(photo by dubai.digital. Flickr, creative commons)
I am honored to announce the wonkiest buzzword ever. Taxonomy. For those of you who don't traffic in test-prep vocabulary, a taxonomy is "the practice and science of classification," or, as I like to think of it, a taxonomy is a way of organizing stuff. Some taxonomies we use all the time and don't think about them. (Who did put the alphabet in alphabetical order?) Others need to be created, modified, crowdsourced, and monitored.
Why would such a deep down, tactical-to- the-bone-level word ever rise to the level of buzz?
Because of metrics. And standards. And maps. And networks. And ratings. And giving portfolios.
And mashups. And online searchable databases of volunteering opportunities. In other words, without taxonomies, none of the other big ideas - measuring, aggregating, timing, ranking, diversifying, collaborating - that might improve social action and philanthropy are possible.
Once we start trying to measure, rank, list, search or find we realize we need categories. Some taxonomies have been around for a long time - The Urban Instititute's NTEE codes, The IRS and The Foundation Center for example have been classifying social sector activities for decades.
And now we have data everywhere. And all kinds of tools for mashing it together into maps, or lists, or ranking systems, or twitter streams. These tools could lead to breakthroughs in our understanding of who is doing what and what really works on various social issues. But we can't connect the maps to the data without taxonomical agreement. And we can't efficiently and effectively search multiple databases without knowing what taxonomy to use. And we can't see all the activity in a certain region or rate one nonprofit against a sector or rate one organization against another or compare one foundation to another, without agreeing on what we're going to call apples and what we are going to call oranges.
Taxonomies are labor intensive, and tactical, and operate, literally, at the "code" level - but without them (and agreement on them) we can't see the bigger picture. Those who are working away on taxonomies - from the IRIS-Standards and Pulse folks, to the Foundation Center experts for Philanthropy Insight, to the Grants Managers Network whose members seem to live and die by taxonomies - are setting the stage for aggregation of data that matters.
We might (soon) be able to search online for organizations that can provide evidence that their programs improve graduation rates in inner city schools - but not without an underlying taxonomy that connects work on metrics to work on programs to databases of nonprofit organizations to a zip code directory. In other words, not without a shared taxonomy. And we may one day be able to see how much money from philanthropy, political contributions, corporate sponsors, and the public sector is going into research on various health care reform proposals - but not without functioning taxonomies that can be connected across data centers.
The buzz about taxonomies has ebbed and flowed over time. It is building again now because of the widespread availability of computing power that makes data crunching possible, the adoption of cloud based data centers that allow info to be pulled across platforms, the migration of data wonks into philanthropy and the social sector,* the general expectation that if the data exist we should be able to find them (thank you search engines), and the hard work of organizations as varied as IssueLab, GuideStar, NeighborWorks America, GivingUSA, SoCap, GreaterGood South Africa, the Opportunity Finance Fund, Kiva, MyC4, TechSoup, The Sunlight Foundation, and New Philanthropy Capital who have been trying to find, organize and use data on nonprofits and/or social enterprises for years now.
The buzz is is also building because of the cycles of technology and information use in the nonprofit world. First we have no data. Then we have too much data. Then we find ways to make sense of what we have. Then we need more data. Which means we don't have data. Until we have too much data. And then we'll find ways to make sense of the data we have. And repeat. Don't get me wrong - this cycle is a good thing. Over the years the problem underneath the cycle has influenced the founding of the Foundation Center, GuideStar, and Kiva, among others. It has driven individuals to smoosh together maps with databases and databases with network analysis software. And it will soon lead us to smoosh data with data and data with pictures and data with who-knows-what else if it will help us understand the world a little better. All of it is about sense-making. And all of it requires taxonomies.
*An undervalued contribution of the Obama administration and tech fortunes, IMHO.