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Week 6: QA/QC 2: Data correction & synthesis with Open Refine Objectives and Competencies for this session: Be able to import a dataset into OpenRefine, make changes to the dataset and its structure, and export the revised Dataset.

QA/QC 2: Using OpenRefine to clean data How many ways can you spell the word… . OpenRefine is a powerful, free, and open source tool that is used to work with and clean messy data.

QA/QC 3: Finding Errors with Data Visualization Objectives and Competencies for this session: Explain the elements of good figures Read: Rougier NP, Droettboom M, Bourne PE (2014) Ten Simple Rules for Better Figures.

PART 1: DataViz to find errors Dataset for part 1: las_data_viz.csv Code: the code used in class is at the bottom of this page. You can also download it here.

Documentation: Metadata, Codebooks Objectives and Competencies for this session: Be able to explain what metadata are and why they are important Identify & list the types of information typically included in metadata records Identify reasons metadata is of value to data users, creators, and organizations Be able to identify metadata standards relevant to different disciplines Explain the elements of good metadata Please read / watch these before class: Readings: None this week

Metadata & Codebooks 1. Review of Other Researchers' Metadata Data repositories such as Dryad and ICPSR are designed to permanently store the data thatused in research so it is available to future scholars.

Data Management Plans Objectives and Competencies for this session: Define a DMP and understand the importance of preparing one Identify the key sections of a DMP and how they vary by discipline Understand how to find and use online tools for creating DMPs Pre-class preparation: Readings:

Introduction - DMPs Today in class we will start drafting the DMP assigned as part of your semester project. To do so we will use the DMP tool, to which we have access as UF Researchers.

Efficient Data Collection Objectives and Competencies for this session: Learn to evaluate data collection procedures to identify steps at which errors are likely to enter and propagate Critique and improve data collection forms Learn to prepare and use checklists for complex procedures such as data collection Please read / watch these before class: Readings: Redman, T.

Efficient Data Collection Breakout: Process Audit of Data Forms Look over these forms link and conduct a process audit. Where and why do you think errors are most likely to sneak in?