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Many organizations, such as publishers, technical societies, membership associations, libraries, and government agencies all have unique collections of valuable content that are rarely seen. In these days of big data, you might be asking, "Who needs even more data?" But yes, even in age of information, there is a need for well-considered, thoughtfully curated content, and some of that might be in your archives, or maybe in boxes somewhere in the basement.
The opportunities for monetizing that content today are better than ever. Improved tools and techniques have reduced the cost of high-quality digitization. And the internet has dramatically increased potential audience size: today you can widely sell your content over the web to audiences you might never have known existed. Improved search technology, specialized aggregators, and the cloud make your content much more discoverable. People no longer need to travel thousands of miles to see unique materials, and they don't even need to touch them (which should make many archivists smile).
Some collections I've seen have included mountaineering maps and images, letters and papers from famous people that have been contributed to a university library, specialized image collections, diaries of Civil War officers, scientific journals dating back decades and even centuries, vintage car repair manuals, movie magazines from the golden age of cinema...the list is endless.
Such collections present opportunities for dissemination and monetization, yet some consideration is required to make archives alive again. Following are some key steps I'd recommend.
1. Identify what you have: How many pages of material exist? How complete is it? What formats is it in (paper, microfilm, electronic files, etc.)? And what condition is it in? All this lets you identify value and cost.
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Mark Gross, president of Data Conversion Laboratory (DCL), is an authority on XML implementation and document conversion. Prior to joining DCL in 1981, Gross was with the consulting practice of Arthur Young & Co. He has a B.S. degree in Engineering from Columbia University and an MBA from New York University. He also has taught at the New York University Graduate School of Business, the New School, and Pace University. He is a frequent speaker on the topic of automated conversions to XML and SGML.