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When faced with a patent case, it is essential to find “prior art” – patents and publications that describe a technology before a certain date. The problem is that the indexing mechanisms for patents and publications are not as good as they could be, making good prior art searching more of an art than a science. We can apply some of our natural language processing and “big data” techniques to the US patent database, getting us better results more quickly.
Van is a software engineer and practicing lawyer at Haynes and Boone, where he spends most of his time helping clients with patent and open source questions. His specialty is translating from “lawyer” to “engineer” and back.
Van has been involved with open source since 1994. He speaks and writes regularly on open source issues, and has been recognized as an authority on open source licensing. He published his first book on open source software and intellectual property law and is working on a second book addressing the economics of open source.
Before becoming a lawyer, Van was a research and development engineer at NTT/Verio, building automation tools and distributed systems. Van still writes software in his spare time. He is a member of and counsel for the Python Software Foundation and is currently chairman of PyCon.
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