My Experience Attending the Midwest Data Librarian Symposium

The Midwest Data Librarian Symposium (MDLS) is an annual conference aimed at providing Midwestern librarians, as well as others across the United States, the chance to network and discuss several industry issues and topics related to research data management. This year the event was co-hosted by the University of Cincinnati, The Ohio State University, and Miami University, as well as virtually through online Zoom conference calls and presentations. With free registration to all participants, MDLS focuses on the goal of providing low-cost networking and educational opportunities for established professionals and developing librarians of the future. Relatively new to the environment of Research Data Management, I was eager to represent FSU and the entire state of Florida at the Symposium, being the only participant in attendance at the conference from the state. While I could not travel to participate in the in-person programming, the free registration allowed me to actively engage with the virtual conference presentations and events, like many others over zoom meetings. 

Whether it was a zoom scavenger hunt or a presentation surrounding a less talked about subject, like “Making Infographics More Accessible”, I found that with each opportunity to engage I was able to learn something new and many things that I could bring back and put into practice in my own work. The presentations also left me with a lot to contemplate and consider, opening my eyes to information and concepts I had yet to broach or discover through my own work, like Digital Curation and Data Management for filmmakers and documentaries. For example, in the growing industry of filmmaking there are many times limited resources, especially for independent filmmakers, to effectively meet the costs to preserve their data. With barriers, like high memory file capacities, time constraints, and the threat of file corruption or loss of data, documentaries have a much more indirect path to successfully serve as critical sources of historical and cultural documentation. 

The vulnerability of data collected in documentaries further illustrates the broader importance to take serious measures to securely store raw data, especially with its potential relevance to guide other research. Additionally, metadata’s pertinence in other research frameworks encapsulates the expansive benefits of open science and universal accessibility. Pressures of academic viability, publishing, and performance can direct researchers’ hesitancy to relinquish ownership and control of data. This exemplifies the utility and demand to create stronger avenues to motivate the open sharing of data even when it is imperfect or incomplete. Procedurally, sharing upon request protocols have been imperfect, to say the least, as the decision to distribute that data is left at the mercy of the Primary Investigator of the original research that was conducted, who may have internal or external factors that motivate, dissuade, or even obstruct their ability to share the data in a timely or consistent manner.

While there were a variety of different topics covered during the conference, several presentations were based around the new National Institutes of Health (NIH) Data Management and Sharing (DMS) policy that will come into effect at the beginning of 2023. More specifically, there were discussions about the effects of this new policy on data management and sharing, as well as how to prepare and instruct those in need of support to navigate through these changes at a university level. For one of the main presentations on this topic the authors conducted semi-structured interviews at their university to survey the research data service needs of their constituents, as well as to gauge and collect their perspectives in relational proximity to the new governmental regulations being put into place. These interviews produced a myriad of noteworthy and interesting observations to take away. Perhaps the most surprising theme to emerge was that many of the researchers and professors were unaware of or unworried about the policy changes, believing that they’d be able to adapt their research practices and proposals when the new year began. Others wondered about how strictly the new policies would be enforced, especially with loose criteria for what might qualify submissions as exceptions and with aspects of proposals not tied to scoring to motivate researchers to put more effort into adopting practices that promote open science. Additional implications of being able to recognize and remove protected health information further supports the importance of collaboration when it comes to properly following research assurance, protocols, and proper maintenance as well as storage of data. 

These interviews revealed that many students and faculty across the country were uninformed and/or ill equipped to seamlessly handle this transitional phase that will take place in the coming months to comply with the new NIH DMS policy. Perhaps an even larger overarching takeaway that can be applied is that the general level of informational literacy is relatively low in association to student needs and the expectations that they must meet in order to perform adequately in their field. Adjustments are necessary to overcome the deficiencies in standard coursework that often operates on a foundational assumption that students will come into their academic institutions already having research skills and a working knowledge of information systems, catalogs, and databases. In most cases an established base of informational literacy is required to locate or know that library resources for these causes even exist. Libraries as well as universities more broadly must make an effort to publicly promote their services and resources more widely, while also making them more accessible to effectively address this dilemma. Without additional infrastructure to develop these skills, students have a much larger barrier to overcome the limitations embedded in the university academic framework. Taking levels of privilege into account with access to both technology and experience must also play a part in the organization of their practicum. 

As always each institution has its own individual needs as well as priorities and is equipped with different resources to be able to develop the necessary systems and resources to provide its student body with enough support to navigate through all academic challenges. Conferences typically follow a shared academic code of free exchange that open science bases itself on principle. Just look at the public accessibility of most universities’ research guides that they produce and publish and one can truly get a sense of the collaborative instruction that academic libraries strive to achieve. The symposium offers an opportunity that amplifies this ideal, allowing different institutions to come together to cooperate and exchange different ideas through dialogue with similar like-minded individuals trying to reach mutual goals. 

Preparing for the Midwest Data Librarian Symposium, my impression was that I’d simply be attending lectures where I’d experience most of the learning. However, in addition to some of the networking events and opportunities, the interconnectedness and interactive components of the entire conference made attending the symposium a much more well-balanced exchange of ideas and information. Moreover, MDLS hosted a slack channel to further promote ongoing discussions and networking, as well as archiving notes that all participants were given access to and permission to contribute as well for each presentation and event. In addition, many of the presentations that were longer than the five-minute rapid-fire “Lightning Talk” featured aspects of involvement from the audience, whether it was through discussion questions, breakout room consultations, or jam board collaborations to exchange ideas on different subjects. The integration of technology was applied seamlessly and improved the overall quality of engagement within the presentations and symposium as a whole. Attending this symposium gave me the chance to consider and discuss countless ideas to bring into practice with my own work. I am grateful for opportunities like these and experiences that enrich professionals at all stages in their careers with an academic environment of common interests and goals. 

Author Bio: Liam Wirsansky is a second-year MSI student at Florida State University and the STEM Libraries Graduate Assistant at FSU’s Dirac Library. He currently serves as the President and Artistic Director of White Mouse Theatre Productions at FSU and acts as the Director of Research and Development for the Rosenstrasse Foundation. Liam loves the academic outlet that research has provided him as well as the opportunity to educate and assist students in the development of their information literacy skills.

If you have any questions regarding the Midwest Data Librarian Symposium (MDLS), please contact the organizers at mwdatalibsym@gmail.com.

Some Helpful Resources That Were Shared at the Symposium:

STEM Data Fellow Spotlight: Diego Bustamante

For Love Data Week 2022, we are highlighting our FSU STEM Libraries Data Fellows! These posts, written by the fellows themselves, tell their stories of how they became interested in data-related work and their experience as a data fellow to this point. Today’s post is contributed by Diego Bustamante.

Prior to my role as a Data Fellow, my idea of what data is was defined by my previous work with quantitative data collected from laboratory experiments. For example, when I worked as a Research Assistant I recorded quantitative data for chemistry experiments, like mass, temperature, volume, etc. I then conducted statistical analysis on the data in order to draw conclusions from each experiment. I personally enjoy collecting and analyzing data, especially because it can lead to many scientific and technological advancements!

While searching for jobs in FSU’s NoleNetwork in summer 2021, one job title that immediately caught my attention was “FSU STEM Libraries Data Fellow.” The job description was unique amongst other jobs offered on campus. As a data fellow, I was offered the opportunity to develop several professional skills in data reference, co-hosting programming language workshops, writing and publishing blog posts, and many more. I felt like it was a great opportunity and a good fit with my previous experience and skills, and so I decided to apply. Thankfully, I was selected as one of the inaugural data fellows, leading to a journey of professional and personal development that has thus far surpassed my initial expectations. 

One of my first tasks in the program was meeting with different librarians at FSU Libraries. In these meetings I was able to learn about different methods and applications for data analysis in a variety of disciplines. For example, I learned that the Digital Humanities Librarian uses a text-mining software to find specific words from books published in the 1800s. She used the data drawn from the software to analyze certain traits of the story by counting the amount of times a character participates in an interaction of this type. This experience helped me realize that qualitative data sets can be used to draw similar conclusions about a study as quantitative data. 

Another concept that I have become familiar with while working as a Data Fellow is open data. We discussed this concept during a workshop where we talked about the potential benefits of making research data openly accessible to the wider research community. Initially, I was hesitant regarding the concept of open data, because I saw academic research as a “race” to find a solution to a given problem. However, further discussion of how researchers are compensated for sharing their data made me realize that it is possible to benefit from open data on a personal and global level. 

Currently, I am still learning about the many different types of data, its definitions, applications, and its importance. I am also working on developing an open source Canvas module on MATLAB where I explain the basics of the math based programming language in a student friendly manner. I look forward to sharing more about this work in the future!

Love Data Week: Data is for Everyone

By: Dr. Nick Ruhs

INTRODUCTION

It’s once again time for Love Data Week!  LDW is a yearly, international outreach event taking place the week of Valentine’s Day (February 14-18 this year). The week is focused on promoting good data stewardship and best practices around working with and interpreting data. LDW was started in 2015 and is currently celebrated by academic libraries and data organizations around the world. While every institution celebrates in their own way, common activities include data workshops, social media outreach, and more! 

Each year, a theme is chosen around which organizations can theme their Love Data Week activities. For 2022, the theme is “Data is for everyone.” This year, we are shining a light on the “people-side” of data, and on how different folks use and interact with data. Data often means something different to everyone, and how someone interacts with data varies based on their chosen discipline, research project, life experiences, and their own beliefs and values. There are also often inherent biases that exist in data collection, analysis, and interpretation, which can affect one’s own impression of a dataset. Despite these differences, the ability to critically evaluate data and interact with it is a universal skill that is crucial for everyone. 

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How do the Pros do Data Analysis?

By: Diego Bustamante and William-Elijah Clark

INTRODUCTION

As technology continues to evolve, the infrastructure needed to run this technology gets more and more sophisticated. Processes and tasks carried out by personal computers, smartphones, and appliances are increasingly automated and run with minimal input from the user. This is made possible through code that is developed with one or more computer programming languages.  However, with the increase in the quantity of software and programming applications, the demand for programmers and the number of languages they are required to learn has increased.  Furthermore, many employers now require skills in data analysis and computer programming as prerequisites for job applications.  In this blog post, we will discuss the most in demand languages in the market and give a brief explanation of each.  (Grand Canyon University 2020; Jiidee 2020; Meinke 2020; University of California – Berkeley, n.d.) 

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What is ‘Big Data’ Anyway?

By: Diego Bustamante and William-Elijah Clark

Maybe you’re on Twitter one day and search ‘#Statistics’ to look up some information for your Introductory Statistics course. Before you know it, you scroll through and see several tweets that are also marked with ‘#BigData’, and you’re left with more questions than you had when you started your search. Maybe you try to search for “big data” on Google, see the definition from Oxford, and are then left with even more questions: 

  • How large is “extremely large?”
  • What kind of patterns, trends, and interactions are we talking about?
  • What isn’t big data?

Big data as a term has become synonymous with the growth of digital data and the glut of information available to researchers and the public. Furthermore, there is a growing interest by both the public and private sector in utilizing large datasets to provide insight into market trends and to improve decision making. However, the exact definition of big data is sometimes unclear and can vary widely depending on who you ask. Businesses, nonprofit organizations, government agencies, and academic researchers each view big data in a different context and with different goals for its use. (University of Wisconsin Data Science, n.d.)

Above: a Google Trends graph that shows the number of searches for the term “Big Data” from 2007 to 2017

In this blog post, we aim to provide clarity and insight into the origins and definitions of big data.  We will also discuss the potential benefits and challenges surrounding big data. In doing so, we will provide some examples linking big data to applications or data that you may interact with on a daily basis.

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My Experience as a STEM Research Data Services Assistant

By: Paxton Welton

Welcome to the third post in the Get Data Lit! blog series. This post will focus on my experience working as a STEM Research Data Services Associate with FSU Libraries during the 2020-2021 school year. In this role, I assisted with outreach and education to FSU students, groups, and organizations at Florida State University around STEM research data services. 

My name is Paxton Welton and I will be graduating with a bachelor’s degree in Finance this semester. One question that you might have right from the start-why is a finance major working in a STEM-focused role? 

When applying for jobs prior to this academic year, I knew I wanted a role that would challenge me and allow me to develop new skills. I believed that being the Research Data Services Assistant would provide me the appropriate level of challenge and opportunity that I was looking for. By and large, I believe that my experience provided me with just that. There was a major learning curve that I faced when I first started this role. While I had a grasp of the basics of data literacy and research data services, I quickly realized I did not know nearly enough to be able to properly speak to student groups about these topics. During the first few weeks of the fall semester, I spent a significant portion of my time getting a stronger understanding of data and everything FSU STEM Libraries had to offer to its students in regards to research data. By reading countless articles about data literacy and engaging in weekly discussions with my supervisor Dr. Nick Ruhs, the STEM Data & Research Librarian, I became confident in my working knowledge on these topics. 

As the STEM Research Data Services Assistant, one of my main responsibilities was conducting targeted outreach to different student organizations across campus. When I first started this process I reached out specifically to STEM-focused groups. This process involved me initiating conversations via email with registered student organizations (RSOs) to introduce them  to the research data services FSU Libraries offers them.  In several cases, we were invited to meet and/or present synchronously to these groups. This gave us a chance to share more in-depth information about our services and just how valuable they are to students. It also gave students a chance to ask us any questions they may have. Getting the chance to directly interact with students and help them find the right resources to feel more prepared for their future was by far my favorite part of this role.

I also had the opportunity to contribute to data-related events hosted by FSU STEM Libraries. Two examples include Love Data Week in February and the Virtual FSU Libraries Data Services Quest in March. My involvement in these events allowed me to see the entire process of creating programming for students. I was able to sit in on brainstorming meetings, give my input on the marketing materials, and create content for the events.

One of my main focuses throughout this year has been to develop and create this blog series you are reading right now–Get Data Lit! The focus of this blog series was data literacy and its applicability to student’s educational experiences. As such, I had the chance to put into practice the new data literacy skills I learned in this role. I also had the opportunity to connect data literacy to real-world practice and explain the importance of critically evaluating data. Doing so made me realize just how important learning data skills are for my future career and education.

One thing that proved to be a common theme throughout all the work I was doing is that data is powerful and knowing how to work with it is even more powerful. From a career in law to a career in fashion, you are going to be working with data in some form. Learning how to critically evaluate data is going to give you the skills you need to stand out in the future. 

By taking on a job in a discipline that I knew very little about, I was able to challenge myself and make the most out of this past year. From getting to work on student programming events to developing a blog series, I was constantly challenged and learning something new. 

Data Literacy and COVID-19: The Importance of Understanding the Data

By: Paxton Welton and Nick Ruhs

Introduction

“Data is the sword of the 21st century. Those who wield it, the samurai.”-Jonathan Rosenberg 

Data is all around us and we often interact with it in ways we don’t even realize. From using an app to mobile order our coffee to reviewing a chart provided in an article, data surrounds us and has become so intertwined with our lives.  However, with the increasing amount of data available at our fingertips, it can be difficult to understand its meaning, accuracy, and relevance to our lives. This is the reason we decided to start this new blog series, Get Data Lit! We realize that data can be difficult to decipher and want to give you the tools to better navigate data you are faced with everyday. 

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