Introducing the CADRE in 5 video series

Check out the first video of “CADRE in 5,” our new series of short videos that explore CADRE in five minutes or less.

This first video, “What is CADRE?,” introduces CADRE and talks about the five pillars that structure our project’s mission: Community, Access, being Data-Centric, Reproducibility, and Empowerment.https://www.youtube.com/embed/IlgpjOvkojQ

Come back for more “CADRE in 5” videos in early spring 2022! These will include:

  • How is CADRE different from other available citation databases?
  • Who uses CADRE?
  • What is the reproducibility crisis?
  • Microsoft Academic Graph is going away—how is CADRE responding?
  • Will we add additional datasets to CADRE?

The CADRE in 5 videos will be housed in this YouTube playlist where you can access all of them in sequence.

Shape the future of CADRE! Join one of our working groups

Starting October 2021, CADRE is launching two working groups to ensure our future technical development and outreach is collaborative and community-oriented. Are you a:

  1. Current CADRE researcher,
  2. Researcher interested in using CADRE but haven’t started yet,
  3. Data librarian, or
  4. Other active CADRE stakeholder?

Then one of these working groups would be an excellent way to have your voice heard so you and your institution’s needs can actively shape the future of CADRE. The time commitment for each group is 2-3 hours per month with required every-other-month meetings. This would be a yearlong commitment. Both groups will be led by CADRE staff. Volunteer now by emailing cadre@iu.edu or read on to learn more about each working group’s scope and potential projects.

Outreach Working Group

The CADRE Outreach Working Group will oversee the development of CADRE outreach materials, as well as the promotion of awareness, understanding, and adoption of CADRE at current member institutions as well as non-member institutions. Examples of projects this group might undertake include:

  1. Running surveys on the current CADRE user community to determine use patterns, pain points, and tool needs.
  2. Identifying and reaching out to targeted researcher communities of potential new CADRE users.
  3. Determining subject matter for an CADRE FAQ Video Series.
  4. Develop communications or toolkits in collaboration with the technical working group to help educate data librarians about how CADRE works and how librarians can conduct outreach in their own campus communities (“teach the teacher” model of outreach).
  5. Develop targeted promotional campaigns that learly articulate what CADRE is, how it can be used, and why it is essential (the “value proposition”).
  6. With the Technical Working Group, identify conferences that would be a good fit for researchers to present their CADRE-related work.

Volunteer for the Outreach Working Group by emailing cadre@iu.edu .

Technical Working Group

The CADRE Technical Working Group will contribute to or lead a number of projects. Some examples of projects this group might work on:

  1. Conducting interviews with fellow researchers to determine how this community currently does their research in CADRE and how it connects to the other platforms and data each researcher uses.
  2. Advise on the creation of future technical roadmaps and revision of the current technical roadmap.
  3. With the Outreach Working Group, identify conferences that would be a good fit for researchers to present their CADRE-related work.
  4. Build a CADRE user guide, geared towards researchers, with detailed technical specifications.

Members of the technical working group need to be active CADRE researchers and preferably have experience in database management, knowledge of programming languages such as Python or R, or similar technical expertise.

Volunteer for the Technical Working Group by emailing cadre@iu.edu

Email cadre@iu.edu to volunteer or if you have any questions.

CADRE Fellows pre-print on COVID publishing

CADRE RCSC Fellows Yulia V. Sevryugina & Andrew J. Dicks have published a open pre-print of their article “Publication practices during the COVID-19 pandemic: Biomedical preprints and peer-reviewed literature” on bioRxiv. This article is about COVID-19-era publishing and the use of pre-print repositories (like bioRxiv!) to deposit cutting edge coronavirus research before it is peer reviewed. Sevryugina & Dicks used the CORD-19 dataset as well as CADRE computing tools and services to make this research possible.

Read their pre-print now!

Full Abstract

The coronavirus pandemic introduced many changes to our society, and deeply affected the established in biomedical sciences publication practices. In this article, we present a comprehensive study of the changes in scholarly publication landscape for biomedical sciences during the COVID-19 pandemic, with special emphasis on preprints posted on bioRxiv and medRxiv servers. We observe the emergence of a new category of preprint authors working in the fields of immunology, microbiology, infectious diseases, and epidemiology, who extensively used preprint platforms during the pandemic for sharing their immediate findings. The majority of these findings were works-in-progress unfitting for a prompt acceptance by refereed journals. The COVID-19 preprints that became peer-reviewed journal articles were often submitted to journals concurrently with the posting on a preprint server, and the entire publication cycle, from preprint to the online journal article, took on average 63 days. This included an expedited peer-review process of 43 days and journal’s production stage of 15 days, however there was a wide variation in publication delays between journals. Only one third of COVID-19 preprints posted during the first nine months of the pandemic appeared as peer-reviewed journal articles. These journal articles display high Altmetric Attention Scores further emphasizing a significance of COVID-19 research during 2020. This article will be relevant to editors, publishers, open science enthusiasts, and anyone interested in changes that the 2020 crisis transpired to publication practices and a culture of preprints in life sciences.

CADRE Fellow Team publishes research in Frontiers

Feb. 9, 2021
The first CADRE Fellow team has published the research they conducted using the platform in Frontiers in Research Metrics and Analysis today.

The research is called “MCAP: Mapping Collaborations and Partnerships in SDG Research,” and the team includes five fellows from Michigan State University. The team used bibliometric methods and network analysis with CADRE’s Microsoft Academic Graph dataset to study research output and collaboration supporting the the United Nations’ Sustainable Development Goals (SDGs). The researchers also perform analysis to assess collaboration beyond multiple, one-time co-authorship.

Read their work now in Frontiers and check out the package they created on CADRE, which you can reproduce in the CADRE Marketplace.

University of Toronto joins CADRE as first international partner

Dec. 1, 2020
The Collaborative Archive & Data Research Environment (CADRE) is thrilled to announce its first international partner. University of Toronto Libraries, which is the largest academic library system in Canada, will join ten Big Ten Academic Alliance (BTAA) libraries supporting the project.

Logo that reads: University of Toronto Libraries.

The BTAA and the Indiana University Network Science Institute serve as major partners on CADRE, led by Indiana University Libraries.

Researchers at University of Toronto Libraries were introduced to CADRE through the project’s three-month, free trial period. The trial gives a university’s researchers access to CADRE’s high-quality, standardized version of the Web of Science through their institutional access to the dataset. The opportunity to trial CADRE is crucial to better understand the platform’s value before committing to the project.

Marcel Fortin, the Head of the Map and Data Library and Advisor on Data Science and Digital Research at University of Toronto Libraries, says CADRE will give the institution’s researchers important data access and data-mining tools.

“Providing CADRE’s standardized text- and data-mining services for big datasets to our researchers will expand on the world-class resources already available to our community through the University of Toronto Libraries,” Fortin said. “We were excited about the opportunity to trial CADRE, which allowed us to take advantage of the platform while evaluating its value to our researchers.”

University of Toronto researchers access CADRE’s proprietary tier of service, which includes features and datasets recently upgraded in CADRE’s beta launch.

Strengthening the CADRE Community

The latest partnership strengthens CADRE’s sustainability and affordability and spreads its mission beyond one academic consortium and across borders as demand grows for a service like CADRE. Academic libraries increasingly face the same obstacles: it is too costly and requires resources libraries do not have to clean and host big bibliometric datasets or offer a viable data-mining interface to researchers.

CADRE helps libraries overcome these barriers by pooling resources across institutions to build a cloud-based infrastructure for hosting big data and create a user-friendly interface that empowers researchers to perform big data analytics.

“As subscribers of Web of Science XML data, we realized CADRE had done all the heavy lifting of creating an environment that would allow for easy querying and analyzing of the data,” Fortin said. “Additionally, coming onboard as a CADRE partner opened the door to more extensive research collaboration with our new Big Ten partners.”

CADRE’s success relies on the users who contribute to it. A growing community of partner institutions lowers costs for everyone while raising the bar for quality through shared resources and contributions.

The list of CADRE’s other BTAA library partners includes:

  • Michigan State University Libraries
  • Ohio State University Libraries
  • Penn State University Libraries
  • Purdue University Libraries
  • Rutgers University Libraries
  • University of Iowa Libraries
  • University of Maryland Libraries
  • University of Michigan Libraries
  • University of Minnesota Libraries

Interested in a trial or becoming a partner? You can request a trial or contact us.

About CADRE

CADRE addresses a critical emergent issue faced by academic libraries: providing sustainable, affordable, and standardized text- and data-mining services for licensed big datasets, as well as open and non-consumptive datasets too large or unwieldy to work with in existing research library environments. By sharing costs across a large number of academic libraries, CADRE will create a cloud-based solution for making these data available to its member institutions–with appropriate security, stewardship, and storage–at a fraction of what it would cost them to do alone.

This project is funded with IMLS award LG-70-18-0202 and is additionally supported by a unique group of cross-industry partners. CADRE’s core leadership team includes CADRE Director Jaci Wilkinson (Indiana University Libraries) and CADRE Co-Directors Jamie V. Wittenberg (University of Colorado Boulder), Patricia L. Mabry (HealthPartners Institute), Valentin Pentchev (Indiana University Network Science Institute), Xiaoran Yan (Indiana University Network Science Institute), and Robert Van Rennes (Big Ten Academic Alliance).

CADRE Publishes Article in Frontiers in Big Data

Nov. 20, 2020
The Collaborative Archive & Data Research Environment (CADRE) today published a paper in Frontiers in Big Data.

The article, called “CADRE: A Collaborative, Cloud-Based Solution for Big Bibliographic Data Research in Academic Libraries,” describes how CADRE helps libraries overcome the significant monetary and technical challenges of hosting big bibliographic datasets and empowers researchers to work with such data.

Illustration. An image of a five-pillar structure with the words: Community, Access, Data-Centric, Reproducibility, and Empowerment written across each pillar.

The authors discuss CADRE’s cloud-based solution through the five pillars the project is built upon:

  • Community: a community of libraries and industry partners who support and maintain the platform and a community of researchers who use it
  • Access: the sharing platform should be accessible and affordable to both proprietary data customers and the general public
  • Data-Centric: the platform is optimized for efficient and high-quality bibliographic data services, satisfying diverse data needs
  • Reproducibility: the platform should be designed to foster and encourage reproducible research
  • Empowerment: the platform should empower researchers to perform big data analytics on the hosted datasets

Read the article in Frontiers in Big Data.

CADRE executes beta launch, invites institutions to trial platform

Oct. 21, 2020
The Collaborative Archive & Data Research Environment (CADRE) began rolling out the beta version of its platform today and invites institutions to access CADRE through a free trial period. Users will have full access to all aspects of the release by Friday, Oct. 23.

Illustration. The CADRE logo: a blue owl.

CADRE’s cloud-based platform provides sustainable, affordable, and standardized text- and data-mining services for licensed big datasets, as well as open and non-consumptive datasets too large or unwieldy to work with in existing research library environments. CADRE is currently seeded with the Web of Science (paid tier), Microsoft Academic Graph, and U.S. Patent and Trademark Office data (available in raw format or in a relational database).

CADRE is led by Indiana University Libraries, in partnership with the Indiana University Network Science Institute and the Big Ten Academic Alliance, and supported by a grant from the Institute of Museum and Library Sciences.

Features of beta release

CADRE’s Beta Release (1.0.0-Beta) provides a stable version of the platform with new and updated functionality, including:

  • Publication and sharing functionality: publish and share packages, tools, and data archives with other users in the Marketplace
  • Graph query engine: access data through a graph database with simplified access to query results and an improved “Job Status” page; take advantage of CADRE’s high-quality, standardized version of the most recent Web of Science data (covering 1900 through 2019) and Microsoft Academic Graph (February 14, 2020 release)
  • User profiles: create a profile you can return to each time you log in; users can now expect their data to persist through the beta launch and all future versions of the platform
  • User interface enhancements: find extensive accessibility and user experience updates throughout the platform
  • User analytics: administrators can receive comprehensive reports on institutional usage of CADRE
  • Bug fixes

In addition to these updates, CADRE now offers a three-month, no-cost trial period for institutions interested in trying the platform. Trial users will access the latest features and CADRE’s version of the Web of Science if the users already have institutional access to the dataset.

We will provide a walkthrough of the changes accompanying the beta launch and more information on how to take part in a CADRE trial in a brief tour on Oct. 26 at 2 p.m. ET. Register now to attend.

Anyone is still welcome to use CADRE and access the open Microsoft Academic Graph dataset, while our sponsoring partners can access the Web of Science dataset. Start working on the newest version of CADRE today.

CADRE Partnerships

This project is funded with IMLS award LG-70-18-0202 and is additionally supported by a unique group of cross-industry partners. CADRE’s core leadership team includes CADRE Director Jaci Wilkinson (Indiana University Libraries) and CADRE Co-Directors Jamie V. Wittenberg (University of Colorado Boulder), Patricia L. Mabry (HealthPartners Institute), Valentin Pentchev (Indiana University Network Science Institute), Xiaoran Yan (Indiana University Network Science Institute), and Robert Van Rennes (Big Ten Academic Alliance).

CADRE partner institutions include:

  • Midwest Big Data Hub
  • South Big Data Hub
  • West Big Data Hub
  • Microsoft Research
  • Web of Science Group
  • Michigan State University Libraries
  • Ohio State University Libraries
  • Penn State University Libraries
  • Purdue University Libraries
  • Rutgers University Libraries
  • University of Iowa Libraries
  • University of Maryland Libraries
  • University of Michigan Libraries
  • University of Minnesota Libraries

Contact:

Stephanie Hernandez McGavin
Email: s m c g a v i n @ i u . e d u

UMD Libraries Expands Researchers’ Access to Big Data

July 14, 2020
University of Maryland Libraries is now among 10 Big Ten Academic Alliance libraries to join the Collaborative Archive & Data Research Environment (CADRE), which provides researchers access to secure, high-quality data on academic research, publication trends and patents in all knowledge domains.

Maryland-affiliated researchers will now be able to use CADRE’s highest level of data- and text-mining services for major datasets such as Web of Science, Microsoft Academic Graph and U.S. Patent and Trademark Office data.

“Improving our data services and curation for the University of Maryland community features heavily in our new strategic plan,” said Adriene Lim, dean of University Libraries. “In our initiatives aimed at improving the Libraries’ ability to meet researchers’ data needs, joining CADRE and leveraging the collective wisdom and work of BTAA colleagues and supporting existing technological solutions are logical and effective next steps.”

Joining CADRE’s founding community of academic libraries allows Maryland to share the costs associated with providing text- and data-mining services for big datasets to UMD researchers.

“At its core, CADRE is a community effort to solve the expensive problem of making big data accessible to researchers. Without collaboration, there is no CADRE,” said CADRE Project Co-Director Jamie Wittenberg. “We are thrilled to welcome the University of Maryland on board and look forward to working with Maryland researchers and librarians to advance our development and improve our service offerings.”

Source: Maryland Today

University of Maryland Libraries joins CADRE as the 10th BTAA partner-institution

June 3, 2020
The Collaborative Archive & Data Research Environment (CADRE) is excited to announce today that the University of Maryland Libraries is joining the esteemed cohort of library partners supporting the CADRE project.

Maryland will join nine other Big Ten Academic Alliance (BTAA) libraries to support CADRE. These libraries also help shape CADRE through their researchers who use the platform: The CADRE team utilizes user stories, such as researchers’ requests for certain functionality or technical support, to inform CADRE’s design.

The BTAA, along with the Indiana University Network Science Institute, serve as major partners on CADRE, led by Indiana University Libraries.

All Maryland-affiliated researchers will now be able to access CADRE’s proprietary tier of service, which includes access to CADRE’s innovative features and to the Web of Science and Microsoft Academic Graph datasets. Even more, the university will join the founding community of academic libraries that are pooling resources to build the premier solution for standardized text- and data-mining of big bibliometric datasets.

“Improving our data services and curation for the University of Maryland community features heavily in our new strategic plan,” said Adriene Lim, Dean of University Libraries. “In our initiatives aimed at improving the Libraries’ ability to meet researchers’ data needs, joining CADRE and leveraging the collective wisdom and work of BTAA colleagues and supporting existing technological solutions are logical and effective next steps.”

Associate Dean of Libraries Daniel Mack agreed, stating, “CADRE will be a valuable tool to help us make informed decisions about subscriptions, partnerships, open access, and other collections issues.”

The list of CADRE’s other BTAA library partners includes:

  • Michigan State University Libraries
  • Ohio State University Libraries
  • Penn State University Libraries
  • Purdue University Libraries
  • Rutgers University Libraries
  • University of Iowa Libraries
  • University of Michigan Libraries
  • University of Minnesota Libraries
A shared infrastructure

Now, more than ever, it is critical for academic libraries to assess how to provide librarians and researchers with standardized text- and data-mining services for licensed and open big datasets at lower costs. CADRE was created to be an affordable, sustainable solution for libraries that cannot afford to purchase big bibliometric datasets, or build the infrastructure and provide the services necessary to host such data, on their own.

Not only does each new partner on the CADRE project contribute resources to grow its shared infrastructure, but each partner also lowers costs for everyone and strengthens CADRE’s commitment to building a collaborative, community-oriented platform.

“At its core, CADRE is a community effort to solve the expensive problem of making big data accessible to researchers. Without collaboration, there is no CADRE,” said CADRE Project Director Jamie Wittenberg. “We are thrilled to welcome the University of Maryland on board and look forward to working with Maryland researchers and librarians to advance our development and improve our service offerings.”

Please contact the CADRE team if you are interested in working with or partnering with CADRE.

You can also access CADRE’s free tier of service, which includes Microsoft Academic Graph, during the alpha phase here: https://cadre.iu.edu/about-cadre/get-started

About CADRE

CADRE addresses a critical emergent issue faced by academic libraries: providing sustainable, affordable, and standardized text- and data-mining services for licensed big datasets, as well as open and non-consumptive datasets too large or unwieldy to work with in existing research library environments. By sharing costs across a large number of academic libraries, CADRE will create a cloud-based solution for making these data available to its member institutions–with appropriate security, stewardship, and storage–at a fraction of what it would cost them to do alone.

This project is led by Indiana University Libraries, in partnership with the Indiana University Network Science Institute and the Big Ten Academic Alliance. CADRE is funded with IMLS award LG-70-18-0202 and is additionally supported by a unique group of cross-industry partners, including:

  • Midwest Big Data Hub
  • South Big Data Hub
  • West Big Data Hub
  • Microsoft Research
  • Web of Science Group
  • Michigan State University Libraries
  • Ohio State University Libraries
  • Penn State University Libraries
  • Purdue University Libraries
  • Rutgers University Libraries
  • University of Iowa Libraries
  • University of Maryland Libraries
  • University of Michigan Libraries
  • University of Minnesota Libraries

IU-based science gateway enables key COVID-19 research using big data

May 15, 2020
The Collaborative Archive and Data Research Environment was established to make an impact on big data research. In 2020, it’s now making an impact on the COVID-19 fight through a new fellowship program to facilitate COVID-19 research.

Led by IU Libraries in collaboration with the IU Network Science Institute (IUNI) and the Big Ten Alliance, CADRE offers access to huge datasets such as those from Web of Science and the U.S. Patent and Trademark Office as well as support and resources to take full advantage of working with such massive datasets.

As COVID-19 began its spread through the United States, CADRE answered a call to action from the White House Office of Science and Technology Policy. The call challenged researchers to help scientists answer high-priority questions using the COVID-19 Open Research Dataset, a resource encompassing tens of thousands of scholarly articles about COVID-19, SARS-CoV-2, and related coronaviruses.

CADRE’s response was to create the Research Cohort for the Study of Coronaviruses fellowship program to give any researcher studying the pandemic an opportunity to take advantage of CADRE’s expertise and services.

“The CADRE project is in a position to be able to help the scientific community, and we wanted to ensure that those resources were made available,” said Jamie Wittenberg, CADRE project director and head of scholarly communication at IU Libraries. “Our fellows will receive a ‘special tier’ of service including dataset access, hands-on support from our technical team and research scientists, and an opportunity to present their work to others.”

The CADRE group quickly granted fellowships to four research teams:

  • Filipi Nascimento Silva, a research scientist at IUNI, and Diego Raphael Amancio, associate professor of computer science at University of São Paulo, will help researchers keep up with the rapidly growing number of COVID-19 studies being released. They will use automated methods to summarize and provide overviews of COVID-19 studies that will allow researchers to assess the relevance of new work to their own research.
  • Sadamori Kojaku, a postdoctoral fellow at the Luddy School of Informatics, Computing, and Engineering at IU Bloomington, is working with others to create a research map of papers about COVID-19 and compare that map with similar maps for other diseases such as SARS and influenza. The comparison will reveal unexplored COVID-19 research areas and concentrations of research activities, and the map will keep incorporating new papers to keep track of expanding research.
  • A third research team will study the dynamics of collaboration and team formation among COVID-19 research groups. Caroline Wagner and Xiaojing Cai of Ohio State University, Caroline Fry of University of Hawaii at Manoa, and Yi Zhang of University of Technology Sydney, Australia, will be looking for key patterns in communication and collaboration among the many international research collaborations that have emerged during the pandemic.
  • Yulia Sevryugina, University of Michigan, is evaluating the research quality of COVID-19 work. At a time when coronavirus research is being disseminated so rapidly, some studies may lack of scientific rigor and be more likely to have errors. Sevryugina will use CADRE’s datasets to identify signs of lower quality such as incoherent writing, stylistic errors, plagiarism, speculative language, unreproducible experiments, and far-fetched conclusions based on poor quality data.

More information about CADRE and its services is available on their website.

Source: IU Research Impact