Difference between revisions of "Week 5"
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=== Reflect === | === Reflect === | ||
| − | + | A set of core competencies for ''scientific data literacy'' is listed in the section below. Answer the following questions on the shared [[Class Journal Week 5]] page: | |
# Which of these core competencies are you most skilled with (or which is most familiar to you)? Where and how did you gain the skills/become familiar? | # Which of these core competencies are you most skilled with (or which is most familiar to you)? Where and how did you gain the skills/become familiar? | ||
# Which of these core competencies do you want to know more about? Why? | # Which of these core competencies do you want to know more about? Why? | ||
Revision as of 20:48, 26 September 2017
This journal entry is due on Tuesday, October 3, at 12:01 AM PDT.
Contents
Objectives
The purpose of this assignment is:
- to deeply explore and perform a critical review of an existing biological database.
- to communicate your findings in an effective oral presentation.
- to gain and perform a self-assessment of your scientific data literacy skills.
Individual Journal Assignment
- Store this journal entry as "username Week 5" (i.e., this is the text to place between the square brackets when you link to this page).
- Link from your user page to this Assignment page.
- Link to your journal entry from your user page.
- Link back from your journal entry to your user page.
- Don't forget to add the "Journal Entry" category to the end of your wiki page.
- Note: You can easily fulfill all of these links by adding them to your template and then using your template on your journal entry.
- For your assignment this week, you will keep an electronic laboratory notebook on your individual wiki page. An electronic laboratory notebook records all the manipulations you perform on the data and the answers to the questions throughout the protocol. Like a paper lab notebook found in a wet lab, it should contain enough information so that you or someone else could reproduce what you did using only the information from the notebook.
- To be clear, on your individual wiki page, you will document your individual process in your electronic lab notebook.
- From this week onward, please use the individual journal page for your electronic lab notebook instead of a separate notebook page.
Homework Partners
For most weeks in the semester, you will be assigned a "homework partner" from a complementary discipline. You will be expected to consult with your partner, sharing your domain expertise, in order to complete the assignment. However, unless otherwise stated, each partner must submit his or her own work as the individual journal entry (direct copies of each other's work is not allowed). You must give the details of the interaction with your partner in the Acknowledgments section of your journal assignment. Homework partners for this week are:
- Eddie Azinge, Mary Balducci
- Eddie Bachoura, Emma Tyrnauer
- Dina Bashoura, Nicole Kalcic
- Blair Hamilton, Corinne Wong
- Hayden Hinsch, Simon Wroblewski
- Arash Lari, Antonio Porras
- Quinn Lanners, John Lopez
- Zach Van Ysseldyk, Katie Wright
NAR Database Evaluation and Presentation
Each year, the journal Nucleic Acids Research (NAR) devotes the first issue in January to biological databases. The Week 4 Assignment introduced you to four "gold standard" biological databases. In this assignment you will use what you learned to evaluate a different biological database. Collectively, through presentations, you will gain experience with the breadth and depth of biological databases available on the Web:
- Read (if you haven't already done so):
- Introduction to the 2017 NAR Database Issue: Galperin, M. Y., Fernández-Suárez, X. M., & Rigden, D. J. (2016). The 24th annual Nucleic Acids Research database issue: a look back and upcoming changes. Nucleic acids research, 45(D1), D1-D11. doi:10.1093/nar/gkw1188
- Slides from DataONE.org
- Together with your partner, choose your database:
- Nucleic Acids Research Database Issue Table of Contents 2017
- Nucleic Acids Research Database Issue Database List
- Make sure that the database you choose has a corresponding paper in the 2017 issue.
- You may not choose a database from NCBI, EBI, or the DNA Databank of Japan. You may not choose Ensembl, UniProt, SGD, or other major model organism database. The intent for this exercise is to pick something that is not one of the "major" databases.
- Sign up for your database by editing this page next to you and your partner's names. Dr. Dahlquist must approve all database choices.
PowerPoint Presentation
Each pair will prepare and give a 12-15 minute PowerPoint presentation based on their assigned database in class on Tuesday, October 3 or Thursday, October 5.
- You will need to prepare ~12-15 slides (assume 1 slide per minute of presentation).
- Please follow the Presentation Guidelines for how to format your slides.
- You may give a live demo of the database if you wish, but practice carefully so that you can do the presentation in 15 minutes.
- Alternately, you may choose to show screen shots instead of the live demo.
- You need to present the information you gathered about your database that you listed in your review above, but organized as a presentation.
- Your presentation (both the slides and the oral presentation) will be evaluated by the instructors using the guidelines shown here in the four areas:
- Content and message
- Organization
- Visuals/slides
- Speaking style/delivery
- Your PowerPoint slides must be uploaded and linked to on your individual journal entries by the journal deadline of 12:01 AM on Tuesday, October 3, even if your presentation is on Thursday .
- You can update your slides before your presentation, but we will be grading the ones you upload by the deadline.
- Finally, your presentation will also be evaluated by your fellow classmates (anonymously) who will answer the following questions:
- What is the speakers’ take-home message? (One short sentence)
- What is the best point about the presentation’s organization? What needs improvement? Give one specific example for each.
- What is the best point about the presentation’s visuals (slides)? What needs improvement? Give one specific example for each.
- What is the best point about the presentation’s delivery (speaking style)? What needs improvement? Give one specific example for each for each presenter.
- Store your journal entry in the shared Class Journal Week 5 page. If this page does not exist yet, go ahead and create it (congratulations on getting in first 👏🏼)
- Link to your journal entry from your user page.
- Link back from the journal entry to your user page.
- NOTE: You can easily fulfill the links part of these instructions by adding them to your template and using the template on your user page.
- Sign your portion of the journal with the standard wiki signature shortcut (
~~~~). - Add the "Journal Entry" and "Shared" categories to the end of the wiki page (if someone has not already done so).
Reflect
A set of core competencies for scientific data literacy is listed in the section below. Answer the following questions on the shared Class Journal Week 5 page:
- Which of these core competencies are you most skilled with (or which is most familiar to you)? Where and how did you gain the skills/become familiar?
- Which of these core competencies do you want to know more about? Why?
Scientific Data Literacy Core Competencies
- Databases and Data Formats
- Understand how to query relational databases, and be familiar with data types and formats for the discipline.
- Discovery and Acquisition of Data
- Locate and utilize disciplinary data repositories, and identify appropriate data sources
- Data Management and Organization
- Understand the lifecycle of data, and use data management plans to track subsets of processed data.
- Data Conversion and Interoperability
- Migrate data from one format to another, and understand the benefits of standard data formats.
- Quality Assurance
- Use metadata and screening procedures to recognize artifacts, incompletion, or corruption of data sets.
- Metadata
- Interpret metadata from external sources, and annotate data so it can be used by external users.
- Data Curation and Re-use
- Recognize the role of curation throughout the data lifecycle in its value in effective reuse of data.
- Cultures of Practice
- Know the practices, values, and norms of discipline as they relate to managing, sharing, and curating data.
- Data Preservation
- Understand the technology, resource, and organizational components of preserving data.
- Data Analysis
- Understand the basic analysis tools of their discipline including workflow management tools.
- Data Visualization
- Use visualization tools of discipline, and understand the advantages of the different types of visualization.
- Ethics, including citation of data
- Understand intellectual property, privacy, and the ethos of the discipline around sharing and citing data.
