The Third Annual State Data Conference: Is Connecticut Falling Behind?
November 15, 2001
The Third Annual State Data Conference brought together data users, collectors and providers to share the latest developments in Connecticut and to discuss the needs of our data community. The broad objective of this conference series was to create an ongoing symposium for those involved in different stages of data generation, archiving, distribution, and use so they can exchange information on current data availability, the challenges they face, their particular needs, and their expectations (or hopes) for future developments. This third in a series of conferences continued the conversation begun at the first two. Participants in the one-day meeting came from various sectors, including government agencies, academic scholars, private enterprise and non-profit organizations.
The organizing theme of this third conference focused on the question of whether Connecticut was falling behind in its efforts to develop and provide data to data users. Ten presenters explored various facets of this question in three sessions.
- The first session put the 2000 Census in context, looking at who we are and how we’ve changed.
- The second session examined three ongoing initiatives to build access to Connecticut data.
- Finally, the last session explored the many benefits of digital spatial mapping.
Challenges, Initiatives and Future Directions for Connecticut’s data system.
The conference theme “Are we falling behind?” likely articulated a fear common among data providers and data users everywhere. There will probably always be concerns about the appropriate provision of information to a community of data users. Part of the reason is that, as with any other scarce commodity, the provision of data involves opportunity costs.
Since we have to give up other goods and services to produce data, we will (quite rationally) never produce the full quantity or quality of data we are technically capable of producing. What’s more, this calculus is complicated by information’s often unpredictable value, a characteristic that makes it easy to underestimate information’s true worth. After a busy news day, for example, a newspaper may be worth far more than its price to the reader. After a slow news day it may be worth far less.
Thus, for long stretches of time some information may seem worthless, and then it may suddenly assume limitless value at a critical moment. Still another reason for the perceived dearth of quality data is that information often takes on the characteristics of a public good—once produced,it becomes difficult to limit data access to paying users only. That reduces the incentive of providers to offer it in sufficient quantity or quality. Because of these challenges to the efficient operation of markets for data, data collection and dissemination is often organized through quasi-public and government agencies, as in the case of the U.S. Census.
Complete Final Report (including links to the websites cited during the conference)