What is CADVCEVS?

CADVCEVS, which stands for Classification Approach to Data Visualization and Content Exploration Via Subject Guides, is a project exploring the use of Linked Data and data visualization to create an interactive learning tool by expanding on the traditional subject guides provided by libraries.

What is cadvcevsWiki?

cadvcevsWiki (aka this site) is a collaborative knowledge base consisting of a collection of subject guides and pages that function similarly to subject guides—i.e. they direct users to resources about a given topic that will help them
  • pursue research,
  • learn about new resources, and
  • find fun and interesting things about Classical topics.

Who are you/Who's in charge here?

CADVCEVS (and by extension, cadvcevsWiki) is a project dreamed up and managed by Emily Gering, who received a B.A. in Classical Studies from the University of North Carolina at Greensboro with a concentration in Classical language and literature. She is currently studying library science at the University of North Carolina at Chapel Hill. [Emily on LinkedIn | More about Emily]

Can I use content from cadvcevsWiki for X?

All content on cadvcevsWiki is licensed under a GNU Free Documentation License and can be used, without asking for permission and without any attribution required, for any purpose, such as teaching (broadly defined); inclusion on a syllabus, worksheet, etc.; distribution to students, colleagues, or library patrons; or wearing it as a hat (although if you want to do that, you will likely have to print it out first).

How can I help?

You can volunteer to help in one or more of the following ways:
  • Content creation (writing wiki pages, adding content, etc.)
  • Revision (editing existing pages and content)
  • Maintenance/metadata (indexing, tagging, etc.)

You can help by visiting the Get Started page and choosing one of three ways of joining the wiki and contributing.

Will I get credit for my contributions?

Everyone who contributes substantially to cadvcevsWiki will receive credit for their contributions in presentations, publications, etc. concerning the project. A substantial contribution is considered to be the creation of one or more pages, addition of new content to existing pages, or significant revision of existing pages. Contribution to maintenance efforts (e.g. maintaining the index, tagging pages, etc.) is also considered a substantial contribution for which contributors will receive credit.

Please note that to receive credit for contributions in the areas of revision and maintenance/metadata, you must register as a contributor or have (or sign up for) a Wikispaces, OpenID, Google, or Yahoo account to join the wiki. Because multiple people can use Quick Start accounts, there is no way to determine who has made what changes based on username, and a unique username/account is necessary to track contributions. However, Quick Start account users who contribute new content can receive credit by adding the name under which they would like to receive credit to the relevant items in the Index.

What are subject guides?

A subject guide is by definition a “[list] of resources created by librarians to assist students with their research needs.” Subject guides traditionally include books, journals, databases, websites, as well as any other topics the librarian feels would assist students with their research.[1]

What's Linked Data?

Linked Data is a method of using the Web to create meaningful links between data from multiple sources.[2] In the context of a website, these links can be the clickable links many Internet users are accustomed to seeing, but the links can also be “hidden” as encoded metadata that looks like normal text. Linked Data can also be stored outside of websites, in databases called triplestores. If you are interested in a slightly more technical introduction to Linked Data, you may be interested in this slideshow.

  1. ^ http://www.libsuccess.org/Subject_Guides
  2. ^ Bizer, C, T. Heath, & T. Berners-Lee. (2009). "Linked Data—The Story So Far" (PDF). International Journal on Semantic Web and Information Systems 5 (3): 1–22. doi:10.4018/jswis.2009081901