Student Impressions of Tech Skills for the Field

by Sarah Nguyen


Back in March, during bloggERS’ Making Tech Skills a Strategic Priority series, we distributed an open survey to MLIS, MLS, MI, and MSIS students to understand what they know and have experienced in relation to  technology skills as they enter the field. 

To be frank, this survey stemmed from personal interests since I just completed an MLIS core course on Research, Assessment, and Design (re: survey to collect data on current landscape). I am also interested in what skills I need to build/what class I should sign up for my next quarter (re: what tech skills do I need to become hire-able?). While I feel comfortable with a variety of tech-related tools and tasks, I’ve been intimidated by more “high-level”computational languages for some years. This survey was helpful for exploring what skills other LIS pre-professionals are interested in and which skills will help us make these costly degrees worth the time and financial investment that is traditionally required to enter a stable archive or library position.

Method

The survey was open for one month on Google Forms, and distributed to SAA communities, @SAA_ERS Twitter, the Digital Curation Google Group, and a few MLIS university program listservs. There were 15 questions and we received responses from 51 participants. 

Results & Analysis

Here’s a superficial scan of the results. If you would like to come up with your own analyses, feel free to view the raw data on GitHub.

Figure 1. Technology-related skills that students want to learn

The most popular technology-related skill that students are interested in learning is data management (manipulating, querying, transforming data, etc.). This is a pretty broad topic as it involves many tools and protocols which can vary between a GUI or scripts. A separate survey that does a breakdown of specific data management tools might be in order, especially since these types of skills can be divided into specialty courses, workshops, which then translates into a specific job position. A more specific survey could help demonstrate what types of skills need to be taught in a full semester-long course, or what skills can be covered in a day-long or multi-day workshop.

It was interesting to see that even in this day and age where social media management can be second nature to many students’ daily lives, there was still a notable interest in understanding how to make this a part of their career. This makes me wonder what value students have in knowing how to strategically manage an archives’ social media account. How could this help with the job market, as well as an archival organization’s main mission?

Looking deeper into the popular data management category, it would be interesting to know the current landscape of knowledge or pedagogy in communicating with IT (e.g. project management and translating users’ needs). In many cases, archivists are working separately from but dependently on IT system administrators, and it can be frustrating since either department may have distinct concerns about a server or other networks. In June’s NYC Preservathon/Preservashare 2019, there was mention that IT exists to make sure servers and networks are spinning at all hours of the day. Unlike archivists, they are not concerned about the longevity of the content, obsolescence of file formats, or the software to render files. Could it be useful to have a course on how to effectively communicate and take control of issues that can be fuzzy lines between archives, data management, and IT? Or as one survey respondent said, “I think more basic programming courses focusing on tech languages commonly used in archives/libraries would be very helpful.” Personally, I’ve only learned this from experience working in different tech-related jobs. This is not a subject I see on my MLIS course catalog, nor a discussion at conference workshops. 

The popularity of data management skills sparked another question: what about knowledge around computer networks and servers? Even though LTO will forever be in our hearts, cloud storage is also a backup medium we’re budgeting for and relying on. Same goes for hosting a database for remote access and/or publishing digital files. A friend mentioned this networking workshop for non-tech savvy learners—Grassroots Networking: Network Administration for Small Organizations/Home Organizations—which could be helpful for multiple skill types including data management, digital forensics, web archiving, web development, etc. This is similar to a course that could be found in computer science or MLIS-adjacent information management departments.

Figure 2. Have you taken/will you take technology-focused courses in your program?
Figure 3. Do you feel comfortable defining the difference between scripting and programming

I can’t say this is statistically significant, but the inverse relationship between 15.7% who have not/will not take a technology-focused course in their program, compared to 78.4% of respondents who are not aware of the difference between scripting and programming is eyebrow raising. According to an article in PLOS Computational Biology,  the term “script” means “something that is executed directly as is”, while a “program[… is] something that is explicitly compiled before being used. The distinction is more one of degree than kind—libraries written in Python are actually compiled to bytecode as they are loaded, for example—so one other way to think of it is “things that are edited directly” and “things that are not edited directly” (Wilson et al 2017). This distinction is important since more archives are acquiring, processing and sharing collections that rely on the archivist to execute jobs such as web-scraping or metadata management (scripts) or archivists who can build and maintain a database (programming). These might be interpreted as trick questions, but the particular semantics and what is considered technology-focused is something modern library, archives, and information programs might want to consider. 

Figure 4. How do you approach new technology?

Figure 4 illustrates the various ways students tackle new technologies. Reading the f* manual (RTFM) and Searching forums are the most common approaches to navigating technology. Here are quotes from a couple students on how they tend to learn a new piece of software:

  • “break whatever I’m trying to do with a new technology into steps and look for tutorials & examples related to each of those steps (i.e. Is this step even possible with X, how to do it, how else to use it, alternatives for accomplishing that step that don’t involve X)”
  • “I tend to google “how to….” for specific tasks and learn new technology on a task-by-task basis.”

In the end, there was overwhelming interest in “more project-based courses that allow skills from other tech classes to be applied.” Unsurprisingly, many of us are looking for full-time, stable jobs after graduating and the “more practical stuff, like CONTENTdm for archives” seems to be a pressure felt in-order to get an entry-level position. Not just entry too; as continuing education learners, there is also a push to strive for more—several respondents are looking for a challenge to level up their tech skills: 

  • “I want more classes with hands-on experience with technical skills. A lot of my classes have been theory based or else they present technology to us in a way that is not easy to process (i.e. a lecture without much hands-on work).”
  • “Higher-level programming, etc. — everything on offer at my school is entry level. Also digital forensics — using tools such as BitCurator.”
  • “Advanced courses for the introductory courses. XML 2 and python 2 to continue to develop the skills.”
  • “A skills building survey of various code/scripting, that offers structured learning (my professor doesn’t give a ton of feedback and most learning is independent, and the main focus is an independent project one comes up with), but that isn’t online. It’s really hard to learn something without face to face interaction, I don’t know why.”

It’ll be interesting to see what skills recent MLIS, MLS, MIS, and MSIM graduates will enter the field with. While many job postings list certain software and skills as requirements, will programs follow suit? I have a feeling this might be a significant question to ask in the larger context of what is the purpose of this Master’s degree and how can the curriculum keep up with the dynamic technology needs of the field.

Disclaimer: 

  1. Potential bias: Those taking the survey might be interested in learning higher-level tech skills because they do not already know the skills, while those who are already tech-savvy might avoid a basic survey such as this one since they already know the skills. This may put a bias on the survey population consisting of mostly novice tech students.   
  2. More data on specific computational languages and technology courses taken are available in the GitHub csv file. As mentioned earlier, I just finished my first year as a part-time MLIS student, so I’m still learning the distinct jobs and nature of the LIS field. Feel free to submit an issue to the GitHub repo, or tweet me @snewyuen if you’d like to talk more about what this data could mean.

Bibliography

Wilson G, Bryan J, Cranston K, Kitzes J, Nederbragt L, Teal TK (2017) Good enough practices in scientific computing. PLoS Computational Biology 13(6): e1005510. https://doi.org/10.1371/journal.pcbi.1005510


Sarah Nguyen with a Uovo storage truck

Sarah Nguyen is an advocate for open, accessible, and secure technologies. While studying as an MLIS candidate with the University of Washington iSchool, she is expressing interests through a few gigs: Project Coordinator for Preserve This Podcast at METRO, Assistant Research Scientist for Investigating & Archiving the Scholarly Git Experience at NYU Libraries, and archivist for the Dance Heritage Coalition/Mark Morris Dance Group. Offline, she can be found riding a Cannondale mtb or practicing movement through dance. (Views do not represent Uovo. And I don’t even work with them. Just liked the truck.)

Assessing the Digital Forensics Instruction Landscape with BitCuratorEdu

by Jess Farrell

This is the sixth post in the bloggERS Making Tech Skills a Strategic Priority series.

Over the past couple of months, we’ve heard a lot on bloggERS about how current students, recent grads, and mid-career professionals have made tech skills a strategic priority in their development plans. I like to think about the problem of “gaining tech skills” as being similar to “saving the environment”: individual action is needed and necessary, but it is most effective when it feeds clearly into systemic action.

So that begs the question, what root changes might educators of all types suggest and support to help GLAM professionals prioritize tech skills development? What are educator communities and systems – iSchools, faculty, and continuing education instructors – doing to achieve this? These questions are among those addressed by the BitCuratorEdu research project.

The BitCuratorEdu project is a two three-year effort funded by the Institute of Museum and Library Services (IMLS) to study and advance the adoption of born-digital archiving and digital forensics tools and methods in libraries and archives through a range of professional education efforts. The project is a partnership between the School of Information and Library Science at the University of North Carolina at Chapel Hill and the Educopia Institute, along with the Council of State Archivists (CoSA) and nine universities that are educating future information professionals.

We’re addressing two main research questions:

  1. What are the primary institutional and technological factors that influence adoption of digital forensics tools and methods in different educational settings?
  2. What are the most viable mechanisms for sustaining collaboration among LIS programs on the adoption of digital forensics tools and methods?

The project started in September 2018 and will conclude in Fall 2021, and Educopia and UNC SILS will be conducting ongoing research and releasing open educational resources on a rolling basis. With the help of our Advisory Board made up of nine iSchools and our Professional Experts Panel composed of leaders in the GLAM sector, we’re:

  • Piloting instruction to produce and disseminate a publicly accessible set of learning objects that can be used by education providers to administer hands-on digital forensics education
  • Gathering information and centralizing existing educational content to produce guides and other resources, such as this (still-in-development) guide to datasets that can be used to learn new digital forensics skills or test digital archives software/processes
  • Investigating and reporting on institutional factors that facilitate, hinder and shape adoption of digital forensics educational offerings

Through this work and intentional community cultivation, we hope to advance a community of practice around digital forensics education though partner collaboration, wider engagement, and exploration of community sustainability mechanisms.

To support our research and steer the direction of the project, we have conducted and analyzed nine advisory board interviews with current faculty who have taught or are developing a curriculum for digital forensics education. So far we’ve learned that:

  • instructors want and need access to example datasets to use in the classroom (especially cultural heritage datasets);
  • many want lesson plans and activities for teaching born-digital archiving tools and environments like BitCurator in one or two weeks because few courses are devoted solely to digital forensics;
  • they want further guidance on how to facilitate hands-on digital forensics instruction in distributed online learning environments; and
  • they face challenges related to IT support at their home institutions, just like those grappled with by practitioners in the field.

This list barely scratches the surface of our exploration into the experiences and needs of instructors for providing more effective digital forensics education, and we’re excited to tackle the tough job of creating resources and instructional modules that address these and many other topics. We’re also interested in exploring how the resources we produce may also support continuing education needs across libraries, archives, and museums.

We recently conducted a Twitter chat with SAA’s SNAP Section to learn about students’ experiences in digital forensics learning environments. We heard a range of experiences, from students who reported they had no opportunity to learn about digital forensics in some programs, to students who received effective instruction that remained useful post-graduation. We hope that the learning modules released at the conclusion of our project will address students’ learning needs just as much as their instructors’ teaching needs.

Later this year, we’ll be conducting an educational provider survey that will gather information on barriers to adoption of digital forensics instruction in continuing education. We hope to present to and conduct workshops for a broader set of audiences including museum and public records professionals.

Our deliverables, from conference presentations to learning modules, will be released openly and freely through a variety of outlets including the project website, the BitCurator Consortium wiki, and YouTube (for recorded webinars). Follow along at the project website or contact jess.farrell@educopia.org if you have feedback or want to share your insights with the project team.

 

Authors bio:

Jess Farrell is the project manager for BitCuratorEdu and community coordinator for the Software Preservation Network at Educopia Institute. Katherine Skinner is the Executive Director of Educopia Institute, and Christopher (Cal) Lee is Associate Professor at the School of Information and Library Science at the University of North Carolina, Chapel Hill, teaching courses on archival administration, records management, and digital curation. Katherine and Cal are Co-PIs on the BitCuratorEdu project, funded by the Institute of Museum and Library Services.

Just do it: Building technical capacity among Princeton’s Archival Description and Processing Team

by Alexis Antracoli

This is the fifth post in the bloggERS Making Tech Skills a Strategic Priority series.

ArchivesSpace, Archivematica, BitCurator, EAD, the list goes on! The contemporary archivist is tasked with not only processing paper collections, but also with processing digital records and managing the descriptive data we create. This work requires technical skills that archivists twenty or even ten years ago didn’t need to master. It’s also rare that archivists get extensive training in the technical aspects of the field during their graduate programs. So, how can a team of archivists build the skills they’ll need to meet the needs of an increasingly technical field? At the Princeton University Library, the newly formed Archival Description and Processing Team (ADAPT), is committed to meeting these challenges by building technical capacity across the team. We are achieving this by working on real-world projects that require technical skills, and by leveraging existing knowledge and skills in the organization, seeking outside training, and championing supervisor support for using time to grow our technical skills.

One of the most important requirements for growing technical capacity on the processing team is supervisor support for the effort. Workshops, training, and solving technical problems take a significant amount of time. Without management support for the time needed to develop technical skills, the team would not be able experiment, attend trainings, or practice writing code. As the manager of ADAPT, I make this possible by encouraging staff to set specific goals related to developing technical skills on their yearly performance evaluations; I also accept that it might take us a little longer to complete all of our processing. To fit this work into my own schedule, I identify real-world problems and block out time on my schedule to work on them or arrange meetings with colleagues who can assist me. Blocking out time in advance helps me stick to my commitment to building my technical skills. While the time needed to develop these skills means that some work happens more slowly today, the benefit of having a team that can manipulate data and automate processes is an investment in the future that will result in a more productive and efficient processing team.

With the support to devote time to building technical skills, ADAPT staff use a number of resources to improve their skills. Working with internal staff who already have skills they want to learn has been one successful approach. This has generally paired well with the need to solve real-world data problems. For example, we recently identified the need to move some old container information to individual component-level scope and content notes in a finding aid. We were able to complete this after several in-house training sessions on XPath and XQuery taught by a Library staff member. This introductory training helped us realize that the problem could be solved with XQuery scripting and we took on the project, while drawing on the in-house XQuery expert for assistance. This combination of identifying real-world problems and leveraging existing knowledge within the organization leads both to increased technical skills and projects getting done. It also builds confidence and knowledge that can be more easily applied to the next situation that requires a particular kind of technical expertise.

Finally, building in-house expertise requires allowing staff to determine what technical skills they want to build and how they might go about doing it. Often that requires outside training. Over the past several years, we have brought workshops to campus on working with the command line and using the ArchivesSpace API. Staff have also identified online courses and classes offered by the Office of Information Technology as important resources for building their technical skills. Providing support and time to attend these various trainings or complete online courses during the work day creates an environment where individuals can explore their interests and the team can build a variety of technical skills that complement each other.

As archival work evolves, having deeper technology skills across the team improves our ability to get our work done. With the right support, tapping into in-house resources, and seeking out additional training, it’s possible to build increased technological capability with the processing team. In turn, the team will increasingly be able to more efficiently tackle day-to-day technical challenges needed to manage digital records and descriptive data.


Alexis Antracoli is Assistant University Archivist for Technical Services at Princeton University Library where she leads the Archival Processing and Description Team. She has published on web archiving and the archiving of born-digital audio visual content. Alexis is active in the Society of American Archivists, where she serves as Chair of the Web Archiving Section and on the Finance Committee. She is also active in Archives for Black Lives in Philadelphia, an informal group of local archivists who work on projects that engage issues at the intersection of the archival profession and the Black Lives Matter movement. She is especially interested in applying user experience research and user-center design to archival discovery systems, developing and applying inclusive description practices, and web archiving. She holds an M.S.I. in Archives and Records Management from the University of Michigan, a Ph.D. in American History from Brandeis University, and a B.A. in History from Boston College.

Students Reflect (Part 2 of 2): Failure and Learning Tech Skills

This is the fourth post in the bloggERS Making Tech Skills a Strategic Priority series.

As part of our “Making Tech Skills a Strategic Priority” series, the bloggERS team asked five current or recent MLIS/MSIS students to reflect on how they have learned the technology skills necessary to tackle their careers after school. In this post, Anna Speth and Jane Kelly reflect thoughtfully on adapting their mindsets to embrace new challenges and learn from failure.

Anna Speth, 2017 graduate, Simmons College

I am about to celebrate a year in my first full-time position, Librarian for Emerging Technology and Digital Projects at Pepperdine University.  In this role I work on digital initiatives, often in tandem with the archive, and direct our emerging technology makerspace. By choosing to center my graduate career on digital archiving, I felt well prepared for the digital initiatives piece.  However, running the makerspace has been a whirlwind of grappling with the world of emerging tech. My best piece of advice (which we’ve all heard a million times) is to maintain a “learner mindset.” I’m a traditional learner who has mastered the lecture-memorize-regurgitate academic system. This approach doesn’t do much when it comes to hands-on tech.  I am faced with 3D printers, VR systems, arduinos, ozobots, CONTENTdm, and more with minimal instruction. I watch tutorials, but these rarely offer a path to in-depth understanding. Instead, I’ve had to overcome the mindset that I’m not a tech person and will make something worse by messing with it. If the 3D printer doesn’t work, you certainly aren’t going to make it worse by taking it apart and trying to put it back together. If you don’t know how to reorder a multipage object on the backend of CONTENTdm, create a hidden sandbox collection and start experimenting.  Remember that the internet – Google, user forums, Reddit, company reps – is your friend. Also remember (and I tell this to kids in the makerspace just as often as I tell it to myself) that failure is your friend. If you mess something up, then all you’ve done is learn more about how the system works by learning how it doesn’t work. Iteration and perseverance are key. And, as this traditional learner has realized, a whole lot of fun!

Jane Kelly, 2018 grad, University of Illinois at Urbana-Champaign

Developing new tech skills has, at least for me, been a process of learning to fail. The intensive Introduction to Computer Science course I took several years ago was supposed to be fun – a benefit of being able to take college courses for almost nothing as a staff member on campus. It might have been fun for the first three weeks of the semester, but that was followed by a lot of agonizing, handwringing, and tears.

I now reflect on my time in that course as an intensive introduction to failure. This shift in mentality – learning how to fail, and how to accept it – has been key for me in being open to developing my tech skills on the job. I don’t worry so much about messing up, not knowing the answer, or the possibility of breaking my computer.

As a humanities student, it simply was never acceptable to me to turn in an assignment incomplete or “wrong.” In that computer science class, and in the information processing course I took at the iSchool at the University of Illinois a couple years later, an incomplete assignment could be a stellar attempt, proof of lessons learned, and an indication of where help is required. The rubric for good work is different for a computer science problem set than a history paper. It has been a valuable lesson to revisit as I try to develop my skills independently and in the workplace.

I have acquired and maintained my tech skills through a combination of computer science coursework before and during library school, an in-person SAA pre-conference sessions that my employer paid for, and, of course, the internet. Apps like Learn to Code with Python or free online courses can be an introduction to a programming language or a quick refresher since I inevitably forget much of what I learn in class before I can put it to work at a job. Google and Stack Exchange are lifesavers, both because I can often find the answer to my question about the mysterious error code I see in the terminal window and reassure myself that I’m not the first person to pose the question.

More than anything, my openness to what I once thought of as failure has been pivotal to my development. It can take a long time to learn and understand exactly what is going on under the hood with some new software or process, but that’s okay. Sometimes a fake-it-til-you-make-it mentality is exactly what’s needed to push yourself to tackle a new challenge. For me, learning tech skills is learning to be okay with failure as a learning process.


 

Speth-Anna_800x450Anna Speth is the Librarian for Emerging Technology and Digital Projects at Pepperdine’s Payson Library where she co-directs a makerspace and works with digital initiatives. Anna focuses on the point of connection between technology and history.  She holds a BA from Duke University and a MLIS from Simmons College.

 

ERS_jane-kellyJane Kelly is the Web Archiving Assistant for the #metoo Digital Media Collection at the Schlesinger Library on the History of Women in America and a 2018 graduate of the iSchool at the University of Illinois. Her interests lie at the intersection of digital archives and the people who use them.

Students Reflect (Part 1 of 2): Tech Skills In and Out of the Classroom

By London Stever, Hayley Wilson, and Adriana Casarez

This is the third post in the bloggERS Making Tech Skills a Strategic Priority series.

As part of our “Making Tech Skills a Strategic Priority” series, the bloggERS team asked five current and recent MLIS/MSIS students to reflect on how they have learned the technology skills necessary to tackle their careers after school. One major theme, as expressed by these three writers, is the need for a balance of learning inside and outside the classroom.

London Stever, 2018 graduate, University of Pittsburgh

Approaching the six-month anniversary of my MLIS graduation, I find myself reflecting on my technological growth. Going into graduate school, I expected little technology training. Naively, I believed that most archival jobs were paper-only, excepting occasional digitization projects. Imagine my surprise upon finding out the University of Pittsburgh required an introduction to HTML. This trend continued, as the university insisted students have balanced knowledge.

I took technology-focused courses ranging from a history of computers (useful for those expecting to work with older hardware) to an overview of open-source library repositories and learning management systems (not to be discounted by those going into academia). The most useful of these classes was the required digital humanities course. Since graduating, I have applied the practical introduction to ArchivesSpace and Archivematica – and the in-depth explanation of discoverability, access, and web crawling – to my current work at SAE International.

However, none of the information I learned in those classes would be helpful on its own. University did not prepare me for talking to the IT Department. Terminology used in archives and in IT often overlaps, but usage does not. Custom, in-house programs require troubleshooting, and university technology classes did not teach me those skills. Libraries and archives often need to work with software not specially designed for them, but the university did not address this.

Self-taught classes, YouTube videos, and outside certifications were the most useful technology education for me. Using these, I customized my education to meet the needs companies mention and my own learning needs, which focus on practical application I did not get in university. I understand troubleshooting, allowing me to use programs built fifteen years ago. Creating a blog or using a content services platform to increase discoverability and internal access is a breeze. In addition to the balanced digital to analog education of university, I also needed a balance of library and general technology education.

Hayley Wilson, current student, University of North Carolina at Chapel Hill

When registering for classes at UNC Chapel Hill prior to the Fall semester of 2017, I was informed that I was required to fulfill a technology competency requirement. I had the option to either take an at home test or take a technology course (for no credit). I decided to take the technology course because I assumed it would be beneficial to other classes I would be required to take as an MLS student.

As it turns out, as a library science student on the archives and records management track, I had a very strict set of courses I was required to take, with room for only two electives. None of these required courses were focused on technology or building technology skills. I have friends on the Information Science side of the program who are required to take numerous courses that have a strong focus on technology. Fortunately, while at SILS I have had numerous opportunities outside of the classroom to learn and build my technology skills through my various internships and graduate assistant positions. However, I don’t think that every student has the opportunity to do so in their jobs.

Adriana Cásarez, 2018 graduate, University of Texas at Austin

Entering my MSIS program with an interest in digital humanities, I expected my coursework would provide most of the expertise I needed to become a more tech-savvy researcher. Indeed, a survey course in digital humanities gave me an overview of digital tools and methodologies. Additionally, a more intense programming course for cultural data analysis taught me specialized coding for data analysis, machine learning and data visualization. The programming was challenging and using the command line was daunting, but I was fortunate to develop a network of motivated peers who also wanted to develop their technical aptitude.  

Sometimes, I felt I was learning just as many technical skills outside of my general coursework. The university library offered workshops on digital scholarship tools for the academic community. My technical skills and knowledge of trends in topics like text analysis, data curation, and metadata grew by attending as many as I could. The Digital Scholarship Librarian and I also organized co-working sessions for students working on digital scholarship projects. These sessions created a community of practice to share expertise, feedback, and support with others interested in developing their technical aptitude in a productive space. We discussed the successes and frustrations with our projects and with the technology that we were often independently teaching ourselves to use. These community meetups were invaluable avenues to learn from each other and further develop our technical capabilities.

With increased focus on digital archives, libraries and scholarship, students often feel expected to just know or to teach themselves technical skills independently. My experience in my MSIS program taught me that often others are in the same boat, experiencing similar frustrations but too embarrassed to ask for help or admit ignorance. Communities of practice are essential to create an environment where students felt comfortable discussing obstacles and developing technical skills together.


Stever-LondonLondon Stever is an archival consultant at SAE International, where she balances company culture with international and industry standards, including bridging the gap between IT and discovery partners. London graduated from the University of Pittsburgh’s MLIS – Archives program and is currently working on her CompTIA certifications. She values self-education and believes multilingualism and technological literacy are the keys to archival accessibility. Please email london.stever@outlook.com or go to londonstever.com to contact London.

IMG_0186-2

Hayley Wilson is originally from San Diego but moved to New York to attend New York University. She graduated from NYU with a BA in Art History and stayed in NYC to work for a couple of years before moving abroad to work. She then moved to North Carolina for graduate school and will be graduating in May with her master’s degree in Library Science with a concentration in Archives and Records Management.

casarez_headshotAdriana Cásarez is a recent MSIS graduate from the University of Texas at Austin. She has worked as a research assistant on a digital classics project for the Quantitative Criticism Lab. She also developed a digital collection of artistic depictions of the Aeneid using cultural heritage APIs. She aspires to work in digital scholarship and advocate for diversity and inclusivity in libraries.

More skills, less pain with Library Carpentry

By Jeffrey C. Oliver, Ph.D

This is the second post in the bloggERS Making Tech Skills a Strategic Priority series.

Remember that scene in The Matrix where Neo wakes and says “I know kung fu”? Library Carpentry is like that. Almost. Do you need to search lots of files for pieces of text and tire of using Ctrl-F? In the UNIX shell lesson you’ll learn to automate tasks and rapidly extract data from files. Are you managing datasets with not-quite-standardized data fields and formats? In the OpenRefine lesson you’ll easily wrangle data into standard formats for easier processing and de-duplication. There are also Library Carpentry lessons for Python (a popular scripting programming language), Git (a powerful version control system), SQL (a commonly used relational database interface), and many more.

But let me back up a bit.

Library Carpentry is part of the Carpentries, an organization is designed to provide training to scientists, researchers, and information professionals on the computational skills necessary for work in this age of big data.

The goals of Library Carpentry align with this series’ initial call for contributions, providing resources for those in data- or information-related fields to work “more with a shovel than with a tweezers.” Library Carpentry workshops are primarily hands-on experiences with tools to make work more efficient and less prone to mistakes when performing repeated tasks.

One of the greatest parts about a Library Carpentry workshop is that they begin at the beginning. That is, the first lesson is an Introduction to Data, which is a structured discussion and exercise session that breaks down jargon (“What is a version control system”) and sets down some best practices (naming things is hard).

Not only are the lessons designed for those working in library and information professions, but they’re also designed by “in the trenches” folks who are dealing with these data and information challenges daily. As part of the Mozilla Global Sprint, Library Carpentry ran a two-day hackathon in May 2018 where lessons were developed, revised, remixed, and made pretty darn shiny by contributors at ten different sites. For some, the hackathon itself was an opportunity to learn how to use GitHub as a collaboration tool.

Furthermore, Library Carpentry workshops are led by librarians, like the most recent workshop at the University of Arizona, where lessons were taught by our Digital Scholarship Librarian, our Geospatial Specialist, our Liaison Librarian to Anthropology (among other domains), and our Research Data Management Specialist.

Now, a Library Carpentry workshop won’t make you an expert in Python or the UNIX command line in two days. Even Neo had to practice his kung fu a bit. But workshops are designed to be inclusive and accessible, myth-busting, and – I’ll say it – fun. Don’t take my word for it, here’s a sampling of comments from our most recent workshop:

  • Loved the hands-on practice on regular expressions
  • Really great lesson – I liked the challenging exercises, they were fun! It made SQL feel fun instead of scary
  • Feels very powerful to be able to navigate files this way, quickly & in bulk.

So regardless of how you work with data, Library Carpentry has something to offer. If you’d like to host a Library Carpentry workshop, you can use our request a workshop form. You can also connect to Library Carpentry through social media, the web, or good old fashioned e-mail. And since you’re probably working with data already, you have something to offer Library Carpentry. This whole endeavor runs on the multi-faceted contributions of the community, so join us, we have cookies. And APIs. And a web scraping lesson. The terrible puns are just a bonus.

Trained in Classification, Without Classification

by Ashley Blewer

This is the first post in the bloggERS Making Tech Skills a Strategic Priority series.

Hi, SAA ERS readers! My name is Ashley Blewer, and I am sort of an archivist, sort of a developer, and sort of something else I haven’t quite figured out what to call myself. I work for a company for Artefactual Systems, and we make digital preservation and access software called Archivematica and AtoM (Access to Memory) respectively. My job title is AV Preservation Specialist, which is true, that is what I specialize in, and maybe that fulfills part of that “sort of something else I haven’t quite figured out.” I’ve held a lot of different roles in my career, as digital preservation consultant, open source software builder and promoter, developer at a big public library, archivist at a small public film archive, and other things. This, however, is my first time working for an open source technology company that makes software used by libraries, archives, museums, and other organizations in the cultural heritage sector. I think this is a rare vantage point from which to look at the field and its relationship to technology, and I think that even within this rare position, we have an even more unique culture and mentality around archives and technology that I’d like to talk about.

Within Archivematica, we have a few loosely defined types of jobs. There are systems archivists, which we speak of internally as analysts, there are developers (software engineers), and there are also systems operations folks (systems administrators and production support engineers). We have a few other roles that sit more at the executive level, but there isn’t a wall between any of these roles, as even those who are classified as being “in management” also work as analysts or systems engineers when called upon to do so. My role also sits between a lot of these loosely defined roles — I suppose I am technically classified as an analyst, and I run with the fellow analyst crew: I attend their meetings, work directly with clients, and other preservation-specific duties, but I also have software development skills, and can perform more traditionally technical tasks like writing code, changing how things function at a infrastructure level, and reviewing and testing the code that has been written by others. I’m still learning the ropes (I have been at the organization full-time for 4 months), but I am increasingly able to do some simple system administration tasks too, mostly for clients that need me to log in and check out what’s going on with their systems. This seems to be a way in which roles at my company and within the field (I hope) are naturally evolving. Another example is my brilliant colleague Ross Spencer who works as a software engineer, but has a long-established career working within the digital preservation space, so he definitely lends a hand providing crucial insight when doing “analyst-style” work.

We are a technical company, and everyone on staff has some components that are essential to a well-rounded digital preservation systems infrastructure. For example, all of us know how to use Git (a version control management system made popular by Github) and we use it as a regular part of our job, whether we are writing code or writing documentation for how to use our software. But “being technical” or having technical literacy skills involves much, much more than writing code. My fellow analysts have to do highly complex and nuanced workflow development and data mapping work, figuring out niche bugs associated with some of the microservices we run, and articulating in common human language some of the very technical parts of a large software system. I think Artefactual’s success as a company comes from the collective ability to foster a safe, warm, and collaborative environment that allows anyone on the team to get the advice or support they need to understand a technical problem, and use that knowledge to better support our software, every Archivematica user (client or non-client), and the larger digital preservation community. This is the most important part of any technical initiative or training, and it is the most fundamental component of any system.

I don’t write this as a representative for Artefactual, but as myself, a person who has held many different roles at many different institutions all with different relationships to technology, and this has by far been the most healthy and on-the-job educational experience I have had, and I think those two things go hand-in-hand. I can only hope that other organizations begin to narrow the line between “person who does archives work” and “technical person” in a way that supports collaboration and cross-training between people coming into the field with different backgrounds and experiences. We are all in this together, and the only way we are gonna get things done is if we work closely together.



Ashley works as at Artefactual Systems as their AV Preservation Specialist, primarily on the Archivematica project. She specializes in time-based media preservation, digital repository management, infrastructure/community building, computer-to-human interpretation, and teaching technical concepts. She is an active contributor to MediaArea’s MediaConch, a open source digital video file conformance checker software project, and Bay Area Video Coalition’s QCTools, an open source digitized video analysis software project. She holds Master of Library and Information Science (Archives) and Bachelor of Arts (Graphic Design) degrees from the University of South Carolina.

Call for Contributions: Making Tech Skills a Strategic Priority

As a follow-up to our popular Script It! Series — which attempted to break down barriers and demystify scripting with walkthroughs of simple scripts — we’re interested in learning more about how archival institutions (as such) encourage their archivists to develop and promote their technical literacy more generally. As Trevor Owens notes in his forthcoming book, The Theory and Craft of Digital Preservation, “the scale and inherent structures of digital information suggest working more with a shovel than with a tweezers.” Encouraging archivists to develop and promote their technical literacy is one such way to use a metaphorical shovel!

Maybe you work for an institution that explicitly encourages its employees to learn new technical skills. Maybe your team or institution has made technical literacy a strategic priority. Maybe you’ve formed a collaborative study group with your peers to learn a programming language. Whatever the case, we want to hear about it!

Writing for bloggERS! “Making Tech Skills a Strategic Priority” Series

  • We encourage visual representations: Posts can include or largely consist of comics, flowcharts, a series of memes, etc!
  • Written content should be roughly 600-800 words in length
  • Write posts for a wide audience: anyone who stewards, studies, or has an interest in digital archives and electronic records, both within and beyond SAA
  • Align with other editorial guidelines as outlined in the bloggERS! guidelines for writers.

Posts for this series will start in late November or December, so let us know if you are interested in contributing by sending an email to ers.mailer.blog@gmail.com!