ITSD anchors its work around multi-faceted, agile teams of researchers who reach across academic disciplines and take advantage of each researcher’s particular background and skills. ITSD researchers possess a broad range of operational, policy, organizational, and technical skills. Their backgrounds cluster primarily in engineering, computer science, economics, political science, and the social sciences. Ninety-three percent of the staff hold graduate degrees, about half of which are at the doctorate level. ITSD also hires and maintains a significant cadre of adjunct research staff members and consultants with extensive military and/or national security experience in cyber to support our sponsors.
ITSD researchers apply their strong analytic reasoning and critical-thinking skills to identify emerging game-changing challenges and solutions that will shape future cyberspace science and technology, research and development, policy, and investment agendas. They are able to develop the broader context (the big picture) of a problem, identify its key components, create and execute an appropriate analytic methodology, and clearly convey their findings to specialists and non-specialists alike. ITSD’s goal is to deliver objective, evidence-based, actionable analyses and advice focused on results.
Cyberspace is constantly evolving. ITSD continually refreshes its staff expertise in new fields to meet its sponsors' needs. ITSD values researchers with excellent communication and technical skills who can use those skills to understand sponsors' challenges and priorities, provide recommendations, and analyze issues and solve problems.
2016 Larry D. Welch Award for Best External Publication
2016 Larry D. Welch Award for Best External Publication winners, Arun Maiya, Dale Visser, and Andrew Wan, Information Technology and Systems Division
In their article “Mining Measured Information from Text(Open external link)(Open external link)(Open external link)(Open external link)(Open external link)(Open external link)(Open external link)(Open external link)(Open external link)” Arun Maiya, Dale Visser, and Andrew Wan of the Information Technology and Systems Division, presented an approach to extract measured information from text (e.g., a 1370° C melting point, a BMI greater than 29.9 kg/m2). Such extractions are critically important across a wide range of domains – especially those involving search and exploration of scientific and technical documents. The authors first proposed a rule-based entity extractor to mine measured quantities (i.e., a numeric value paired with a measurement unit), which supports a vast and comprehensive set of both common and obscure measurement units. Their method was highly robust and could correctly recover valid measured quantities even when significant errors were introduced through the process of converting document formats like PDF to plain text. Next, they described an approach to extracting the properties being measured (e.g., the property pixel pitch in the phrase “a pixel pitch as high as 352 μm”).Finally, they presented MQSearch: the realization of a search engine with full support for measured information.
Their paper was published in the Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, August 2015.