My Data Knowledge Index This page keeps track of the things I learn about data (broadly). I'll peel it off into sub-pages eventually.
- Handy short link for this page: [https://bit.ly/know-data].
- See Also: My Digital Literacy page
* Know Data, you know, like a "no data found" error. It's an update on my old nerd pun.
- Association of Computing Machinery — ACM Code of Ethics and Professional Conduct
- Data Science Association — DATA SCIENCE CODE OF PROFESSIONAL CONDUCT
- Oxford-Munich Code of Conduct
- Accenture — Universal Principals of Data Ethics, 12 Guidelines for developing ethics codes (PDF)
- See page Bias and Justice
- Phi Delta Kappan — Ethical and appropriate data use requires data literacy
- Cathy O'Niel Weapons of Math Destruction
- Tim O'Reilly WTF? What’s the Future and Why It’s Up to Us
Wikipedia's page on data literacy is in a sad state; I plan to use the information below to remedy that condition. (some day, maybe)
- Dalhouseie Data Literacy Report (2015). Dalhousie University, 2015. This is an excellent "synthesis report that provides a wealth of infromation including references to many sources of learning and informtion.
- Data literacy instruction in academic libraries: best practices for librarians
- UBC—Library:Faculty Information Literacy Toolkit
- Building a unified data and information literacy program: A collaborative approach to instruction
- Working Group on Education: digital skills for life and work. UNESCO, 2017. I found this report while looking at the OECD Skills Outlook 2019, which refers to this report (p. 187) as a reference for "Digital Literacy", within which "data literacy" is a component of Information and Communication Technology (ICT) literacy. This is interesting from the perspective of understanding what "data literacy" and "digital literacy" are and why they are important to learn.
- Media and Information Literacy in Higher Education O'Reilly Learning Platform
I am focusing on learning sources that have the highest probability of being available and remaining free. There are many non-free resources (such as the books listed below), of mixed quality. Before spending money, I strongly suggest that learners focus on simple, free options to get a handle on the basics.
The Data Literacy Project (Free)- Primarily sponsored by Qlik, this site has a wealth of learning material that is worth looking into. This group also offers certification as well as a feudal system of classification (e.g. Data Knight, Data Aristocrat). Looking past classification differences, however, this a very worthy project and a good place to start learning.
- School of Data (Free) — General Introduction to Data Topics
- Data Fundamentals — Modules: "What is Data", "Finding Data", "Sort and Filter: The basics of spreadsheets", "Taming the Fierce Beast – The Math you need to start", "From Data to Diagrams: An introduction to plots and charts", "Look Out!: Common Misconceptions and how to avoid them", "Tell me a story: Working out what’s interesting in your data", "Data provenance", and "Basic Graphs"
- Data Cleaning — Modules: "Course outline: a gentle introduction to cleaning data", "Section 1: Nuts and chewing gum", "Section 2: the Invisible Man is in your spreadsheet, messing with your data", "Section 3: your data is a witch’s brew", and "Section 4: Did you bring the wrong suitcase (again)?"
- Introduction to Exploring Data
- A gentle Introduction into Extracting Data
- A Gentle Introduction to Mapping
- Collecting data using smartphones
- Presenting Data
- DataJournalism.com (Free. Registration req. for some content) — Instruction for journalists to understand and communicate data-related topics. This material is mostly narrative, but is story-driven which makes it very approachable for non-technical learners.
- The Data Journalism Handbook 1 — How Journalists can use data to Improve the News
- The Data Journalism Handbook 2 — Towards a Critical Data Practice. (Work in Progress) A deeper dive into the topics of data, but many chapters do not have all of the articles listed.
- Doing Journalism with Data: First Steps, Skills, and Tools (Video with exercises. Registration req.) — Course Description: Comprising of video lectures, tutorials, assignments, readings, and discussion forums, this course is open to anyone in the world with an Internet connection who wants to tell stories with data.
- European Data Portal - E-Learning Programme (Free) — Provides 16 learning modules focused around open data and its use. Only a sample of Lessons are listed below; go to the E-Learning Programme page to see the full list.
- Data Equity for Main Street — The Data Equity for Main Street project has developed curriculum to promote open data literacy by training librarians and community members how to find, use and give feedback about open data.
Here are some nice links to resources that focus on Data Science instruction, which brings together advanced topics and tools including machine learning, programming with R and Python, and more. Advanced data analytics often requires you to leave the comfortable embrace of Microsoft Excel, especially when you have to prepare and transform data before you can use it for analysis.
- Microsoft Academy (Free for now)
- EdX (Free to learn, Pay for Certificate)
- The Centre for Humanitarian Data — We Are All Data People: Insights From The Data Literacy Survey
- Common statistical tests are linear models (or: how to teach stats)
- An introduction to the General Temporal Data Model and the Structured Population Event History Register (SPEHR)
- Mike Smit (co-author): Publications List
- The Information Diet
- Infromation Literacy and Lifelong Learning
- Data Association Data Management Body of Knowledge (DAMA DM-BOK), 2nd Edition
- Data Visualization and Statistical Literacy for Open and Big Data Skillsoft
"DataOps (data operations) has its roots in the Agile philosophy. It relies heavily on automation, and focuses on improving the speed and accuracy of computer processing, including analytics, data access, integration, and quality control. DataOps started as a system of best practices, but has gradually matured to a fully functional approach for handling data analytics. Additionally, it relies on, and promotes, good communications between the analytics team and the information technology operations team." (Source: DataVersity)
- Wikipedia: DataOps
- Garner Glossary: DataOps
- Data Kitchen: (datakitchen.io)
- Dataversity: Understanding DataOps
- DevOps.com: 5 Ways Your Business Can Benefit From DataOps
- IBM Big Data & Analytics Hub: 3 reasons why DataOps is essential for big data success
- Also, for more context on
*Ops, check out this article from Medium.com: What the Heck is *Ops?
- Organiation for Economic Cooperation and Development (OECD) — https://data.oecd.org/
- US Federal Reserve Bank — https://www.federalreserve.gov/data.htm
- Proquest Statistics Abstract of the United States (via California State Library. Card req.) — https://statabs-proquest-com.proxy.library.ca.gov/
- US Census — https://www.census.gov/data/tables.html
- California Child Welfare indicators Project
- US Center for Disease Control
- Federal Open Data Portal
- California
Public data is defined as data that is not specifically posted to
These links point to various resources that provide data upon request. They typically involve an approval process, but are not the same as a public records request.