A brief history of markup of social science data: from punched cards to "the life cycle" approach
August 2, 2010
Traditional quantitative social science data analysis requires three ingredients: the raw data, metadata (what we used to call a codebook), and software. Software changes all the time, within some limits. Raw data without metadata is useless: it might as well be generated by a random number generator. And metadata without data is like the index to a periodical the last remaining copy of which was sent for recycling last month. Over time, metadata have been expected to support many different functions, and microsolutions have never quite satisfied many, much less all, of those functions. Until recently, that is: a roughly 25-year process of historical evolution has led to DDI, the Data Documentation Initiative, which unites several levels of metadata in one emerging standard.