Summit on Digital Tools for the Humanities–Day Two

Wow. That’s a lot for one day. This is a break down of the major points of interest. I won’t parcel these out into tools because a single tool might incorporate many of these attributes.
Major points of need that came up:
*collaboration (within and across projects),
*basic tools that do “basic” scholarly primitives *
*institutional structures [tenure, peer-review, repostitory so that *projects aren’t duplicated],
*continued open source
*participation, “training” courses are not a good idea-people need to be invested in what they are doing; the U.S. needs a system like EPOCH as a repository for differnt tools and projects.
*richer data;
*standards and documentaion (or tools that switch across different formats);
How:
Simplify tools–low threshhold, high ceiling; easy to play but very sophisticated for knowledge production; we need teams that collaborate and provide training;
*A tool wiki (isn’t this like Tapor?) where you can go to get documentation and to get the tool.
*Multiplayer gaming environment to facilitate different perspectives and engaging with the tool;
*Record keeping; processing that data for documentation.
Knowledge brokering system that allows us to tap into the various domains; a way of defining our
functional requirements in an open way, a team driven process.
Limits: immense cost in dollars and time in creating data; these environments require rich data.
research methods: reading, finding/discovering/seraching; comparison; interpretation; interrelating and interreferencing; self-reflection; collection building; collecting data; selection/exclusion; filtering;authenticity analysis; evaluation; copus statistics; analysis; modeling/representation; classification/ontologies; statistical analysis; geographic spatial coordinating; visualization; temporal coordination; chaos; ordering/arranging; patter recognition/representation; conjecture; serendipity;
challenge: developing new methods; defining research; research methods vs. dig res. methods;
defining canonical list of methods not possible w/out tech.; facilitating the development of new
methods; improving effectiveness and efficiency of existing methods (traditional methods and digial
methods); ambiguity/uncertainty representation;
classification tools; collaboration; simulation; method standards; data modeling; encourage
collaboration (all scholars with all scholars); methodology [teaching methodology (self
reflection); applying methodology; methods should inform tools];
Question of the day:
If we’re on an island and they’re not coming to get us, what would we want to reproduce and what not? What would be intellectually rewarding?