By Emily Goligoski (“In Conversation” Video Producer, Women 2.0)

Among the many information discussions at Data 2.0 this week, we recognized:

It’s important to focus on citizens’ responsibilities not just as voters, but as information advocates. The conference at UCSF started with a comparison of different cities’ offerings (with SF celebrating census data mashups, NY offering a way to filter the city’s checkbook, and Chicago bringing transparency to government contracts). The core theme? Much of this information wasn’t consolidated with public consumption in mind, and it’s up to citizens to start optimizing it for public usage. “Mediation by talented by community members in important for these apps,” the City of San Francisco’s Director of CRM told open data fans. “Government isn’t always the delivery mechanism, and it’s important that we become more involved as individuals in making and keeping this public information usable.”

Between the day’s other conversations about the API economy and “enlightened IT” (which takes a more collaborative approach to making data usable by businesspeople), the lack of diversity in the room was startling. Anthony Goldbloom, whose data prediction platform Kaggle just unveiled a predictive algorithm contest for patient data, said he’s gotten used to seeing few women working in the space. Of the tens of thousands of people who enter his company’s data science competitions annually, he says he remembers only one woman registrant among the professionals who work in statistics, computer science, engineering, and physics. Citing degree disparity, Goldbloom said he’s so concerned with the low level of female engagement that he wonders if men are just more competitive.

Following conference keynote speaker Vivek Wadhwa’s piece “Women of Color in Tech: How Can We Encourage Them?” this week, it was disappointing to see a room of approximately 10 percent women, several of them press. But I don’t blame the conference — if anything, the audience represented the work that still needs to be done to get more women working in opening data.