The word “research” is thrown around on college campuses
like a Frisbee is thrown around Library Lawn on a sunny spring day. Students
hear it in every class. It does not discriminate based on major or interests.
But what exactly is research?
This is a question I have asked multiple times over the
course of the last few weeks. With the Undergraduate Library Research Award applications open, I began wondering who can apply
and what type of research qualifies for the award. Through a bit of
investigation of my own, I’ve learned that research takes on a variety of forms
and covers many topics.
Perhaps the most important discovery I made was how many
things fall under the umbrella of research. Performing what one may consider
more traditional research (visions of hypotheses and lots of tests fill my
head) is not the only form or process for performing research. An artist
searching for new techniques or methods may speak with other artists, visit
museums or test out new materials. A dietician could study dietary patterns in
a group of people or try out new recipes. A journalist may interview various
sources or read dozens of news articles. Research does not fit inside a nice,
neat box. It reaches beyond what we may expect.
I’ve also learned that research is a conversation.
It is a dialogue between many sources, and we, as researchers, must determine
which aspects of the conversation we should digest. How do these voices work
together and help us understand the broader picture? Which voices should we
listen to and which should we question?
Not all information and sources are credible, and delving in further to
determine the truth is sometimes necessary. These are all important elements of
well-rounded research.
I never realized how much research I have actually done
during my college career, and I now realize the important role research will
play in my future. Professionals, regardless of industry, perform research
nearly every day. But what good does this research do if it just sits on your
computer?
This brings me back to the Undergraduate Library Research Award.
The OSU Library encourages students to share their research work with the world
through ULRA. Graphic designers, architects, entrepreneurs, engineers and
really anyone with a thirst for knowledge and the drive to seek out information
qualifies for this award. Students who wish to apply should submit a 750-1,000
word essay describing their research process and a finished or nearly complete
version of the research project. Participants have the opportunity to win
$1,500 for their work. Awards of $750 are also available for honorable mentions.
The OSU Library provides students with the opportunity to apply
for ULRA in hopes of inspiring and supporting research across campus. It also
provides students with dozens of resources to succeed in their research, such
as research guides, databases, subject librarians and research data services. This also includes SHAREOK, the joint institutional repository
that I discussed in my previous post.
All of this is just the tip of the iceberg. There are many
facets to research that would probably take more than a single blog post to
truly explain. My hope is that you do some research of your own and learn more
about the different types of research and why it is important. Of course, it
helps us make discoveries we otherwise would not have made, but it does more
than give us facts. It connects us to other people, other cultures and other ways
of thinking. Research broadens our horizons beyond what can be found in the
classroom. All it takes is a little motivation, commitment and curiosity.
Posted by Jenny Berry, electronic communications intern
Showing posts with label research. Show all posts
Showing posts with label research. Show all posts
Wednesday, February 13, 2019
Monday, January 28, 2019
SHAREOK Gives Access to Scholarly Work
Access to scholarly work and research is an incredibly
important aspect of any university curriculum. Luckily, the Oklahoma State
University Libraries have made accessing scholarly work easier than ever with
SHAREOK.
While the benefits to students and faculty may be evident, the benefits of SHAREOK extend beyond what we see at OSU. Professionals in every industry have access to the material. The research conducted at OSU is often publically funded, so why shouldn’t the public be able to learn from the research, too? Furthermore, peer-reviewed research has traditionally been limited by subscription-only paywalls, the costs of which have risen dramatically in the last two decades. SHAREOK provides everyone with a way to continue learning and using the information on the platform without the financial burden of paying for a subscription service.
SHAREOK is a joint institutional repository for the Oklahoma
State University Libraries, the University of Oklahoma Libraries and the
University of Central Oklahoma Max Chambers Library.
Essentially, it is a place for students and faculty to
deposit digital versions of their work. SHAREOK houses theses, dissertations,
research reports and more from some incredibly talented and brilliant people
across the state. Why is this so important? Well, the documents are all
open access, meaning they can be read by anyone, anywhere, anytime.
Because the documents on SHAREOK are all open access, this
provides students with a way to find scholarly work after they graduate. For a
student like myself who will graduate in May, this is exciting news. I
currently have access to a plethora of databases provided by the library, yet
once May rolls around, that access will no longer be available. SHAREOK allows
students like myself to transition into their postgraduate lives while
preserving one of the educational assets they had at OSU.
Juliana Nykolaiszyn, a professor in the Digital Resources
and Discovery Services department at the OSU library, is responsible for maintaining
SHAREOK at OSU.
“The whole goal is to make everything open, accessible and
free,” Juliana said. “Not only for students here at OSU, but throughout the
state of Oklahoma and worldwide.”
Students are not the only ones who benefit from this
platform. When faculty submit their work to SHAREOK, they gain another layer of
visibility in the scholarly world. Rather than just allowing it to sit on their
computers, unseen and unused, professors can submit their articles,
presentations, posters or other work to SHAREOK where anyone in the world may
now find it.
Clarke Iakovakis, an assistant professor in Research and Learning Services, works to increase the visibility of SHAREOK at OSU. He
explained some of the benefits faculty gain by submitting their work to the
repository.
“It’s this movement toward making what has been invisible more visible,” Clarke said. “There are people who are interested in really building their online scholarly profiles and sharing the work that they do. Downstream, other researchers can benefit from it, but it also can help build their profiles as researchers.”
“It’s this movement toward making what has been invisible more visible,” Clarke said. “There are people who are interested in really building their online scholarly profiles and sharing the work that they do. Downstream, other researchers can benefit from it, but it also can help build their profiles as researchers.”
While the benefits to students and faculty may be evident, the benefits of SHAREOK extend beyond what we see at OSU. Professionals in every industry have access to the material. The research conducted at OSU is often publically funded, so why shouldn’t the public be able to learn from the research, too? Furthermore, peer-reviewed research has traditionally been limited by subscription-only paywalls, the costs of which have risen dramatically in the last two decades. SHAREOK provides everyone with a way to continue learning and using the information on the platform without the financial burden of paying for a subscription service.
People around the globe can explore the information available on the platform.
They may discover something that, had they been required to purchase access,
they may never have learned. After all, knowledge is one of the greatest
treasures. Why shouldn’t we share ours with the world?
Posted by Jenny Berry, electronic communications intern
Monday, November 26, 2018
Information Overload: How Students Consume Media
Media, news, information, data, whatever you call it, we are surrounded by it every day. Yet with the changes in media culture we’ve experienced over the last several years, the ways we consume media has also changed. Especially for students.
Oklahoma State was one of 11 universities that participated in a study about students’ news consumption habits. The study was done through Project Information Literacy, a nonprofit research institute that, according to the group’s website, “conducts ongoing, national studies on what it is like being a student in the digital age.” The OSU Library had the unique opportunity to serve as the liaison between OSU and the authors of the study.
While many people, myself included, might assume that most college students obtain the news through social media, the study found that most students are “multi-modal.” This means they consume media through social media, online newspapers and discussions with peers and professors.
The report details five big takeaways from the research, including a summary of the various pathways millennials take to get the news, and how and why students share news on social media.
The findings are followed by recommendations and solutions made by journalists, librarians and educators. One of the most important and interesting solutions, in my opinion, is teaching students from an early age to read the news critically and ask questions in order to develop “mental and intellectual frameworks for credibility testing of information,” (Head, Wihbey, Metaxas, MacMillan, & Cohen, 2018).
Matt Upson, the director of undergraduate instruction and outreach services at the library, believes that teaching students to evaluate the news is crucial to their understanding of their world.
“Traditional media is often portrayed as 'fake news,' and the nature of social media often prevents us from figuring out exactly where our information is coming from,” Upson said. “It can be easy to confuse what’s misinformation and what’s true.”
He hopes that the librarians, faculty and staff at OSU can create a supportive environment where students can continue reading and digesting the news in an informed manner.
“Students are interested in news; they want to share it, to be participants, to make a difference,” he said. “How can we help them do that and be more effective and efficient users of media?”
Teaching students to critically read the news and ask questions provides them with a foundation to consume information analytically and think for themselves. It is our responsibility as consumers to engage with the news. We cannot turn a blind eye to the events around us, but we cannot blindly accept everything we read, either.
This study is incredibly important for students, journalists, educators and librarians. If you’re interested in reading more about this study, you can find the full report at www.projectinfolit.org.
Sources:
Head, A. J., Wihbey, J., Metaxas, P., MacMillan, M., & Cohen, D. (2018, October). How Students Engage with News: Five Takeaways for Educators, Journalists, and Librarians (Rep.). Retrieved http://www.projectinfolit.org/uploads/2/7/5/4/27541717/newsexecutivesummary.pdf
Posted by Jenny Berry, electronic communications intern
Oklahoma State was one of 11 universities that participated in a study about students’ news consumption habits. The study was done through Project Information Literacy, a nonprofit research institute that, according to the group’s website, “conducts ongoing, national studies on what it is like being a student in the digital age.” The OSU Library had the unique opportunity to serve as the liaison between OSU and the authors of the study.
While many people, myself included, might assume that most college students obtain the news through social media, the study found that most students are “multi-modal.” This means they consume media through social media, online newspapers and discussions with peers and professors.
The report details five big takeaways from the research, including a summary of the various pathways millennials take to get the news, and how and why students share news on social media.
The findings are followed by recommendations and solutions made by journalists, librarians and educators. One of the most important and interesting solutions, in my opinion, is teaching students from an early age to read the news critically and ask questions in order to develop “mental and intellectual frameworks for credibility testing of information,” (Head, Wihbey, Metaxas, MacMillan, & Cohen, 2018).
Matt Upson, the director of undergraduate instruction and outreach services at the library, believes that teaching students to evaluate the news is crucial to their understanding of their world.
“Traditional media is often portrayed as 'fake news,' and the nature of social media often prevents us from figuring out exactly where our information is coming from,” Upson said. “It can be easy to confuse what’s misinformation and what’s true.”
He hopes that the librarians, faculty and staff at OSU can create a supportive environment where students can continue reading and digesting the news in an informed manner.
“Students are interested in news; they want to share it, to be participants, to make a difference,” he said. “How can we help them do that and be more effective and efficient users of media?”
Teaching students to critically read the news and ask questions provides them with a foundation to consume information analytically and think for themselves. It is our responsibility as consumers to engage with the news. We cannot turn a blind eye to the events around us, but we cannot blindly accept everything we read, either.
This study is incredibly important for students, journalists, educators and librarians. If you’re interested in reading more about this study, you can find the full report at www.projectinfolit.org.
Sources:
Head, A. J., Wihbey, J., Metaxas, P., MacMillan, M., & Cohen, D. (2018, October). How Students Engage with News: Five Takeaways for Educators, Journalists, and Librarians (Rep.). Retrieved http://www.projectinfolit.org/uploads/2/7/5/4/27541717/newsexecutivesummary.pdf
Posted by Jenny Berry, electronic communications intern
Thursday, November 15, 2018
Data and Software Carpentries
What is Data Science?
Well, simply put, it is the act of collecting new and insightful ideas and methods from data sets. The modern world revolves around data, and data is an important factor in any business or organization. You have your finances, your social media interaction, your production, your employee and partner information - the list goes on. No matter where you are in life, you’re going to have to deal with data at some point. Data Science deals specifically with digital data, which is based on various systems of code that are interpreted, processed and altered by computers.
The Data and Software Carpentries are programs that are looking to teach people how to conveniently and effectively manage the data that they gather in their businesses, organizations and even research opportunities at school. The benefits are that research becomes less painful, and the techniques learned through the data carpentries lead to more research being done more effectively.
According to Phillip Doehle, the program coordinator in the Oklahoma State University High Performance Computing Center, the tagline of the Carpentries is to “help researchers get their work done with less pain and more convenience.”
Software and Data Carpentry are not the same thing, though there is much overlapping between the two and many of the same tools are used. The difference is that Data Carpentry deals with a method of organizing data in an easy and understandable way so that interpretation and analysis are more simple and convenient. A huge factor that plays into Data Carpentry is the Data Lifecycle, which consists of data collection, data organization/cleaning, data analysis and a positive production trend.
Alternatively, Software Carpentry focuses on programming skills and techniques such as software development. Coding is a big tool within this program, which is used to create a reproducible method. According to Evan Linde, a research cyberinfrastructure analyst from the OSU High Performance Computing Center, Software Carpentry can give you the introductory knowledge needed to get you out of a tight situation. For example, a graduate student struggling with a data problem can learn how to write a specific bit of code needed to link multiple processes together and solve that problem.
Now you might be thinking, “I have no experience with stuff like this, and I don’t think I’ll be able to keep up with it!” According to the official Data Carpentry website, their initial target audience is “learners with little to no computational experience.” Even if there is a bit of a learning curve, the experience and benefits gained are worth the time investment.
Software and Data Carpentries are starting points for coding and data management. The idea of the Carpentries is “Reproducible Data.” What this means is that the data can be duplicated through different means. When a data set is duplicated through different methods, then error risks are reduced, results are validated and it shows that the data can be adaptive to multiple different conditions.
While the techniques learned in the Carpentries can be very useful and informative, they don’t necessarily make you ready to immediately go out and work at a research facility. The Carpentries have a larger emphasis on the academics of research rather than an industrial emphasis. Even so, they provide a beneficial and explanatory introduction to the world of Data Science and Data Analysis. The programs are beneficial for graduate students who are getting involved in research or are interested in concepts of data science. Faculty members have told me that the knowledge they gained from the Data and Software Carpentries helped them maximize the time that they spent as a graduate student when they were working with research because their data was organized and reproducible.
The Carpentries are an informative and practical method for somebody who is looking to delve into a career based around data science, as well as students who are involved in research opportunities. They provide a foundation for understanding how to organize and interpret data, as well as how to make that data applicable within various situations. They’re an opportunity that many don’t know about, and they can potentially give somebody an extra push in understanding their career or research choice.
Posted by Braiden Ellis, student staff member, Research and Learning Services
Well, simply put, it is the act of collecting new and insightful ideas and methods from data sets. The modern world revolves around data, and data is an important factor in any business or organization. You have your finances, your social media interaction, your production, your employee and partner information - the list goes on. No matter where you are in life, you’re going to have to deal with data at some point. Data Science deals specifically with digital data, which is based on various systems of code that are interpreted, processed and altered by computers.
The Data and Software Carpentries are programs that are looking to teach people how to conveniently and effectively manage the data that they gather in their businesses, organizations and even research opportunities at school. The benefits are that research becomes less painful, and the techniques learned through the data carpentries lead to more research being done more effectively.
According to Phillip Doehle, the program coordinator in the Oklahoma State University High Performance Computing Center, the tagline of the Carpentries is to “help researchers get their work done with less pain and more convenience.”
Software and Data Carpentry are not the same thing, though there is much overlapping between the two and many of the same tools are used. The difference is that Data Carpentry deals with a method of organizing data in an easy and understandable way so that interpretation and analysis are more simple and convenient. A huge factor that plays into Data Carpentry is the Data Lifecycle, which consists of data collection, data organization/cleaning, data analysis and a positive production trend.
Alternatively, Software Carpentry focuses on programming skills and techniques such as software development. Coding is a big tool within this program, which is used to create a reproducible method. According to Evan Linde, a research cyberinfrastructure analyst from the OSU High Performance Computing Center, Software Carpentry can give you the introductory knowledge needed to get you out of a tight situation. For example, a graduate student struggling with a data problem can learn how to write a specific bit of code needed to link multiple processes together and solve that problem.
Now you might be thinking, “I have no experience with stuff like this, and I don’t think I’ll be able to keep up with it!” According to the official Data Carpentry website, their initial target audience is “learners with little to no computational experience.” Even if there is a bit of a learning curve, the experience and benefits gained are worth the time investment.
Software and Data Carpentries are starting points for coding and data management. The idea of the Carpentries is “Reproducible Data.” What this means is that the data can be duplicated through different means. When a data set is duplicated through different methods, then error risks are reduced, results are validated and it shows that the data can be adaptive to multiple different conditions.
While the techniques learned in the Carpentries can be very useful and informative, they don’t necessarily make you ready to immediately go out and work at a research facility. The Carpentries have a larger emphasis on the academics of research rather than an industrial emphasis. Even so, they provide a beneficial and explanatory introduction to the world of Data Science and Data Analysis. The programs are beneficial for graduate students who are getting involved in research or are interested in concepts of data science. Faculty members have told me that the knowledge they gained from the Data and Software Carpentries helped them maximize the time that they spent as a graduate student when they were working with research because their data was organized and reproducible.
The Carpentries are an informative and practical method for somebody who is looking to delve into a career based around data science, as well as students who are involved in research opportunities. They provide a foundation for understanding how to organize and interpret data, as well as how to make that data applicable within various situations. They’re an opportunity that many don’t know about, and they can potentially give somebody an extra push in understanding their career or research choice.
Posted by Braiden Ellis, student staff member, Research and Learning Services
Thursday, October 25, 2018
Data Culture in the Library
If I asked somebody what a data culture is, they would probably look at me with a disinterested, glazed expression, followed closely by a mumbled, “I don’t know.”
And they may not really care either.
I feel like most people tend to see the word “data” as a very scary and intimidating word, and this prevents them from learning about just how useful and informative data can really be. Most people also tend to think that data is strictly quantitative information, such as numerical statistics. However, data can be text as well (such as emails, interview notes and media reports), which is qualitative data.
When analyzed, data provides ideas and solutions to various problems and situations. This ties into data culture and the benefits it can bring to a company or organization.
A data culture is an organization that uses data to make decisions to improve themselves. Some business leaders may prefer to make decisions based on gut instinct, ignoring data because their way just “makes more sense” (at least to them it does). A data-driven organization follows the path that makes the most sense in correlation with the data, even if it doesn’t necessarily make sense from a conventional standpoint. This has proven to be far more strategic and efficient. Erik Brynjolfsson et al. al. from MIT’s Sloan School of Management conducted a study that showed data-driven organizations to have a five to six percent higher output and productivity than other systems in which organizations tend to go with what they “feel” is the best path.
The Data Culture Project provides a great method for learning how data can be useful and how to connect with others through detailed analysis. The Data Process described below is a step-by-step system from the Data Culture Project that details how to bring about a more data-oriented workplace. The OSU Library is piloting the Data Culture Project this semester and plans to offer it in the future for those who are interested.
The Data Process:
#1: Warmups
Anytime you get a group together for a team-building exercise, warmups are a great way to get things started. Quick and creative activities that help to establish a feeling of comfort and informality allow participants to be invested and confident, leading to more engagement, which leads to more results in the long run.
#2: Asking Questions
This is the first step in analyzing data. When we look at a data set, there are plenty of questions to be asked, and there are plenty of questions to be answered. Colleagues are divided into small groups to analyze a data set and develop insightful observations and questions. Now, this exercise isn’t particularly about answering any questions that are asked, but it is instead about thinking creatively to generate stimulating questions.
#3: Gathering Data
This step goes hand-in-hand with the previous step. Data is difficult to interpret sometimes, even more so when the data is wrong or unorganized. You might need to combine multiple data sets as well, because a single data set may not be able to answer every question.
#4: Analyzing Data
Oh no, here comes the hard stuff!
Not really, but this is how many people feel when it comes to analyzing data. There are many different ways to analyze data because there are many different types of data. If you’re having a hard time trying to figure out a data set, maybe you just aren’t using the right method for you! Analyzing data with colleagues leads to a combination of different ideas to maintain positive trends.
#5: Telling Your Story
This is the fun part of the process (as if you weren’t having fun before). This allows you to be creative while explaining a data set to colleagues. Various types of displays such as sketches and word webs communicate the context of the data through a narrative. This also allows abstract ideas and numbers to be represented by a concrete visual display.
#6: Try It Out
The final step is simple: just try it out! This answers many questions you may have about your developed story and the data backing it. Is the data understandable? Does the story make sense? Is it compelling? The idea of narrating your data is to influence your audience, informing and propelling them into action to improve the data.
A data-driven culture isn’t something that immediately happens, and it definitely isn’t something that has immediate results. It requires cooperation and understanding among colleagues, and the entire organization needs access to data in order to practice analyzing and interpreting it. In addition, data literacy must be encouraged so that each member of the organization can effectively contribute to improving and developing a collective network to help make important decisions.
Posted by Braiden Ellis, student staff member, Research and Learning Services
And they may not really care either.
I feel like most people tend to see the word “data” as a very scary and intimidating word, and this prevents them from learning about just how useful and informative data can really be. Most people also tend to think that data is strictly quantitative information, such as numerical statistics. However, data can be text as well (such as emails, interview notes and media reports), which is qualitative data.
When analyzed, data provides ideas and solutions to various problems and situations. This ties into data culture and the benefits it can bring to a company or organization.
A data culture is an organization that uses data to make decisions to improve themselves. Some business leaders may prefer to make decisions based on gut instinct, ignoring data because their way just “makes more sense” (at least to them it does). A data-driven organization follows the path that makes the most sense in correlation with the data, even if it doesn’t necessarily make sense from a conventional standpoint. This has proven to be far more strategic and efficient. Erik Brynjolfsson et al. al. from MIT’s Sloan School of Management conducted a study that showed data-driven organizations to have a five to six percent higher output and productivity than other systems in which organizations tend to go with what they “feel” is the best path.
The Data Culture Project provides a great method for learning how data can be useful and how to connect with others through detailed analysis. The Data Process described below is a step-by-step system from the Data Culture Project that details how to bring about a more data-oriented workplace. The OSU Library is piloting the Data Culture Project this semester and plans to offer it in the future for those who are interested.
The Data Process:
#1: Warmups
Anytime you get a group together for a team-building exercise, warmups are a great way to get things started. Quick and creative activities that help to establish a feeling of comfort and informality allow participants to be invested and confident, leading to more engagement, which leads to more results in the long run.
#2: Asking Questions
This is the first step in analyzing data. When we look at a data set, there are plenty of questions to be asked, and there are plenty of questions to be answered. Colleagues are divided into small groups to analyze a data set and develop insightful observations and questions. Now, this exercise isn’t particularly about answering any questions that are asked, but it is instead about thinking creatively to generate stimulating questions.
#3: Gathering Data
This step goes hand-in-hand with the previous step. Data is difficult to interpret sometimes, even more so when the data is wrong or unorganized. You might need to combine multiple data sets as well, because a single data set may not be able to answer every question.
#4: Analyzing Data
Oh no, here comes the hard stuff!
Not really, but this is how many people feel when it comes to analyzing data. There are many different ways to analyze data because there are many different types of data. If you’re having a hard time trying to figure out a data set, maybe you just aren’t using the right method for you! Analyzing data with colleagues leads to a combination of different ideas to maintain positive trends.
#5: Telling Your Story
This is the fun part of the process (as if you weren’t having fun before). This allows you to be creative while explaining a data set to colleagues. Various types of displays such as sketches and word webs communicate the context of the data through a narrative. This also allows abstract ideas and numbers to be represented by a concrete visual display.
#6: Try It Out
The final step is simple: just try it out! This answers many questions you may have about your developed story and the data backing it. Is the data understandable? Does the story make sense? Is it compelling? The idea of narrating your data is to influence your audience, informing and propelling them into action to improve the data.
A data-driven culture isn’t something that immediately happens, and it definitely isn’t something that has immediate results. It requires cooperation and understanding among colleagues, and the entire organization needs access to data in order to practice analyzing and interpreting it. In addition, data literacy must be encouraged so that each member of the organization can effectively contribute to improving and developing a collective network to help make important decisions.
Posted by Braiden Ellis, student staff member, Research and Learning Services
Monday, July 23, 2018
Learning about Agriculture Data and Databases
In June, I attended a conference called Driving Innovation through Data in Agriculture. It was an enjoyable and interesting experience, combining researchers and librarians onsite at the National Agricultural Library (NAL). There were several things that I brought back with me for further discussion. One of them was that I learned quite a bit about the different agriculture specific databases that the USDA manages. They are all public and provide different specialty products and can be accessed through the National Agricultural Library website. The NAL is responsible for building an integrated portfolio of knowledge products that can be used by the general public, researchers and those working in agriculture.
The Long-Term Agroecosystem Research Data Overview (LTAR) database publishes the data and information generated through the Long-Term Agroecosystem Research (LTAR) Network, a partnership of 18 research sites across the United States. They focus on building knowledge that will make agriculture sustainable and examining the environmental impacts of farming practices. The data generated is “Common Observatory Data” or CORe observational data and research data from management studies with crops and livestock. It compares current practices to experimental practices to determine the effects of the changes. Available data types from LTAR include site photographs, weather and aerial images for the research stations as well as data sets and reports published by LTAR. It has an average of 50 years of historical data. LTAR maintains the data to be sure that it is FAIR: Findable, Accessible, Interoperable and Re-usable. It is hosted at the Ag Data Commons repository and the Geospatial Platform. The Ag Data Commons is the central registry for USDA data and provides links to any data that is housed outside of the repository, including data that is first uploaded to agency sites and provides citable DOI’s for each dataset. The Geospatial Platform provides curation for GIS data but is cross referenced and linked with both Ag Data Commons and Data.gov, the government’s one stop shop for all government sponsored data.
Some of the other specialized USDA data bases include the Life Cycle Assessment Commons, USDA Food Composition Database, the i5 Workspace@NAL, which is a community specializing in arthropod genomes and research and Dr. Duke’s Phytochemical and Ethnobotanical Databases. Less specialized databases include the NAL catalog which covers the entire NAL collection, AGRICOLA, PubAg and NAL Digital Collections, which includes all the full text digitized materials of NAL.
I hope researchers, faculty and students will explore some of these. I would be interested to hear about any projects that utilize them. We here in the library are discussing the use of these specialized databases versus the more popular, general use ones. Feel free to post any examples and please, contact me or any of our friendly librarians if you need more information.
post by Kay Bjornen, Research Data Initiatives Librarian
Monday, May 21, 2018
Introducing Kay Bjornen: The New Research Data Initiatives Librarian
A Library Future Series post from February 13, 2017, highlighted the work done to establish data management services on the Oklahoma State campus. The post explained the survey and data collection process that was used to identify needs and target services that were most needed by researchers here at OSU. Since then there have been several important developments.
One of them is that I was hired to serve as a full-time data services librarian. My name is Kay Bjornen, and I joined the library as a Research Data Initiatives Librarian in February. I bring a Ph.D. in chemistry and a long career in research and data management with me. Since research support and data management are my sole responsibilities (at least for now), I have had the opportunity to knock on doors and introduce myself to many of the departments on campus that carry on data intensive research. I want to make sure that faculty and students know I am here, and I am anxious to assist with any needs they may have. If I haven’t made it to your department yet, feel free to reach out. Or just hold tight, I plan to get there as soon as possible.
One of the questions I have been asked is "Why is the library doing this?" The answer is research is changing and so are libraries. Researchers have access to a wealth of information resources and need less assistance to conduct their literature searches, chase down interlibrary loan items and answer reference questions. Information is increasingly online and digital so librarians are comfortable with electronic information sources of all kinds. It is also true that in the era of "Big Data," there are more and more challenges in managing research outputs. These include describing, storing, securing, organizing and sharing data. The library is a natural partner in these things. That’s why we are working to get the word out about the services we offer.
I am excited to be here at OSU and anxious to contribute to the research community. Do you have any questions about how the library can help you with your research? Feel free to post them here or check out the research data services we offer on the library website. My contact information is there and so is a consultation form you can fill out with the information I need to help you with your research data dilemma.
Post by Kay Bjornen, Research Data Initiatives Librarian
Monday, February 13, 2017
Data Management Research
In 2016, the Research & Learning Services department took on a campuswide research project. The goal of this project was to determine how new, tenure-track faculty manage their data. We recently spoke with Cinthya Ippoliti, Associate Dean for Research & Learning Services, about this research into data management and how to better the management process across the Oklahoma State campus.
For this research, the group interviewed 31 faculty across campus. They were pleased to receive feedback from 12 percent of those who received an invitation.
Participants were asked questions like:
- Do any of your funding sources require you to draft a management plan?
- What type of data do you generate?
- How often and how do you share your data with others?
- What happens to your data after the research project has concluded?
Once all the feedback was collected, the faculty responses were divided among RLS librarians, examined and condensed to a spreadsheet for ease of access. Upon its completion, the group met to discuss the results that surfaced during the interview process. They found that most of the participants did not have a data management plan in place and mainly stored their data on hard drives.
From this, the group discovered several needs. These included data storage solutions for smaller data sets; training on creating data management plans, file naming conventions and file organization schemas; and answers to questions about data sharing and re-purposing methods and tools.
Using a design-thinking process, the group developed ideas to better the Research Data Services program and provide data management solutions for researchers. There is now an outlet of resources for managing data and developing the skills necessary to increase impact of research findings.
The services offered by the Research Data Services are data information literacy, data storage and management support; metadata & documentation, institutional repository and data visualization; research impact, workshops and consultations.
Cinthya Ippoliti specializes in the workshops, consultations and data management plans, and Nicole Sump-Crethar works with metadata, institutional repository and data curation. Both can be contacted through Research Data Services.
Post by Jennifer Barnett, E-Communications Intern for OSU Library Communications
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