The document discusses data sources and data management. It notes that data comes in numerical and textual forms from various sources like existing sites, repositories, experiments, surveys, and all around us. It asks about the differences between human and computer memory for managing data. It also outlines several tools for working with different data types, including spreadsheets for numerical data, online sites for visualizing data, and programs like Inspiration for linking textual data.

2.  Data comes in two basic forms:
 Numerical – numbers
 Textual – words
 Data comes from many sources
 Let’s brainstorm a few…
 First open a program called
Inspiration
 Now name some sources

3.  Sources include:
 Existing statistical sites online
▪ Real time data sites
 Repositories of events like encyclopedias and
books
 Our own experiments
 Surveys and questionnaires
 All around us in all kinds of forms
▪ Text
▪ Visuals

4.  What is difference between your memory and
a computer when it comes to managing data?
▪ How many e-mail contacts can you recall from your
address book?
▪ If you read long speech, how long does it take you to
determine the key themes?
▪ If you take notes from a lecture, how do you determine
the most important information?

5.  Spreadsheet programs like Microsoft Excel
 Keep track of numerical data
 Allows you to sort or filter data
 Allows you create formulas to answer questions
 Allows you to display and communicate data visually
through charts and graphs
 Also has a way to grab real-time data (search Google for
“Real time data sites”)
 Online sites such as Many-Eyes, Google Earth or
Google Public Data let you visually represent
numerical data in powerful ways

6.  Inspiration and Kidspiration let you
link text
 Draws out connections
 Visually shows the important data
 Add images to enhance understanding
 Many-Eyes and Wordle are online
tools to help express text data
visually for analysis
 Wikis are also a way to capture text
data in the form of an encyclopedic
form

7.  Develop a lesson/activity relevant to your
discipline, topic, and grade level that involves
data analysis using one of the tools.