Posted in response to the following prompt as a classmate-assigned asynchronous learning activity.

1. Take a few minutes to brainstorm/freewrite a list of all the places where you have data stored in memory – all the types of memory you use and access.
2. Think about the different types of data you store in these various places. Are there clear distinctions between the locations, or do you store files in whatever memory system is most readily available? Do you save in multiple locations as back-up or for convenience? Are you ever frustrated by the breadth of your memory?
3. Using Google Drawings (or draw by hand) to create a Venn Diagram showing the network of your memory systems. Label the spheres with the different places where you have stored data – lap top, work computer, Google Drive, flash drive, etc. Overlap the  spheres where we have stored the same data. Write the type of data (lesson plan, essay, photos) on the overlapping area of the sphere to show what you keep where.
4. Post to your blog (embed or scan and upload) with the tag “Memory Network” and maybe write a comment or two about anything interesting you learned.

Here’s what I learned—I am a little bit anal about where and how I save files. I have always created detailed folder/directory structures for saving files. As a result, I don’t have a great deal of “overlap” when it comes to individual files, or even file types. While Google Drive has become a go-to lately, my non-cloud-based files I’ve tried to carefully restrict to one and only one memory location. This tendency makes cloud-based file management easier; I have a single authoritative version of any given file that I try hard never to duplicate. In general, if a significant change is required, I try to create a duplicate of the file with a new file name to indicate that it’s a significantly different file. In this way, I try to create only unique nodes in my memory networks. “Normalized data” is a professional term for have a clear, one-to-one correlation between what data’s content is and where and how it’s stored. From working with UR Web Services and data conversions between CSV, MySQL, and XML data, I have discovered how vitally important normal data can be.