Archive of ‘digital storytelling’ category

text and data mining

38 great resources for learning data mining concepts and techniques

http://www.rubedo.com.br/2016/08/38-great-resources-for-learning-data.html

Learn data mining languages: R, Python and SQL

W3Schools – Fantastic set of interactive tutorials for learning different languages. Their SQL tutorial is second to none. You’ll learn how to manipulate data in MySQL, SQL Server, Access, Oracle, Sybase, DB2 and other database systems.
Treasure Data – The best way to learn is to work towards a goal. That’s what this helpful blog series is all about. You’ll learn SQL from scratch by following along with a simple, but common, data analysis scenario.
10 Queries – This course is recommended for the intermediate SQL-er who wants to brush up on his/her skills. It’s a series of 10 challenges coupled with forums and external videos to help you improve your SQL knowledge and understanding of the underlying principles.
TryR – Created by Code School, this interactive online tutorial system is designed to step you through R for statistics and data modeling. As you work through their seven modules, you’ll earn badges to track your progress helping you to stay on track.
Leada – If you’re a complete R novice, try Lead’s introduction to R. In their 1 hour 30 min course, they’ll cover installation, basic usage, common functions, data structures, and data types. They’ll even set you up with your own development environment in RStudio.
Advanced R – Once you’ve mastered the basics of R, bookmark this page. It’s a fantastically comprehensive style guide to using R. We should all strive to write beautiful code, and this resource (based on Google’s R style guide) is your key to that ideal.
Swirl – Learn R in R – a radical idea certainly. But that’s exactly what Swirl does. They’ll interactively teach you how to program in R and do some basic data science at your own pace. Right in the R console.
Python for beginners – The Python website actually has a pretty comprehensive and easy-to-follow set of tutorials. You can learn everything from installation to complex analyzes. It also gives you access to the Python community, who will be happy to answer your questions.
PythonSpot – A complete list of Python tutorials to take you from zero to Python hero. There are tutorials for beginners, intermediate and advanced learners.
Read all about it: data mining books
Data Jujitsu: The Art of Turning Data into Product – This free book by DJ Patil gives you a brief introduction to the complexity of data problems and how to approach them. He gives nice, understandable examples that cover the most important thought processes of data mining. It’s a great book for beginners but still interesting to the data mining expert. Plus, it’s free!
Data Mining: Concepts and Techniques – The third (and most recent) edition will give you an understanding of the theory and practice of discovering patterns in large data sets. Each chapter is a stand-alone guide to a particular topic, making it a good resource if you’re not into reading in sequence or you want to know about a particular topic.
Mining of Massive Datasets – Based on the Stanford Computer Science course, this book is often sighted by data scientists as one of the most helpful resources around. It’s designed at the undergraduate level with no formal prerequisites. It’s the next best thing to actually going to Stanford!
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners – This book is a must read for anyone who needs to do applied data mining in a business setting (ie practically everyone). It’s a complete resource for anyone looking to cut through the Big Data hype and understand the real value of data mining. Pay particular attention to the section on how modeling can be applied to business decision making.
Data Smart: Using Data Science to Transform Information into Insight – The talented (and funny) John Foreman from MailChimp teaches you the “dark arts” of data science. He makes modern statistical methods and algorithms accessible and easy to implement.
Hadoop: The Definitive Guide – As a data scientist, you will undoubtedly be asked about Hadoop. So you’d better know how it works. This comprehensive guide will teach you how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. Make sure you get the most recent addition to keep up with this fast-changing service.
 Online learning: data mining webinars and courses
DataCamp – Learn data mining from the comfort of your home with DataCamp’s online courses. They have free courses on R, Statistics, Data Manipulation, Dynamic Reporting, Large Data Sets and much more.
Coursera – Coursera brings you all the best University courses straight to your computer. Their online classes will teach you the fundamentals of interpreting data, performing analyzes and communicating insights. They have topics for beginners and advanced learners in Data Analysis, Machine Learning, Probability and Statistics and more.
Udemy – With a range of free and pay for data mining courses, you’re sure to find something you like on Udemy no matter your level. There are 395 in the area of data mining! All their courses are uploaded by other Udemy users meaning quality can fluctuate so make sure you read the reviews.
CodeSchool – These courses are handily organized into “Paths” based on the technology you want to learn. You can do everything from build a foundation in Git to take control of a data layer in SQL. Their engaging online videos will take you step-by-step through each lesson and their challenges will let you practice what you’ve learned in a controlled environment.
Udacity – Master a new skill or programming language with Udacity’s unique series of online courses and projects. Each class is developed by a Silicon Valley tech giant, so you know what your learning will be directly applicable to the real world.
Treehouse – Learn from experts in web design, coding, business and more. The video tutorials from Treehouse will teach you the basics and their quizzes and coding challenges will ensure the information sticks. And their UI is pretty easy on the eyes.
Learn from the best: top data miners to follow
John Foreman – Chief Data Scientist at MailChimp and author of Data Smart, John is worth a follow for his witty yet poignant tweets on data science.
DJ Patil – Author and Chief Data Scientist at The White House OSTP, DJ tweets everything you’ve ever wanted to know about data in politics.
Nate Silver – He’s Editor-in-Chief of FiveThirtyEight, a blog that uses data to analyze news stories in Politics, Sports, and Current Events.
Andrew Ng – As the Chief Data Scientist at Baidu, Andrew is responsible for some of the most groundbreaking developments in Machine Learning and Data Science.
Bernard Marr – He might know pretty much everything there is to know about Big Data.
Gregory Piatetsky – He’s the author of popular data science blog KDNuggets, the leading newsletter on data mining and knowledge discovery.
Christian Rudder – As the Co-founder of OKCupid, Christian has access to one of the most unique datasets on the planet and he uses it to give fascinating insight into human nature, love, and relationships
Dean Abbott – He’s contributed to a number of data blogs and authored his own book on Applied Predictive Analytics. At the moment, Dean is Chief Data Scientist at SmarterHQ.
Practice what you’ve learned: data mining competitions
Kaggle – This is the ultimate data mining competition. The world’s biggest corporations offer big prizes for solving their toughest data problems.
Stack Overflow – The best way to learn is to teach. Stackoverflow offers the perfect forum for you to prove your data mining know-how by answering fellow enthusiast’s questions.
TunedIT – With a live leaderboard and interactive participation, TunedIT offers a great platform to flex your data mining muscles.
DrivenData – You can find a number of nonprofit data mining challenges on DataDriven. All of your mining efforts will go towards a good cause.
Quora – Another great site to answer questions on just about everything. There are plenty of curious data lovers on there asking for help with data mining and data science.
Meet your fellow data miner: social networks, groups and meetups
Reddit – Reddit is a forum for finding the latest articles on data mining and connecting with fellow data scientists. We recommend subscribing to r/dataminingr/dataisbeautiful,r/datasciencer/machinelearning and r/bigdata.
Facebook – As with many social media platforms, Facebook is a great place to meet and interact with people who have similar interests. There are a number of very active data mining groups you can join.
LinkedIn – If you’re looking for data mining experts in a particular field, look no further than LinkedIn. There are hundreds of data mining groups ranging from the generic to the hyper-specific. In short, there’s sure to be something for everyone.
Meetup – Want to meet your fellow data miners in person? Attend a meetup! Just search for data mining in your city and you’re sure to find an awesome group near you.
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8 fantastic examples of data storytelling

8 fantastic examples of data storytelling

Data storytelling is the realization of great data visualization. We’re seeing data that’s been analyzed well and presented in a way that someone who’s never even heard of data science can get it.

Google’s Cole Nussbaumer provides a friendly reminder of what data storytelling actually is, it’s straightforward, strategic, elegant, and simple.

 

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more on text and data mining in this IMS blog
hthttp://blog.stcloudstate.edu/ims?s=data+mining

digital storytelling brainstorming

digital storytelling from writing

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Forget storytelling. ‘Hypertelling’ is the future, says Google Zoo founder

At C2 Montreal, Mike Yapp explains how technology is driving a narrative leap akin to the printed word

Read more at http://www.campaignlive.co.uk/article/forget-storytelling-hypertelling-future-says-google-zoo-founder/1396454#4sCKmcICYCQa13Lw.99

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Defining Digital Storytelling from digitalstorytelling

 

school leadership and digital storytelling

Guajardo, M., Oliver, J. A., Rodríguez, G., Valadez, M. M., Cantú, Y., & Guajardo, F. (2011). Reframing the Praxis of School Leadership Preparation through Digital Storytelling. Journal of Research on Leadership Education, 6(5), 145–161. http://doi.org/10.1177/194277511100600504
http://web.stcloudstate.edu/pmiltenoff/lib490/literature.html#d
p. 149-150. Digital storytelling applies techniques that cross disciplines, fields, and subject matter. Digital storytelling pioneer Dana Atchley used the varied techniques such as case study, personal experience, introspection, life story, interviews, artifacts, cultural texts, observations, historical interaction, visual texts, and others (Lambert, 2002, 2006). Atchley’s techniques are firmly rooted in research methodology and collectively describe routine and problematic moments and meanings in individuals’ lives (Denzin & Lincoln, 2000; Lambert, 2006). Qualitative researchers often refer to this process as a bricolage, or the creation or construction from a variety of things. This bricolage helps Downloaded from jrl.sagepub.com at SAINT CLOUD STATE UNIV on June 8, 2016 Guajardo et. al./REFRAMING THE PRAXIS OF SCHOOL LEADERSHIP 150 to clarify our ontologies and inform epistemologies. Ladson-Billings (2000) explained epistemologies as more than the traditional way of knowing. Instead, epistemologies are a system of knowing that has both internal logic and external validity. The assortments of experiences used to inform our way of knowing then become the deliberate choices between hegemony and liberation. This process allows individuals to move beyond a traditional epistemological stance, or what Stanley (2007) has called the master narrative. Shujaa (1997) has called it a worldview epistemology that looks at knowledge as a symbiotic interaction of how we view the world, the knowledge we possess, and the knowledge we are capable of passing on to others.
p. 156 digital storytelling has been found to help organizations understand themselves (Militello & Guajardo, 2011). When organizations delve into introspective practices through the use of digital media, small and large organizations alike invite the opportunity to learn from deep, digital reflection.

storytelling and virtual reality

Is storytelling the key to VR’s future?

Virtual reality may be the closest to teleportation we will ever have in our lifetime.

More on virtual reality in this IMS blog:

http://blog.stcloudstate.edu/ims?s=virtual+reality

more on storytelling in this IMS blog:

http://blog.stcloudstate.edu/ims?s=storytelling

timeline tools for history and education

Technology tools for history lessons

HSTRY Timeline Creator.
HSTRY is a multimedia timeline creation tool that will work on your laptop, Chromebook, iPad, or tablet. With a HSTRY account you can build timelines in a vertical scroll format similar to that of a Facebook feed. To start the process pick a topic and upload a cover photo. To add events to the timeline just click the “+” symbol and select the type of media that you want to add to your timeline. You can add videos, images, audio, and text to the events on your timeline.
There are two features of HSTRY that make it stand-out from the crowd. First, as a teacher you can create an online classroom in which you can view all of your students’ timelines. Second, as a teacher you can build questions into timelines that you share with your students. You can even build-in explanations of the answers to your questions.
For other timeline creation tools, check out this chart.

My note: HSTRY could be a great tool, if the organizers were not that greedy. Their plan + kicks in way to early and does not allow participants to collaborate. E.g., Zaption allows teachers / students to “share” their presentations, but HSTRY asks right away to upgrade. Thumb down!

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5 Timeline Creation Tools Compared – Chart

http://www.freetech4teachers.com/2014/12/5-timeline-creation-tools-compared-chart.html

Free Online Tools for Creating Timelines – Richard Byrne – FreeTech4Teachers.com

  Multimedia options Collaboration options Registration required iPad/ tablet compatibility Output/ publishing
Timeline JS

timeline.knightlab.com

Text Images Videos Yes, if you collaborate through Google Spreadsheets*** Google Account required. Display: yes Creation: no Embed code for posting  on blog / website.
RWT Timeline

bitly.com/1ym46nY

Text Images No. No. iPad app bitly.com/1vMTI7C Android app bitly.com/1vOcZEB Web app bitly.com/1ym46nY PDF.

Image saved on camera roll.

TimeGlider*

timeglider.com

Text Images Yes. Yes. Display: yes Creation: yes Embed code for posting on blog / website. Direct link to TG page.
Dipity**

dipity.com

Text Images Videos Yes. Yes. Display: yes Creation: no Embed code for posting on blog / website.
MyHistro

myhistro.com

Text Images Videos No. Yes. Display: yes Creation: iOS PDF.

Embed code.

*TimeGlider’s basic plan is free for students. A paid subscription is required to activate collaboration tools.

**Dipity’s basic plan is free for students. The basic account is limited to three timelines.

***Timeline JS utilizes Google Spreadsheets as the basis of timeline event creation. Students collaborate on a spreadsheet to build timelines. A video of the process is available at http://bitly.com/1zRLdr5

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More on the use of technology in history in this IMS blog:

http://blog.stcloudstate.edu/ims?s=history

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