Reflecting on the immense amount of data openly and freely available online, especially on COVID-19, I wanted to write a blog post about the value and opportunities available to researchers related to open data. But as I began to write I thought about the other aspects of ‘openeness’ and realized there is so much more to write about than just open data. A recent blog post published by the SEA region of NNLM during love data week, 23 things about open data, completely covers the open data piece and I have nothing to add there. In addition, you may want to check out the very comprehensive list of COVID-19 open-access data and computational resources compiled by the Office of Data Science Strategy.
However, I think there are other aspects of open science at a broader level that could use some additional explanation and examples. The Carpentries, a non-profit organization, provides open and free coding and data science training opportunities through three programs, Data Carpentry, Software Carpentry, and Library Carpentry. Their lessons are all available online for self-directed learning or you can participate in training opportunities near you. Open Science can also entail open and participatory data collection through citizen science research activities like SciStarter. Open science initiatives and scientists often rely on open-source software and tools such as Zotero for collaborating on citation collection, Open Refine, Phyton, and R studio for data collection and manipulation, as well as many other visualization and data applications so that data can be easily shared and manipulated. Open Science also entails open collaboration for doing research that integrates tools for storing and sharing open science projects through the full research cycle such as the Open Science Framework (OSF). Open repositories can provide an infrastructure and space for collecting, archiving and preserving open data and provide identifiers for data collections when the research is finally published. And last but not least, is the emerging number of opportunities for publishing open research such as journals and books. Although many publishers require the author to pay publications fees for making research open to other researchers, there are many quality and open research examples available.
Even as I have been research open science and open scholarship I have found some open textbooks about open science I would like to recommend such as the Open Data Handbook, Open: The Philosophy and Practices that are Revolutionizing Education and Science, Issues in Open Research Data, and international perspectives in the Social Dynamics of Open Data. The Foster Open Science website in the EU offers some interesting paths into open science based on what you are interested in doing So to get started, jump into the open culture at any of these different open points to learn more about open data, how to find and manipulate open data, and how to share and publish in open formats.
Open Sicence Umbrella Image: FlickerThe post Living on the Data Fringes: Open Science Goes Beyond Open Data first appeared on MidContinental Region News.
Written By: Kiri Burcat, Data & Evaluation Coordinator, NNLM SEA
Advocacy and communication are a part of many librarians’ jobs. Infographics are a popular way to present information visually, and can help to communicate your point more clearly, more persuasively, and more memorably. Very few of us, however, have formal art or design training. Fortunately, for health information and outreach professionals, there are already many infographics on popular topics.
Here are a few reliable resources for health and wellness infographics*:
The American Heart Association has a collection of infographics focused on healthy living. Two favorites: choosing seasonal produce and staying cool during warm weather workouts.
The Centers for Disease Control and Prevention has infographics for many different public health issues. You can look for them on any CDC topic page, but here are a few selections:
If you still want to make your own from scratch, there are several available tools. Venngage, Canva, and Piktochart are popular and approachable options. Whichever program you choose, a few foundational design tips can build your confidence and help your infographics look more polished:
Learn about the rule of thirds. Use grids and guides to place elements for visual interest and compositional balance.
Use hex codes or RBG values to precisely match colors and draw inspiration from existing palettes. Adobe Color is one tool that you can use to choose color schemes. It includes an accessibility tool, which identifies potential color conflicts and simulates how your palette will look to individuals with different types of color blindness. Here, I uploaded a picture of the NNLM Data Roadmap graphic, and the program created a color palette. The hex codes are provided under the swatches so I can match them in my design program:
In some programs, you can fill a shape element with a photo to get a more custom look for your photos or elements. For presentations, I’ll sometimes do this with my photo and a circle element:
Explore possibilities beyond your software’s default photos, fonts, and icons. High-quality visual elements go a long way toward elevating your infographics, and usage rights and access can be affordable. With proper attribution, some free sources include: Unsplash (for photos), Google Fonts, and The Noun Project (for icons).
For more visual information topics from the NNLM, check out archived webinars on:
Or our on-demand class about data visualization: Cool Creative Communications: Dazzling Data Visualization
*Note and comply with attribution and usage guidelinesThe post Infographics: Tips, Tools, and Resources first appeared on SEA Currents.
The NNLM SEA is pleased to host an online Library Carpentry workshop on March 25th – 26th 2021.
Library Carpentry focuses on building software and data skills within library and information-related communities. Their goal is to empower people in these roles to use software and data in their own work and to become advocates for and train others in efficient, effective, and reproducible data and software practices.
The target audience is learners who have little to no prior computational experience. The instructors put a priority on creating a friendly environment to empower researchers and enable data-driven discovery. Biomedical and health sciences librarians and LIS students are encouraged to participate.
In this interactive, hands-on workshop you will learn core software and data skills, with lessons including:
- This workshop will be held via Zoom, from 9 am – 5:00 pm ET each day.
- Participants must have access to a computer (no tablets or Chromebooks) with Windows, Mac, or Linux operating system and an internet connection that can support a Zoom video meeting.
- Participants must agree to follow theCarpentries Code of Conduct.
- Participants will be responsible for downloading some files and software before the workshop. Setup instructions will be provided.
To apply, please complete the NNLM SEA Library Carpentry application.
There are 20 seats available. They will generally be awarded on a first-come-first serve basis, but applicants from organizations in the Southeastern Atlantic region of the NNLM will be prioritized.
Notice of acceptance to the workshop will be announced on Monday, March 15th.
Questions? Contact Kiri Burcat at firstname.lastname@example.org.The post Online Library Carpentry Workshop Opportunity: March 25th – 26th first appeared on SEA Currents.
Last January, MLA announced the Data Services Specialization (DSS) certificate that librarians can earn to demonstrate their attainment of the relevant knowledge and skills necessary to provide data services.
Best geared for health sciences librarians and information professionals and built upon the MLA Data Services Competency, the Basic Certification requires the completion of four 4-credit free Network of the National Library of Medicine courses. These courses cover 5 skill areas (i.e. principles of data literacy; data services; research data best practices across the data lifecycle, open science practices, and training and consultation on data-related topics) and are available on demand. An additional three credits in the five skill areas are required and several NNLM courses are listed on the NNLM Data Services Specialization page.
Registration for the NNLM courses is open and free. MLA DSS certification costs for MLA members is $55 and for MLA nonmembers is $75. You can find more information about the DSS certificate, including cost, requirements, and skills on the MLA website.The post DataFlash: MLA’s New Data Services Specialization (DSS) Certificate first appeared on Dragonfly.