What Does It Look Like, Really? Imagining How Citizens Might Effectively, Usefully and Easily Find, Explore, Query and Re-present Open/Linked Data

摘要

Are we in the semantic web/linked data community effectively attempting to make possible a new literacy - one of data rather than document analysis? By opening up data beyond the now familiar hand crafted Web 2 mash up of data about X plus geography, what are we trying to do, really? Is the goal at least in part to enable net citizens rather than only geeks the ability to pick up, explore, blend, interogate and represent data sources so that we may draw our own statistically informed conclusions about information, and thereby build new knowledge in ways not readily possible before without access to these data seas? If we want citizens rather than just scientists or statisticians or journalists for that matter to be able to pour over data and ask statistically sophisticated questions of comparison and contrast betewen times, places and people, does that mission re-order our research priorities at all? If the goal is to enpower citizens to be able to make use of data, what do we need to make this vision real beyond attending to Tim Berners-Lee's call to "free your data"? The purpose of this talk therefore will be to look at key ineraction issues around defining and delivering a useful, usable *data explorotron* for citizens. In particular, we'll consider who is a "citizen user" and what access to and tools for linked data sense making means in this case. From that perspective, we'll consider research issues around discovery, exploration, interrogation and representation of data for not only a single wild data source but especially for multiple wild heterogeneous data sources. I hope this talk may help frame some stepping stones towards useful and usable interaction with linked data, and look forward to input from the community to refine such a new literacy agenda further.