Capstone came and went today without seeing anyone from my Master’s class talk. Instead of six talks, there were cancellations that whittled it down to just three — two HCI and one Bio. All three were students a while back, only now finishing off the capstone work.
- Tara Blazer — I only caught the tail end of this first talk due to dropping the Biggest Kid off in the morning (9a is also the start of Elementary school). This project focused on caring for seniors, taking some approaches similar to what we discovered with mPath a couple years back. There were some nice insights that acknowledged that future seniors will be more computer literate (to the point of expecting and demanding computer tools for their care) and that people were important in the caregiving process. I played catch-up trying to figure out the purpose of the project, but the work seemed very thorough. I wonder how much it evolved over the course of the past four years.
- Kristin Hanks — “iFind Indiana” is a search tool based on extensive research on people with disabilities. That group comprises 10-20% of population (800,000 in Indiana alone). Kristin told the story of her process with effective slides and an engaging manner, although that story was a little long as it circled around the eventual solution. The cliff notes are: Plenty of printed information exists to help disabled people, but it immediately becomes out-of-date; Online tools are “glorified yellow pages”; Most people don’t know what questions to ask; Consumers readily use the computer but trust human resources most. All of these things led Kristin to focus on a system that addresses the problems of existing online tools — Semantics (systems use words that real people don’t use, like “employment” instead of “job”), Search & Database interface (it isn’t intuitive and often leads to no results), and Network issues (focus on large hubs, overlooking small organizations that might be the best fit for the consumer). She dubbed the desire to reject the frustating search tools as “Google Flight.” Rather than apply her research to existing sites or create something from scratch, Kristin’s strategy was to synthesize existing systems.
- Di Ren — A bioinformatics talk entitled “A library of orthologue Protein Clusters from Multiple Yeast Proteomes,” Di’s solution was to create a search tool that accepted a genetic sequence and then checked against data libraries to find matches among yeast genomes. S.cerevisiae was the first Eukaryotic genome sequenced (yeast from bread and beer) and is used to help understand the molecular mechanism involved in generation and duplication. To build the search tool, Di clustered sequences in elevent NIH genome library files into one big file. He then processed the big file using BLAST repeatedly, and then dealt with multi-alignment of protein sequences using CLUSTALW, a general-purpose program that calculates the best match for biologically meaningful alignments of divergent sequences. After three years of listening to science capstones, I’m still not entirely sure what all that means, except that it is taking a lot of data and massaging it into useful information. the web site — which allows a biologist to enter a query sequence, returning corresponding yeast proteins — is an HCI/d capstone waiting to happen.
