily invested in. I see my blog as complementing that - its for longer form pieces, and then you share them on twitter - but for a bit of conversation in the middle of the working day, or for catching up as you wait on your train on the platform, twitter is great.
ResBaz: You’ve included PhD Comics in the list of ‘essential reading’ on your blog roll, but apart from the brief appearance of Gerard, PhD Comics lacks a Humanities character. Do you think that the Humanities is at risk of being marginalised in digitally driven research?
MT: Lets take PhD comics first. My personal opinion is that Jorge Cham writes what he knows - he has a PhD in engineering sciences - although a lot of what he writes about is applicable to a whole range of PhD experience. I spent 4 years in an engineering department, so for me, that was the PhD experience! But I think he does a good case with Tajel, the anthropologist, in exploring non-science issues. What went wrong with Gerard, who only appears in a couple of strips, is that instead of laughing at the PhD process, he immediately fell into the laugh-at-the-humanities-subject, which gives the character very little place to go. That’s my tuppence on why Gerard didnt get fleshed out. But overall, I think Jorge Cham has done a terrific service to academia in normalising the PhD experience, and describing a lot of the stresses and psychological issues that people face, and going “yes! its not just me! its normal to feel like *insert funny graph of work and emotion here*“. I met him once when he was at UCL - I have utmost respect for what he has done both with and for the PhD experience.
But as for Humanities being marginalised - its true they have a lot less resources, and access to a lot less infrastructure, and that makes doing digital research hard. From my point of view, the best thing to do is to build strategic alliances between computer and engineering sciences and humanities, looked for shared resources, and opportunities. And the tools available to everyone, at low or no cost, are improving every year. So the barriers to those in the humanities (provided they have a computer and network, etc) are coming down significantly. It is a problem, it has been a problem, but I’m hopeful about things, moving forward.
ResBaz: It sometimes seems that students are expected to acquire digital skills by osmosis. Do you see a place for explicit teaching of digital tools and methods in Humanities undergraduate courses?
Yes, indeed. We’ve recently gone through that process at UCL - a requirements gathering for an option for all humanities undergraduates, and it may take a year or two to get on the books, but we see that digital tools and techniques should be something that all humanities students are at least given the basics on, not just for Digital Humanities research, but for an information literacy point of view. They should know about digital skills, and be taught how to find and manipulate data, and sources, in a structured way. The digital shift isn’t going away any time soon, and all humanities students really should have some element of digital skills taught, as part of a whole range of approaches and methods they are exposed to.
ResBaz: I’ve seen it suggested that Digital Humanities has a 'dark side’, in that it adds another set of skills Humanities graduates can be expected to acquire, while there are deeper problems in the academic job market and the funding of Humanities. Do you think there is a danger that Digital Humanities becomes an attempt to justify Humanities research to funders or employers in an increasingly competitive sector?
MT: Its not just the Digital Humanities that has problems - most of academia is a bit of a bottle neck, as far as PhD to Job goes, and there are huge issues in the USA with adjuncts, etc, doing a lot of teaching, and huge issues worldwide about privilege in the academy, and elitism, and gender issues, and race issues… so there is a lot in the academy that needs improving, and tackling. As for DH’s own bug bears, I sometimes think that a lot of these issues are brought up in relation to DH because there are so many people from DH talking openly online about all aspects of DH - but it doesn’t mean that these are “just” problems for DH. I see that a lot in discussions about DH - actually, it’s the whole academy which could be held up to account for these things, but DH seems to be getting a lot of flack for it. The issues are the same in many disciplines. And they are issues, which need tackling. Expecting people to get lots of skills to get jobs… well, there’s no getting away from it, if you want to work in Digital Humanities, you need to have an aptitude and an ability for both the Digital, and the Humanities. The academy has never been fair (although it has, at times, been fairer that others). I also don’t believe the Humanities are sinking - if you look at the 4humanities.org website you can see how vibrant the support for them is at the moment.
ResBaz: It seems we often focus on bringing technology to Humanities problems, but surely the benefits flow both ways. Do you see Humanities researchers bringing benefits to science or technology projects?
MT: Absolutely. The issues they bring are real world issues, which are often fuzzy in nature, and terribly hard to crack: we see that in our imaging work, that we are doing - it means that new solutions have to be found in computing science, which then can often help or change the trajectory of methods being applied to other problems. There is a large amount of DH that now takes off the shelves tools, but there are some of us working as equals with computing and engineering science - there is a new discipline currently forming called “Heritage Science” that works equally across these traditional boundaries - but it is intellectually stimulating for both sides of the academic divide to work in a cross-discplinary manner… if you find the right project, and right collaborators! (and often, we talk about disciplines, when really, it all comes down to the right individual project, and working with people who are open to this kind of work).
ResBaz: Do you think that, as digital tools and methods become more integrated into the toolbox of the Humanities researcher, we’ll stop talking about 'Digital Humanities’, or do you think we’ll continue to be explicit about its methodologies?
MT: I think when digital methods become embedded into the Humanities, a lot of the DH stuff will have done its work - we already see it with people using various tools for mapping or text analysis - but there is still a place for those further along the technology life cycle (or rather, right at the start of the technology life cycle) looking at various new opportunities that emerge, and saying “how can I use this in the humanities?” and questioning the use of technologies, and how applicable they are, and what it means to apply these - thats our job as humanists, to be critical of that. I spoke about this at length in my professorial inaugural this year, which scopes out the place for Digital Humanities, given that digital technologies are becoming ever more pervasive in our society. The tech will keep coming, and we have to keep questioning, building, applying, and reflecting. Thats not going to go away any time soon!
You can watch Prof. Terras’ lecture A Decade in Digital Humanities here
No matter your research discipline, there will be something to satisfy your research training taste buds at the Research Bazaar Conference. There will be four major teaching streams running concurrently over multiple sessions and days (i.e. each participant will sign up to one of these), plus a number of other elective classes that anyone can attend.
Stream 1: Programming and data analysis using Python, R or MATLAB
Stream 2: Research maps using CartoDB and TileMill
Stream 3: Natural language processing using Python
Stream 4: Drawing and printing 3D objects using AutoDesk Inventor
Extras: Elective classes
Programming and data analysis using Python, R or MATLAB
Researchers spend much of their time wrestling with software, but most are self-taught programmers. As a result, they spend hours doing things that should take minutes, reinvent a lot of wheels, and still don’t know if their results are reliable. To tackle this problem, we’re running a stream based on the world renowned Software Carpentry teaching syllabus.
Our volunteer @swcarpentry #matlab tutors are hard at work! Thanks tutors! #ResBaz @ITS_Res https://t.co/FFexdWspje
— Damien Irving (@DrClimate)
August 18, 2014
The target audience for Software Carpentry is researchers with a basic familiarity with programming concepts like loops, conditionals, and arrays, but who need help to translate this knowledge into practical tools to help them work more productively. The syllabus covers:
Research maps using CartoDB and TileMill
The research maps stream will begin with an introduction to CartoDB, which is a simple yet powerful tool that lets you visualise data onto maps. You’ll learn how to format data to make a map visualisation, and we’ll explore the range of inbuilt features that CartoDB offers and how to start customising these tools to produce a map that communicates your research data. Finally, we’ll explore more complex data visualisation and how to publish and share your maps.
Three intense @cartoDB and @tilemill workshops at UWS completed: http://t.co/jvHI8bE7Uv http://t.co/iUjtXijfaZ and http://t.co/o7g7YM76yz
— Steve Bennett (@stevage1)
July 22, 2014
After this introduction to CartoDB the mapping stream will move on to TileMill, which is a more advanced tool that has many more options for map customisation. In the TileMill sessions you’ll learn about the art of cartography and the types of data that you can access and use in TileMill. We’ll introduce you to CartoCSS, so you can customise the appearance of your map and control the level of detail that appears and create a map that you’ll be proud to publish. Finally, we’ll look at how to publish and share your creations.
The mapping stream is recommended for researchers who want to be able to create highly customised maps to illustrate their research. No knowledge of programming is necessary.
Natural language processing using Python
What do you do when you want to comment on features of the language in a large corpus of text? Python’s Natural Language Toolkit (NLTK) offers a powerful means of analysing text and provides a basis for understanding more complex text mining tools. During the NLTK sessions at ResBaz, participants will be introduced to Python and learn to apply NLTK to answering questions about text. The course will also address how to prepare texts for analysis with NLTK or similar tools. These sessions are particularly designed for researchers in the humanities and social sciences and no knowledge of programming is required.
Guest blog from @FCTweedie on her #mozfest session re: the Python Natural Language Toolkit: http://t.co/IErz7Mmsez
— Mozilla Science Lab (@MozillaScience)
October 16, 2014
Drawing and printing 3D objects using AutoDesk Inventor
Interested in creating 3D models as part of your research? Interested in designing and 3D printing your experiment apparatus? Participants in this stream will use AutoDesk Inventor to create basic parametric 3D models for 3D printing.
Best.#Lego.#Solidworks.Model.Ever #resbaz #digismith #cad https://t.co/XfNMXAnC1R .@SOLIDWORKS .@Dassault3DS
— Paul Mignone (@paulmignone)
August 23, 2014
Elective classes
Genomics data workflows using Galaxy: Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.
Medical/clinical surveys with REDCap: Nowadays more and more research studies need to collect data from disparate places or people in an electronic format that facilitates their management. REDCap assists this process by providing a secure web application designed to support data capture and management for clinical or health-related research studies. Collected data can be easily exported afterwards for analysis using statistical tools. If you need or want to collect health-related data in an electronic format for your project or you need to conduct health-related surveys then REDCap is the tool for you.
Online collaborative editing using Authorea: We’re very excited to announce that the co-founders of Authorea - an academic start-up that’s fundamentally changing the way researchers write papers - will be at ResBaz to present an introduction to Authorea and a crash course in LaTeX. There will be two different electives available - one for the Humanities and one for the Sciences. Authorea for Humanies will include integration with reference managers, embedding images, and working with non-standard fonts and characters. Authorea for Sciences will explore embedding graphs and figures and including large formulae or equations.
The @authorea tutorial is underway at #g3workshop! @ResPlat @GigaScience pic.twitter.com/hUgpH55HIx
— Damien Irving (@DrClimate)
September 19, 2014
Introduction to the Research Cloud: The session is going to be a high level introduction to the conceptual foundations, advantages, disadvantages, and the parts of the research cloud. If you understand these then you’ll be far less likely to be bitten in your journey to the cloud: and given the scale and low price of the research cloud you will, most likely, be making that journey.
Databases and SQL: Almost everyone has used spreadsheets, and almost everyone has eventually run up against their limitations. The more complicated a data set is, the harder it is to filter data, express relationships between different rows and columns, or handle missing values. Databases pick up where spreadsheets leave off. While they are not as simple to use if all we want is the sum of a dozen numbers, they can do a lot of things that spreadsheets can’t, on much larger data sets, faster. And even if we never need to create a database ourselves, knowing how they work will help us understand why so many of the systems we use behave the way we do, and why they insist on structuring data in certain ways.
Introduction to 3D printing: 3D printing is changing the way we create, design, and manufacture objects. In this session, we’ll introduce the concept of 3D printing, take a look at it’s many applications in different industries, and visit the Engineering Workshop where you can have a first-hand look at 3D printers in action (and maybe print something for yourself!).
Social media for research: Interested in collaborations? Sharpening your academic writing? Increasing your reputability? Enhancing the public’s understanding of research? Sourcing ideas? Endorsing your publications? Well, have you considering Twitter or blogging? Step inside the world of social. In this workshop, we’ll show you how to use social media in scholarly ways - to better your research, from start to finish. You’ll be tweeting (alongside your favourite academics) in no time at all.
Critical approaches to Big Data: Research taking advantage of enormous datasets is become more and more common, both within and outside academia. While much attention has been paid to methodologies for manipulating and extracting findings from Big Data, critical discussion of the ontology and epistemology of Big Data research is only beginning to emerge. In this elective, Big Data is conceptualised as both theory and resource. After briefly sketching the current landscape of Big Data research, claims concerning the ability of Big Data to provide more objective insights, or to reveal new things about human life, are problematised. Ethical issues and ownership and control of data are also briefly discussed.
Online surveys with LimeSurvey: LimeSurvey is a user-friendly tool for creating and managing online surveys. It offers a number of templates to help you get your survey right and a single user account lets you run multiple surveys. LimeSurvey lets you create complex conditions between questions and, with MySQL as the back-end database, is also great for analysing your results once they’re in. As LimeSurvey is also hosted by the University of Melbourne, you can be confident that your respondents private information won’t be stored off-shore.
A crash course in Wikipedia editing: Increasingly, participating in online projects is an important way to grow your online profile and disseminate your research. But beware - Wikipedia editing has its own etiquette and the community will let you know if you’re doing it wrong. In this short workshop, we’ll introduce you to the fun of Wikipedia editing while helping you to avoid some of the traps along the way.
Our “Warm up to Wikipedia” workshop last week got half a dozen new articles into Wikipedia! http://t.co/pI88hsaGej https://t.co/vBpa5B9yX2
— Research Platforms (@ResPlat)
August 13, 2014
High performance computing using MATLAB: High performance computing (HPC) is traditionally complicated and involves a steep programatic learning curve. HPC 2.0 involves using any and all tips and tricks to make your existing code run faster. There are actually a number of simple things you can do to substantially speed up your code. We’re offering an introduction to *some* examples in MATLAB, including techniques like automatic vectorisation as well as new learning how to run MATLAB code on Graphics Processing Units (GPUs).
Final session of the #matlab @swcarpentry bootcamp - an intro to #HPC. @ResPlat #ResBaz pic.twitter.com/8YXePvpxw2
— Damien Irving (@DrClimate)
August 27, 2014
Analysing urban data with AURIN: In Part One, we will introduce you to over 1300 Australian urban datasets accessible by urban researchers containing a wealth of information on health, socio-economics, demographics and the built environment in general. Not only mash-up open datasets, but access secure data restricted for urban policy development and use a suite of online mapping and decision support tools. In Part Two we will explore specialised analytical tools that pull together diverse sources of data surrounding human settlements and combine them to reveal patterns and solve problems. We will look at how transport networks, population density and industry clustering interact at the meso-urban scale and how we might be able to create more sustainable, healthier built environments.
Image repositories with Omeka: Omeka is an image repository originally designed to help small galleries and museums to create online exhibitions but which can also be used as a research database. Omeka makes it easy to search across your collection and handles images, video and descriptive text. In this session you’ll learn the basics of Omeka, including formatting data, creating metadata, building a collection and creating an online exhibition. This session is recommended for researchers who want an easy-to-use database to manage and share their research, especially those working with cultural collections. It is ideally suited for, but not limited to, art historians and archivists. No knowledge of programming is necessary.
Python and data management in the atmospheric and ocean sciences: If you work/study in the atmospheric and ocean sciences and have a basic knowledge of the command line and Python, then do not miss this session. Damien Irving will take you through the Python libraries and data management practices that will make your life that much easier!
If you’re having trouble deciding what tool would be best for your research, feel free to send us a Tweet (@ResPlat), come down to Hacky Hour for a chat, or contact one of our Research Community Coordinators who will be more than happy to help you figure out the most appropriate tool for your data.
In July and August this year, we at @resbaz did a university first. Over six weeks, we ran a series of ‘alpha’ Computer Aided Design (CAD) workshops to over a hundred Melbourne School of Engineering students. For quite a few years, there has been growing interest from engineering students at the university for providing opportunities to learn and develop CAD skills.
The calm before the storm…
This has been mainly due to employers expecting engineering students to have these skills upon graduation. In addition, students have greater access to 3D printing resources, giving them opportunities fabricate many of their projects. Therefore with the help of Dr. Colin Burvill, and some awesome people from MUR Motorsports, we taught a series of one-day Solidworks CAD courses.
The CAD workshops were a full house every Saturday!
Each class was followed up with a feedback session, where we incorporated student feedback into the course for the next iteration. By the end of the six weeks, we had a series of modules which quickly and effectively taught part design, assembly setup and engineering drawing within a single day. A draft of the course can be freely-downloaded here.
Creating sketches in Solidworks #resbaz #digismith https://t.co/KduBFyKoZm
— Fiona Tweedie (@FCTweedie)
August 22, 2014
CAD in the Vine!
Once again, without the help of some fantastic people from MUR, this course would not have been possible. They are as follows:
Jacob (a.k.a Squishy) teaching part design!
Squishy on the #solidworks vine #digismith #resbaz https://t.co/s4HoQXYdkc via @vineapp
— Paul Mignone (@paulmignone)
August 23, 2014
Darcy teaching applied part design and reverse engineering!
Darcy on the #solidworks vine #resbaz #digismith #cad https://t.co/GX0z396KGc
— Paul Mignone (@paulmignone)
August 23, 2014
Alex teaching engineering drawing!
Alex shows us #solidworks drawings on the vine #resbaz #cad #digismith https://t.co/3WPuLPCr2z
— Paul Mignone (@paulmignone)
August 23, 2014
Clarke teaching assembly modelling…by assembling Lego!
Clarke shows #lego on the #solidworks vine #resbaz #digismith #cad https://t.co/FUvt4qWtQe
— Paul Mignone (@paulmignone)
August 23, 2014
So what’s next for CAD at UniMelb? Plenty. With the ResBaz conference around the corner, we have a series of CAD classes around Autodesk Inventor an Civil3D designed to grow and develop the local community of CAD users at UniMelb. Stay tuned for details…
Best.#Lego.#Solidworks.Model.Ever #resbaz #digismith #cad https://t.co/XfNMXAnC1R .@SOLIDWORKS .@Dassault3DS
— Paul Mignone (@paulmignone)
August 23, 2014
Best.Lego.Model.Ever.Clarke
(THE RISE OF THE DIGITALLY NATIVE RESEARCHER)
“In five years time, researchers will no longer spend the majority of their time in word-processing and ‘office’ tools; the researcher’s day will be spent using discipline specific apps, digital toolchains and datasets which will be shared with research partners worldwide…”
[Bio21 Institute connect their digital research equipment to a series of digital workflow tools which enable secure collaboration across the research team]
How can researcher focused departments in Universities be ready for supporting the new tide of data driven research, and digital native, digital research tools and data sets?
————-
“In five years time, all research students and early career researchers will have natively used dozens of social media tools which will facilitate their face-to-face interactions, enhancing trusted new partnerships with fellow digital research natives worldwide…”
[Digitally native researchers enhance their face-to-face community relationships with social platforms they’ve used their entire lives]
How can we be ready for the tide-change of researchers who natively collaborate through new social platforms (digital and face-to-face)?
Let’s begin to unravel the answer to these questions together! Join our ‘online’ community through Twitter, Facebook, Tumblr & YouTube.
But more importantly, let’s chat 'offline’! Come to HackyHour (on every Thursday at Tsubu), one of our events, or especially our ResBaz Conference in Feb 2015!
It’s through these conversations, connections and collaborations that we can change and better the face of research.
Last week we held our first ever software carpentry bootcamp for the R statistical programming language. Rather than teach to a room of novice learners, we pitched this bootcamp to a much smaller crowd of potential helpers and instructors. We did this for two reasons:
Testing the #RStudio @swcarpentry teaching materials on the @projectnectar Research Cloud! #ResBaz @sritchie73
— Research Platforms (@ResPlat)
September 23, 2014
While the python teaching materials are quite mature, this is not the case for the R materials. Although there have been roughly 30 R bootcamps taught in the past year, these have come from each individual instructor, rather than from a unified set of materials.
Currently there are two sets of materials in the Software Carpentry lessons repository:
We chose to work from the intermediate materials for two reasons:
Many on the R-discuss mailing list have also recently expressed they would not be using the novice materials, for reasons similar to #1 above, and there are plans for a conference call in the next few weeks to discuss the path forward for creating appropriate novice materials.
We spent a full day going through the intermediate materials. The lessons covered can be found here on the bootcamp site, and feedback on the material and teaching can be found on the corresponding etherpad. In summary, we found the material was became too technical too quickly, lacked research context, and lacked sufficiently spaced challenges.
At the end of the day, we sat down and brainstormed on ways to transform this material into something suitable for novices, but also representative of real world R code. We came up with a list of challenges to re-mold the intermediate materials around, splitting them across two afternoons (we find splitting bootcamps across afternoons is much better for helping attendees retain knowledge, and avoid scheduling conflicts).
Afternoon 1: Understanding Data Types
Confusion over data types is one of the biggest struggles for novice R users, so we still want to provide a strong foundation by creating lessons around them.
The goal of afternoon 1 is to teach attendees how to read in various types of data, what those data structures mean, extract a useful subset of the data, and visualise it.
Lesson 1: Read in some small research datasets for each data type (matrix, data.frame, list) so that the instructor can explain the different data types.
Challenge 1: (a)Create vectors of various types, (b) combine them into a matrix, data.frame, list. What happened? Is it what you expected?
Lesson 2:Seeking help and collaborating. Teach attendees how to save/write objects.
Challenge 2: Save the object you created for challenge 1, and share it with the person next to you. Load in their data.
Lesson 3: Subsetting data
Challenge 3: current exercises for intermediate materials “R Basics”
Lesson / Challenge 4: Plotting data
Afternoon 2: Wrangling and Exploring Data
The goal of the second afternoon is to dive deeper into data exploration, introducing the split-apply-combine (a.k.a MapReduce) pattern of problem solving, which includes writing your own functions.
Lesson 5: The apply lesson from the intermediate materials, with the split-apply-combine image from the alternate lesson.
Challenge 5: applying some basic function to groups within some loaded data.
Lesson 6: writing your own functions (and using them inside apply).
Challenge 6:write a function to do x, and apply it to the groups as before.
Lesson / Challenge 7: Plotting data subsets
Lesson 8: Seeking help: stackoverflow (minimal reproducible example, dput!), CRAN task views
Challenge 8: “Package Speed dating”: instructors + helpers break off into small groups to show off useful/cool packages related to their area of expertise.
Another thought we had was creating an R cheatsheat, featuring common “gotchas” and protips, pointing out useful functions, and default arguments to common functions that may trip you up (e.g. stringsAsFactors).
We will be sharing our experience and thoughts with the R software carpentry community, and actively contributing to the next iteration of R novice materials. We plan to run a larger R bootcamp in late November / early December with the updated materials. Watch this space for dates!
