1. Semantic Visualization What do we mean when we talk about visualization? - Understanding data - Showing the relationships between elements of data Overviews Changes The context of information can be set with semantic information

2. A Geospatial Web A set of semantic ontologies to organize information Searching semantic data can be contextually driven - Does searching become browsing with semantic information defaults? - Personalized results based on matching the semantics of your situation & the data? People, interfaces, search systems & information resources

3. Beyond Keywords Semantics take us beyond keywords - How far beyond? - Exposing metadata? “the structure of the posted data is flat” - What about existing & derived metadata? GML helps with geospatial information - But users still need to understand what they’re looking at - Subtleties of understanding are complex Time * Place vs. Time / Place

4. Lakes in Maine Find “lakes in Maine” User sees lakes by counties in Maine Matching US geometry & lake information Distinctions between lakes inside Maine & actual lake location Understanding of what a lake is, typical uses of lake data, etc. Users will have more facets of their query exposed, with some good initial guesses as to their intention with the query

5. Geospatial Semantics Natural language with minimum markup - HTML, XHTML, META tags, naming conventions Simple metadata - XML, Dublin Core, Links Data models - RDF for relationships, better interfaces Logical semantics - Automated reasoning to determine correspondence among queries & real-world entities Is this easy (easier) because it is real world based?

6. A Geospatial format Another flavor of XML to help with this complex relationship - Geospatial format for queries - Assessment metrics for matching queries & noting precision & recall What is the best format for storing geo semantics? What is the best way to present this to users? - Map coordinates? Map coordinates? - Drill down? Drill down?

7. A Conversational Web Mapping There are many ways to map information Non-physical methods are the most challenging, but also potentially the most interesting - From an additive, metadata view Netscan project - “Qualitative data in a quantified setting” - Is it possible to extract semantics from this? What would you need to know to make use of this data?

8. Semantic Structures? Usenet is organized into groups These groups fit a complex taxonomy Mostly text - Annotations (threads) - Date & Time - User ID Variance among groups - Posting vs. Conversing - Topic influences post types - Contributions

9. Let’s take a look at a map

10. Are groups changing? Alt.binaries is growing, changing usenet from conversation to file exchange Areas of usenet are popular, and shifting - SPAM - Alt groups change - More users online = more potential conversations? - Corporate or intended use of groups

11. Special purposes & replies

12. Semantic Interactions How are people changing online? What is the metadata than can be derived & shown or used semantically? How can you understand posting conventions automatically? - Question, reply, trolls, flamer, chatter Does this analysis help us understand the conversations visually? - What about any kind of understanding, even generally?

13. Blog Conversations Blogs provide us with some extra semantics by default

14. TagClouds What could be better with tag clouds? - Delicious Delicious - NY Times NY Times - Flickr Flickr - Yahoo News Yahoo News

15. Semantic Interfaces or Maps? - Tag Cloud Gallery Tag Cloud Gallery - 5 Alternate Ways to Browse Amazon.com 5 Alternate Ways to Browse Amazon.com - Many Eyes – Semantic Many Eyes – Semantic - MindRaider (Outliner) MindRaider (Outliner) - Bioinformatics Bioinformatics