Copyright and IUScholarWorks

So you want to submit a published or unpublished article into IUScholarWorks (IUSW) repository? Here’s what you’ll need to know about copyright.

If you are submitting an unpublished article, no worries – you are the rightsholder, so go ahead and submit it to IUSW. If you are submitting an article that has been previously published, though, you (the author) are probably not the rightsholder. If this is the case, you will need to do a little extra research before depositing into IUSW.

Generally, copyright transfers over to a publisher upon publication of an article, so you will need to check with the publisher prior to depositing it. If you still have your signed publishing agreement this should indicate what your rights are. If you don’t have this document, here are some suggestions to move forward.

  1. Your first step is to search SHERPA/RoMEO, a freely available online database of publisher copyright policies. Simply type in the name of your journal and you should receive information on what you can submit to an institutional repository such as IUSW. (For those new to S/R, this helpful video should clarify the search process and terminology.)
  2. If you cannot find information through SHERPA/RoMEO, you will want to check to see if the journal has a website. If so, copyright information may be located there.
  3. The final way to check copyright of an article is to contact the editor of the journal–not the publisher, which usually oversees many journals. It is helpful for the author of the work in question to write the message. We’ve found that this usually helps expedite the process. You can use a format like this sample letter to the editor. 

After completing these steps, you should now know what exactly can be deposited into IUSW: pre-print, post-print, or the publisher’s version of your article.

One easy way to save yourself this trouble moving forward is to complete the SPARC Author Addendum prior to signing your copyright over to a publisher. This legal document ensures that you keep the rights that you want, including the ability to archive your work in an institutional repository like IUSW. Read about the addendum to determine if it’s right for you!

Free Tools to Visualize Your Data

Data visualization has grown in popularity as datasets have become larger and tools have become more user-friendly. This area is eagerly being explored by researchers in a variety of disciplines. Although many people think of numbers when they consider types of data, data comes in many forms–including text! In fact, for many researchers, especially those in the humanities or social sciences, text is their primary data source.

Image 1: network visualization
This example of a network visualization could be created using a tool like Gephi or Sci2. Image: Clickstream Data Yields High-Resolution Maps of Science. Johan Bollen, Herbert Van de Sompel, Aric Hagberg, Luis Bettencourt, Ryan Chute, Marko A. Rodriguez, Lyudmila Balakireva. http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004803

Here is a brief list of freely available tools you can use to explore and visualize both numerical and textual data. This list is by no means comprehensive; to check out additional tools, try the visualization tool list at Bamboo DiRT.

  • D3 – A JavaScript data visualization library. While you would need to invest the time to learn basic JavaScript, this introductory tutorial breaks down steps to learn D3. You can also check out the array of impressive visualizations resulting from its use.
  • Gephi – If you only wanted to invest the time to learn one visualization tool, this open source software for visualizing networks and complex systems is a great choice. Take a look at one of the many available tutorials to get started.
  • ManyEyes – This tool allows users to easily upload datasets and create basic visualizations. To get a feel for the types of visualizations created, view the ManyEyes gallery.
  • Sci2 Tool – This tool, developed at the Indiana University Cyberinfrastructure for Network Science Center, is billed as “a modular toolset specifically designed for the study of science [that] supports the temporal, geospatial, topical, and network analysis and visualization of scholarly datasets.” Its strength lies in its ability to handle network data, similar to Gephi.
  • Tableau Public – This free, limited-functionality version of the popular software Tableau simplifies the act of creating charts and graphs.
  • Voyant – This is a browser-based platform for analysis and visualization of texts. It is a beginner-friendly tool with modest functionality: visualizations created within Voyant are limited to charts and graphs, though it would be easy to plug the data generated by the program into another platform with greater capacity for visualization, such as Gephi.
  • WordSeer – WordSeer is a textual analysis and visualization tool comparable to Voyant. The latest version, 3.0, has not yet been released publicly.

Lastly, I would be remiss if I failed to mention the important role that data management plays in data visualization. Poorly managed data may hinder your ability to create effective visualizations, so learn a few simple steps to manage your data more effectively. For more information, contact Stacy Konkiel, Science Data Management Librarian, at skonkiel@indiana.edu to schedule a consultation!

Simple Steps to Manage Your Data More Effectively

Data management can be an intimidating topic. However, learning how to manage your data can improve your research processes and therefore your life! Not to mention the fact that many grant funding agencies now require data management plans to be submitted with proposals. Is your interest piqued yet? Read below for some easy first steps toward managing your data.

Consider your current data practices

Here are some preliminary questions to ask yourself.

  • What data do I collect?
  • Do I follow a process for collecting and documenting my data?
  • Who contributes data–just me or others, too?
  • What format is the data in?
  • Where is the data stored?
  • Is the data being backed up?

Determine areas to improve

Compare the following suggestions to your own data practices. If you can start taking steps to improve the weaker areas, you’ll be all set.

  • Documentation – Document the processes and workflows you follow when collecting and managing your data in a README file (click here for a good example). It is also important to follow standards within your field for documenting contextual information about your data. In library jargon, this is known as metadata. To search for a metadata standard in your discipline, try the Digital Curation Centre’s helpful search tool.
  • Formats – Ideally, data should be stored in open, non-proprietary formats. This will ensure that it can be accessed well into the future. The Open Data Handbook gives a good overview of open formats. This can be as simple as saving files as a CSV instead of Excel spreadsheet or a text file instead of Microsoft word document.
  • Storage – IU offers several options for data storage. You can store your data on the cloud through IU Box, which also provides excellent versioning and collaborative functionality. For sensitive or large data sets, you can use the Scholarly Data Archive. Whatever you do, just make sure that you are backing up your data and not just relying on your hard drive to keep your data safe. Also note that these options do not ensure long-term preservation. For this, you should consider adding completed data sets to the IU institutional repository, IUScholarWorks (IUSW).
  • Sharing and Access Opening up your data won’t be appropriate for all researchers, but those whose research is complete should consider storing their data in IUSW to promote discoverability and access to their data.

Get help

Data management advice is nearly impossible to generalize, especially in a short blog post! Contact Stacy Konkiel, Science Data Management Librarian, at skonkiel@indiana.edu with questions, comments, or to schedule a one-on-one consultation about how the IU Libraries Data Management Service can help you manage your data.

Predatory Publishers and IUScholarWorks

My name is Brianna Marshall and I am the Scientific Data Curation Assistant in the Scholarly Communication Department. While my responsibilities primarily pertain to helping researchers manage their data, I also work with IUScholarWorks (IUSW) quite frequently. Making your work available in IUSW ensures that it is preserved and made available to researchers around the world. Unfortunately, individuals submitting work to IUSW and other institutional repositories may find themselves targeted by predatory open access publishers.

What is a predatory publisher?

Often, predatory publishers do not offer traditional editorial services, such as peer review (although they may claim that they do). Many of these journals will accept an article then let the author know that they owe an exorbitant publication fee.

These predatory publishers can seem legitimate – they may have fully functional websites and authors rights statements that are similar to those of well-respected publishers, but this is no guarantee of their quality. The rise of online publishing has made it easier for these groups to masquerade as legitimate publishers.

How can I identify a predatory publisher?

Predatory publishers don’t serve any risk to researchers if you can identify and discount them as an option for disseminating your work.

Predatory publishers are seeking to make a large profit, so they are known to aggressively seek out new authors or editors. Receiving a form email that requests your submission to a particular publisher should be your first clue. Some publishers are bold enough to find authors who have submitted to institutional repositories: a librarian within our department experienced this firsthand after submitting her work into IUSW.

Don’t be fooled by these publishers. If you have any suspicions about the publisher, we recommend that you consult Beall’s List of Predatory Publishers. Jeffrey Beall, a librarian at the University of Colorado-Denver, publishes a list of “potential, possible, or probable predatory scholarly open-access publishers” on his website. If after consulting his list you still have questions or concerns, consult your local librarian.

How can I avoid unwanted reuse of my work?

Clearly licensing your work with a non-commercial Creative Commons license is a possible way to thwart unwanted reuse of your work, but it’s not fool-proof. The rise of predatory publishers means that scholars need to be more vigilant than ever about researching where they choose to publish and what rights they have over that work.