Current Issues or Challenges in Visual Analytics

A Promising and Active Area, but Facing many challenges Process aspect How does an analyst work? “Don’t make me think”  “Help me think quickly and effectively” How do a group of analysts work? Group dynamics + visual analytics Data aspect Scalability of data Tools for small data sets may work for large data sets. Quality of data Data is often messy. Model aspect Only considering data attributes Distributions, types, etc. How about user interaction? Knowledge aspect What new knowledge to provide What do they know already?

Process Aspect

Theory on Visual Analytics Visual analytics process always involves complex problem-solving, decision-making activities Tasks, cognition, etc. Not just another user interface design Users often need to switch among different levels of skills, routines, and knowledge

Theory on Visual Analytics Visual analytics process always involves complex problem-solving, decision-making activities Tasks, cognition, etc. Not just another user interface design Users often need to switch among different levels of skills, routines, and knowledge However, we don’t have a good theory, yet!

Collaborative Visual Analytics Analyzing big data often requires team work. How to work effectively as a team? Social aspects Complicated issues. Task aspects How to make collaborative analytics successful?

Visual Analytics Tasks Some tasks can be easily managed in a team. e.g., Team research reports in IST 220 Some may not. e.g., your team project How to support such collaboration? Information artifacts Visualization tools

Team Knowledge Distributed expertise Bias Divide tasks into subtasks Integrate results from individual experts Bias People favor information they are familiar with and down- play information they don’t know much How to make information analysis more objective? An Example: Collaborative Visual Analytics in Emergency Management

Public Works Environmental Mass Care

CIVIL: Support Collaborative Visual Analytics in Emergency Management Chatting Tool Sorting Table Aggregation Chart Contribution Timeline Private Map Public Map Let’s review the main components of this interface. Users can draw and comment on both private map and public map. The difference is things on the private map can only be seen by the creator, while on public map, all the collaborators can see the shared comments, sketches, and also the others’ cursor. Users can sort the information based on a certain attribute in sorting table, aggregation chart compare different options, here are the four shelters. Contribution timeline shows individual contribution history. All the items are color-coded by roles and hyperlinked to each other. By clicking one item on the aggregation chart, it will highlight the corresponding items on the map, the sorting table, and the timeline. Most importantly, we found that this web-based design is valuable when people using different machines to work together. No complex installation is needed as long as you have a browser and flash.

Video Demo

Data Aspect

What Did You Do to understand and structure data for Your Project Data?

Data Understanding data is usually a prerequisite for using algorithms and visualization tools Social media data: who, what, how, etc. Intelligence reports It is a challenge to have a deep understanding of big data. Appropriate tools to get good, representative snippet. E.g., twitter data Find unique, but crucial information

Structuring Data for Visualization Data can be structured different from what a visualization tool can support, or totally unstructured. Example: Social networks Data formats

Data Format <?xml version="1.0" encoding="UTF-8"?> graph [   node   [    id A   ]   node   [    id B   ]   node   [    id C   ]  node    [    id D   ]   node   [    id E   ]   edge   [    source B    target A   ]   edge   [    source C    target A   ]   edge   [    source C    target B   ]   edge   [    source C    target E   ]   edge   [    source D    target E   ]   edge   [    source D    target B   ] ] <?xml version="1.0" encoding="UTF-8"?> <gexf xmlns="http://www.gexf.net/1.2draft" version="1.2"> <meta lastmodifieddate="2009-03-20"> <creator>Gexf.net</creator> <description>An Network Example</description> </meta> <graph mode="static" defaultedgetype="directed"> <nodes> <node id="0" label="A" /> <node id="1" label="B " /> <node id="2" label="C" /> <node id="3" label="D" /> <node id="4" label="E" /> </nodes> <edges> <edge id="0" source=“1" target=“0" /> <edge id=“1" source=“2" target=“0" /> <edge id=“2" source=“2" target=“1" /> <edge id=“3" source=“2" target=“4" /> <edge id=“4" source=“3" target=“3" /> <edge id=“5" source=“3" target=“2" /> </edges> </graph> </gexf>

Structuring Data for Visualization Data can be structured different from what a visualization tool can support, or totally unstructured. Example: Social networks Data formats Constructing social networks based on different sources public forum activities (e.g., reddit) email messages co-presence in an event other social ties (e.g., hometown, school, race, etc.)

Model Aspect

Models/Algorithms Data-oriented Have various assumptions Data types, distributions, ranges, etc. Usually don’t consider interactivity with users A black box model

01010101010

01010101010

An Analogy for You to Think How much do you trust results from search engines? Considering the fake news stories, do you trust search engines more or less?

An Analogy for You to Think Visual Analytics Online Search Raw data Sources on Internet Data models Indexing algorithms Results Search results

How Much Should We Trust Algorithms/Models?

Knowledge Aspect

Who Are Our Audiences? How much do they know? Data, visualization tools, algorithms, etc. Think about graphic user interfaces Different kind of users Expert users: efficiency, almost error-free Novice users: easy to use People’s prior knowledge may not be what you think.

Effective Communications https://www.youtube.com/watch?v=jbkSRLYSojo http://www.gapminder.org/tools/#_locale_id=en;& chart-type=bubbles

Summary

Adding Them Up New theoretical models on visual analytics Individual work process Group process New design practices Integrating data (data collectors), algorithms (algorithm designers), users (analysts), and audiences together. Considering these stakeholders in the beginning New system models Complex data and algorithms: web-based services may not be good enough. May demand super computers. Supercomputers are not service-oriented!

Wednesday I will talk to individual groups. I expect all group members show up. Show me your progress and status of visualization designs Should have something right now!

Extra Credit Opportunity Participating a study on gesture-based user interaction 1 point