Several weeks ago, I was invited to speak to an audience of IT and business leaders at Walmart about the Language of Discovery. Every presentation is a feedback opportunity as much as a chance to broadcast our latest thinking (musicians call it trying out new material), so I make a point to share evolving ideas and synthesize what we've learned since the last instance of public dialog.
For the audience at Walmart, as part of the broader framing for the Age of Insight, I took the opportunity to share findings from some of the recent research we've done on Data Science (that's right, we're studying data science). We've engaged consistently with data science practitioners for several years now (some of the field's leaders are alumni of Endeca), as part of our ongoing effort to understand the changing nature of analytical and sense making activities, the people undertaking them, and the contexts in which they take place. We've seen the discipline emerge from an esoteric specialty into full mainstream visibility for the business community. Interpreting what we've learned about data science through a structural and historic perspective lead me to draw a broad parallel between data science now and natural philosophy at its early stages of evolution.
We also shared some exciting new models for enterprise information engagement; crafting scenarios using language of discovery to describe discovery needs and activity at the level of discovery architecture, IT portfolio planning, and knowledge management (which correspond to UX, technology, and business perspectives) - demonstrating the versatility of the language as a source of linkage across separate disciplines.
We continue to identify new frontiers for the language of discovery - I'm looking forward to sharing some of this work soon.