Category Archives: Open Data

Change is coming – are you open to it?

This blog post is a collaboration between Paolo Mangiafico from ScholarWorks and Sophia Lafferty-Hess from the Center for Data and Visualization Sciences and the Duke Research Data Repository.

Open access journals have been around forOpen sign several decades, and almost all researchers have read them or published in them by now. Perhaps less well known are trends toward more openness in sharing of data, methods, code, and other aspects of research – broadly called open scholarship. There are lots of good reasons to make your research outputs as open as possible, and increasing support at Duke for doing it.

There are many different variants of “open” – including goals of making research accessible to all, making data and methods transparent to increase reproducibility and trust, licensing research to enable broad re-use, and engagement with a variety of stakeholders, among other things. All of these provide benefits to the public and they also provide benefits to Duke researchers. There’s growing evidence that openly available publications and data result in more citations and greater impact (Colavizza 2020), and showing one’s work and making it available for replication helps build greater trust. There’s greater potential economic impact when others can build on research more quickly, and more avenues for collaboration and interdisciplinary engagement.

Recognizing the importance of making research outputs quickly and openly available to other researchers and the public, and supporting greater transparency in research, many funding agencies are now encouraging or requiring it. NIH has had a public access policy for over a decade, and NSF and other agencies have followed with similar policies. NIH has also released a new Data Management and Sharing policy that goes into effect in 2023 with more robust and clearer expectations for how to effectively share data. In Europe, government research funders back a program called Plan S, and in the United States, the recently passed U.S. Innovation and Competition Act (S. 1260) includes provisions that instruct federal agencies to provide free online public access to federally-funded research “not later than 12 months after publication in peer-reviewed journals, preferably sooner.”

The USICA bill aims to maximize the impact of federally-funded research by ensuring that final author manuscripts reporting on taxpayer-funded research are:

  • Deposited into federally designated or maintained repositories;
  • Made available in open and machine-readable formats; 
  • Made available under licenses that enable productive reuse and computational analysis; and
  • Housed in repositories that ensure interoperability and long-term preservation.

Duke got a head start on supporting researchers in making their publications open access in 2010, when Academic Council adopted an open access policy, which since then has been part of the Faculty Handbook (Appendix P). The policy provides the legal basis for Duke faculty to make their own research articles openly available on a personal or institutional website via a non-exclusive license, while also making it possible to comply with any requirements imposed by their journal or funder. Shortly after the policy was adopted, Duke Libraries worked with the Provost’s office to implement a service making open access easy for Duke researchers. DukeSpace, a repository integrated with the Scholars@Duke profile system, allows you to add a publication to your profile and deposit it to Duke’s open access archive in a single step, and have the open access link included in your citations alongside the link to the published version.

Duke Libraries also support a research data repository and services to help the Duke community organize, describe, and archive their research data for open access. This service, with support from the Provost’s office, provides both the infrastructure and curation staff to help Duke researchers make their data FAIR (Findable, Accessible, Interoperable, and Reusable). By publishing datasets with digital object identifiers (DOIs) and data citations, we create a value chain where making data available increases their impact and positions them as standalone research objects. The importance of data sharing specifically is also being formalized at Duke through the current Research Data Policy Initiative, which has a stated mission to “facilitate efficient and quality research, ensure data quality, and foster a culture of data sharing.” Together the Duke community is working to develop services, processes, procedures, and policies that broaden our contributions to society through public access to the outputs of our research.

Are you ready to make your work open? You can find more information about how to deposit your publications and data for open access at Duke on the ScholarWorks website, and consultants from Duke Libraries’ ScholarWorks Center for Scholarly Publishing and Center for Data and Visualization Sciences are available to help you find the best place to make your work open access, choose an appropriate license, and track how it’s being used.

Share More Data in the Duke Research Data Repository!

We are happy to announce expanded features for the public sharing of large scale data in the Duke Research Data Repository! The importance of open science for the public good is more relevant than ever and scientific research is increasingly happening at scale. Relatedly, journals and funding agencies are requiring researchers to share the data produced during the course of their research (for instance see the newly released NIH Data Management and Sharing Policy). In response to this growing and evolving data sharing landscape, the Duke Research Data Repository team has partnered with Research Computing and OIT to integrate the Globus file transfer system to streamline the public sharing of large scale data generated at Duke. The new RDR features include:

  • A streamlined workflow for depositing large scale data to the repository
  • An integrated process for downloading large scale data (datasets over 2GB) from the repository
  • New options for exporting smaller datasets directly through your browser
  • New support for describing and using collections to highlight groups of datasets generated by a project or group (see this example)
  • Additional free storage (up to 100 GB per deposit) to the Duke community during 2021!

While using Globus for both upload and download requires a few configuration steps by end users, we have strived to simplify this process with new user documentation and video walk-throughs. This is the perfect time to share those large(r) datasets (although smaller datasets are also welcome!).

Contact us today with questions or get started with a deposit!

Publish Your Data: Researcher Highlight

This post was authored by Shadae Gatlin, DUL Repository Services Analyst and member of the Research Data Curation Team.

Collaborating for openness

The Duke University Libraries’ Research Data Curation team has the privilege to collaborate with exceptional researchers and scholars who are advancing their fields through open data sharing in the Duke Research Data Repository (RDR). One such researcher, Martin Fischer, Ph.D., Associate Research Professor in the Departments of Chemistry and Physics, recently discussed his thoughts on open data sharing with us. A trained physicist, Dr. Fischer describes himself as an “optics person” his work ranges from developing microscopes that can examine melanin in tissues to looking at pigment distribution in artwork. He has published data in the RDR on more than one occasion and says of the data deposit process that, “I can only say, it was a breeze.”

“I can only say, it was a breeze.”

Dr. Fischer recalls his first time working with the team as being “much easier than I thought it was going to be.” When Dr. Fischer and colleagues experienced obstacles trying to setup OMERO, a server to host their project data, they turned to the Duke Research Data Repository as a possible solution to storing the data. This was Dr. Fischer’s first foray into open data publishing, and he characterizes the team as being  responsive and easy to work with. Due to the large size of the data, the team even offered to pick up the hard drive from Fischer’s office. After they acquired the data, the team curated, archived, and then published it, resulting in Fischer’s first dataset in the RDR.

Why share data?

When asked why he believes open data sharing is important, Dr. Fischer says that “sharing data creates an opportunity for others to help develop things with you.” For example, after sharing his latest dataset  which evaluates the efficacy of masks to reduce the transmission of respiratory droplets, Fischer received requests for a non-proprietary option for data analysis instead of using the team’s data analysis scripts written for the commercial program Mathematica. Peers offered to help develop a Python script, which is now openly available, and for which the developers used the RDR data as a reference. As of January 2021, the dataset has had 991 page views.

Dr. Fischer appreciates the opportunity for research development that open data sharing creates, saying, “Maybe somebody else will develop a routine, or develop something that is better, easier than what we have”. Datasets deposited in the RDR are made publicly available for download and receive a permanent DOI link, which makes the data even more accessible.

“Maybe somebody else will develop a routine, or develop something that is better, easier than what we have.”

In addition to the benefits of long-term preservation and access that publishing data in the RDR provides, Dr. Fischer finds that sharing his data openly encourages a sense of accountability. “I don’t have a problem with other people going in and trying, and making sure it’s actually right. I welcome the opportunity for feedback”. With many research funding agencies introducing policies for research data management and data sharing practices, the RDR is a great option for Duke researchers. Every dataset that is accepted into the RDR is carefully curated to meet FAIR guidelines and optimized for future reuse.

Collaborating with researchers like Dr. Martin Fischer is one of the highlights of working on the Research Data Curation team. We look forward to seeing what fascinating data 2021 will bring to the RDR and working with more Duke researchers to share their data with the world.

Dr. Fischer’s Work in the Duke Research Data Repository:

  • Wilson, J. W., Degan, S., Gainey, C. S., Mitropoulos, T., Simpson, M. J., Zhang, J. Y., & Warren, W. S. (2019). Data from: In vivo pump-probe and multiphoton fluorescence microscopy of melanoma and pigmented lesions in a mouse model. Duke Digital Repository. https://doi.org/10.7924/r4cc0zp95
  • Fischer, E., Fischer, M., Grass, D., Henrion, I., Warren, W., Westman, E. (2020). Video data files from: Low-cost measurement of facemask efficacy for filtering expelled droplets during speech. Duke Research Data Repository. V2 https://doi.org/10.7924/r4ww7dx6q

Got Data? Data Publishing Services at Duke Continue During COVID-19

While the library may be physically closed, the Duke Research Data Repository (RDR) is open and accepting data deposits. If you have a data sharing requirement you need to meet for a journal publisher or funding agency we’ve got you covered. If you have COVID-19 data that can be openly shared, we can help make these vital research materials available to the public and the research community today. Or if you have data that needs to be under access restrictions, we can connect you to partner disciplinary repositories that support clinical trials data, social science data, or qualitative data.

Speaking of the RDR, we just completed a refresh on the platform and added several features!

In-line with data sharing standards, we also assign a digital object identifier (DOI) to all datasets, provide structured metadata for discovery, curate data to further enhance datasets for reuse and reproducibility, provide safe archival storage, and a standardized citation for proper acknowledgement.

Openness supports the acceleration of science and the generation of knowledge. Within the libraries we look forward to partnering with Duke researchers to disseminate their research data! Visit https://research.repository.duke.edu/ to learn more or contact datamanagement@duke.edu with any questions.

Duke University Libraries Partners with the Qualitative Data Repository

Duke University Libraries has partnered with the Qualitative Data Repository (QDR) as an institutional member to provide qualitative data sharing, curation, and preservation services to the Duke community. QDR is located at Syracuse University and has staff and infrastructure in place to specifically address some of the unique needs of qualitative data including curating data for future reuse, providing mediated access, and assisting with Data Use Agreements.

Duke University Libraries has long been committed to helping our scholars make their research openly accessible and stewarding these materials for the future. Over the past few years, this has included launching a new data repository and curation program, which accepts data from any discipline as well as joining the Data Curation Network. Now through our partnership with QDR we can further enhance our support for sharing and archiving qualitative data.

Qualitative data come in a variety of forms including interviews, focus groups, archival materials, textual documents, observational data, and some surveys. QDR can help Duke researchers have a broader impact through making these unique data more widely accessible.

“Founded and directed by qualitative researchers, QDR is dedicated to helping researchers share their qualitative data,” says Sebastian Karcher, QDR’s associate director. “Informed by our deep understanding of qualitative research, we help researchers share their data in ways that reflect both their ethical commitments and do justice to the richness and diversity of qualitative research. We couldn’t be more excited to continue our already fruitful partnership with Duke University Libraries”

Through this partnership, Duke University Libraries will have representation on the governance board of QDR and be involved in the latest developments in managing and sharing qualitative data. The libraries will also be partnering with QDR to provide virtual workshops in the spring semester at Duke to enhance understanding around the sharing and management of qualitative research data.

If you are interested in learning more about this partnership, contact datamanagement@duke.edu.

Introducing Duke Libraries Center for Data and Visualization Sciences

As data driven research has grown at Duke, Data and Visualization Services receives an increasing number of requests for partnerships, instruction, and consultations. These requests have deepened our relationships with researchers across campus such that we now regularly interact with researchers in all of Duke’s schools, disciplines, and interdepartmental initiatives.

In order to expand the Libraries commitment to partnering with researchers on data driven research at Duke, Duke University Libraries is elevating the Data and Visualization Services department to the Center for Data and Visualization Sciences (CDVS). The change is designed to enable the new Center to:

  • Expand partnerships for research and teaching
  • Augment the ability of the department to partner on grant, development, and funding opportunities
  • Develop new opportunities for research, teaching, and collections – especially in the areas of data science, data visualization, and GIS/mapping research
  • Recognize the breadth and demand for the Libraries expertise in data driven research support
  • Enhance the role of CDVS activities within Bostock Libraries’ Edge Research Commons

We believe that the new Center for Data and Visualization Sciences will enable us to partner with an increasingly large and diverse range of data research interests at Duke and beyond through funded projects and co-curricular initiatives at Duke. We look forward to working with you on your next data driven project!

OSF@Duke: By the Numbers and Beyond

The Open Science Framework (OSF) is a data and project management platform developed by the Center for Open Science that is designed to support the entire research lifecycle. OSF has a variety of features including file management and versioning, integration with third-party tools, granular permissions and sharing capabilities, and communication functionalities. It also supports growing scholarly communication formats including preprints and preregistrations, which enable more open and reproducible research practices.

In early 2017, Duke University became a partner institution with the OSF. As a partner institution, Duke researchers can sign into the OSF using their NetID and affiliate a project with Duke, which allows it to be displayed on the Duke OSF page. After 2 years of supporting OSF for Institutions here at Duke, the Research Data Management (RDM) team wanted to gain a better perspective surrounding how our community was using the tool and their perceptions. 

As of March 10, 2019, Duke has 202 users that have signed into the system using their Duke credentials (and there are possibly more users that are authenticating using personal email accounts). Of these users, 177 total projects have been created and affiliated with Duke. Forty-six of these projects are public and 132 remain private. Duke users have also registered 80 Duke affiliated projects, 62 of which are public and 18 are embargoed. A registration is a time-stamped read-only copy of an OSF project that can be used to preregister a research design, to create registered reports for journals, or at the conclusion of a project to formally record the authoritative copy of materials.

But what do OSF users think of the tool and how are they using it within their workflows? A few power users shared their thoughts:

Optimizing research workflows: A number of researchers noted how the OSF has helped streamline their workflows through creating a “central place that everyone has access to.” OSF has helped “keeping track of the ‘right’ version of things” and “bypassing the situation of having different versioned documents in different places.” Additionally, the OSF has supported “documenting workflow pipelines.”

Facilitating collaboration: One of the key features of the OSF is that researchers, regardless of institutional affiliation, can contribute to a project and integrate the tools they already use. Matt Makel, Director of Research at TIP, explains how OSF supports his research – “I collaborate with many colleagues at other institutions. OSF solves the problem of negotiating which tools to use to share documents. Rather than switching platforms across (or worse, within) projects, OSF is a great hub for our productivity.”

Offering an end-to-end data management solution: Some research groups are also using OSF in multiple stages of their projects and for multiple purposes. As one researcher expressed – “My research group uses OSF for every project. That includes preregistration and archiving research materials, data, data management and analysis syntax, and supplemental materials associated with publications. We also use it to post preprints to PsyArXiv.”

It also surfaced that OSF supported an ideological perception regarding a shift in the norms of scholarly communication. As Elika Bergelson, Crandall Family Assistant Professor in Psychology and Neuroscience, aptly put it “Open science is the way of the future.” Here within Duke University Libraries, we aim to continue to support these shifting norms and the growing benefits of openness through services, platforms, and training.

To learn more about how the OSF might support your research, join us on April 3 from 10-11 am for hands-on OSF workshop. Register here: https://duke.libcal.com/event/4803444

If you have other questions about using the OSF in a project, the RDM team is available for consultations or targeted demonstrations or trainings for research teams. We also have an OSF project that can help you understand the basic features of the tool.

Contact askdata@duke.edu to learn more or request an OSF demonstration.

ArcGIS Open Data

What is Open Data?

Finding data can be challenging.  Organizations and government agencies can share their data with the public using ESRI’s ArcGIS Open Data, a centralized spatial data clearinghouse.  Since its inception last year, over 1,600 organizations have provided more than 22,000 open datasets to the public.  Open Data allows users to find and download data in different formats, including shapefiles, spreadsheets, and KML documents, as well as APIs (GeoJSON or Esri GeoServices) to call the data into your own application.  It also lets you create various types of charts.

Search_Open_Data

How to Find and Use Data

Open Data allows consumers to type in a geographic area or a topic of interest in a single search box.  Once you’ve found data that appears to be what you were looking for, you can use the data for GIS purposes or use a table to create charts and graphs.  If you are looking for GIS data, you can preview the spatial data before downloading by clicking the “Open in ArcGIS” icon.  This takes users to ArcGIS Online where they can create choropleth maps and interact with the attribute table.   Users interested in tabular data can filter it and create various types of charts.  If more analysis of the data is necessary, you can download it by clicking the “Download Dataset” icon; you are able to download the entire dataset or the filtered dataset you’ve been working with.

OpenData_Page

Tips

The Source and Metadata links below the “About” heading provide information about the data.  In-depth information such as descriptions, attributes, OpenDataAboutand how the data was collected are provided in these links.  Below the name of the dataset there are three tabs:  “Details,” “Table,” and “Charts.”  Under the “Details” tab there are three sections, the Description, Dataset Attributes, and Related Datasets sections.  The Dataset Attributes section outlines the fields found within the dataset and provides field type information, while the Related Datasets section provides links to other datasets that have similar geographies or topics to the dataset you’ve chosen.  In the “Table” tab, you can view and filter the entire table in the dataset and the “Charts” tab allows you to create different charts.

OpenDataDetailTo obtain the most updated dataset or other updated articles related to the dataset, users should subscribe to the dataset they are interested in.  To subscribe, copy the link provided into an RSS Reader.  For specific data source questions, feel free to ask the Data and Visualization Department at askdata@duke.edu.

Wrangle, Refine, and Represent

Data visualization and data management represented the core themes of the 2011 Computer Assisted Reporting (CAR) Conference that met in Raleigh from February 24-27.  Bringing together journalists, computer scientists, and faculty, the conference united a number of communities that share a common interest in gathering and representing empirical evidence online (and in print).

While the conference featured luminaries in data visualization (Amanda Cox, David Huynh , Michal Migurski, Martin Wattenberg) who gave sage advice on how to best represent data online, web based data visualization tools provided a central focus for the conference.

Notable tools that may be of interest to the Duke research (and teaching) community include:

DataWrangler – An interactive data cleaning tool much like Google Refine (see below)

Google Fusion Tables – “manage large collections of tabular data in the cloud” – Fusion tables provides convenient access to google’s data visualization and mapping services.  The service also allows groups to annotate data online.

Google Refine – Refine is primarily a data cleaning tool that simplifies the process of cleaning data for further processing or analysis.  While users of existing data management tools may not be convinced to leave their current data management tool, Refine provides a rich suite of tools that will likely attract many new converts.

Many Eyes – One of the premier online visualization tools hosted by IBM.  Visualizations range from pie charts to digital maps to text analysis.  Many Eye’s versatility is one of its key strengths.

Polymaps – Billed as a “javascript library for image- and vector-tiled maps” – Polymaps allows the creating of custom lightweight map services on the web.

SIMILE Project (Semantic Interoperability of Metadata and Information in unLike Environments) – The SIMILE Project is a collection of different research projects designed to “enhance inter-operability” among digital assets.  At the conference, the Exhibit Project received particular attention for its ability to produce data rich visualization with very little coding required.

Timeflow –  Presented by Sarah Cohen and designed by Martin Wattenberg- Timeflow provides a convenient application for visualizing temporal data.