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A D V A N C E D M A T E R I A L S & P R O C E S S E S | N O V E M B E R / D E C E M B E R 2 0 1 9 1 8 on the type of organization: small start- up, large corporation, university, gov- ernment research lab, or even national government agency. Despite differences in the specif- ic business drivers, they can all be ad- dressed by a finite group of simple business questions, which typically are based on who, what, where, when, and how, or any combinations of these, as il- lustrated in the Fig. 1 examples. It is only after the business drivers and relevant business questions have been defined that patent analytics are introduced. Typically, these analytics are visual rep- resentations of rankings, trends, or re- lationships that address the relevant questions. As highlighted in the side- bar, patent analytics might be provided within the software and/or service used to gather patent data, or they can be developed with the assistance of other popular data handling software pack- ages or more powerful statistical and semantic analysis tools. Analytics addressing these spe- cific questions can be developed from typical patent data. For example, a pie chart may illustrate the top assign- ees (i.e., who) in any given technology area, or a line graph may show patent- ing time trends (i.e., when) for a given technology. These various information components might also be combined in a variety of ways to address more complex questions (e.g., a timeline of patenting activity of themost prolific in- venting entities within a specific region to address who, when, and where in a single analytic). Once the appropriate patent ana- lytics are defined and developed, they need to be further interpreted in light of the technology/business/legal issues of concern to lead to patent intelligence— the combination of the analytics and the observations and insights derived from them. Only with this interpretation of the analytics can an organization define an action plan to address the original business drivers. One can imagine a fairly exten- sive array of drivers and questions that might be addressed in any single pat- ent study. However, after undertaking hundreds of patent intelligence stu- dies, we often find a core set of driv- ers, questions, and analytics that ad- dress a broad range of organizational types, functions, and stages of business development. R&D FUNCTION—EARLY STAGE Driver: An advanced materials company’s R&D has particular exper- tise in nano-sized materials fabrication and wants to explore opportunities for commercial exploitation of these technologies. Questions: What end-use appli- cations of nanomaterials that are po- tentially being commercialized, as evidenced through patent filings, might be considered for internal R&D invest- ment? When have these patents been filed and, specifically, what end-use ap- plications appear to be more recent and therefore possibly emerging? Patent Analytics: A variety of pat- ent analytics can be designed to visual- ize key technology themes and trends within the nanotechnology area. For example, the ThemeScape map shown on the first page highlights several end- use applications of nanotechnology described in patents filed globally be- tween 2000 and 2015 based on seman- tic analysis and clustering of textual similarities of select patent fields (in this case, the Derwent World Patent Index “Use” field). In this map, each dot rep- resents an invention, and the distances between inventions are determined by similarity in their textual content; the closer the location, the higher the sim- ilarity. Superimposed on these are key high-level themes that summarize this information, revealing particular focus in the areas of microelectronics, power applications, optical materials, environ- mental applications, and life sciences. While this ThemeScape map pro- vides information regarding what technologies are active in this area, additional actionable insights may be gained through “time slicing” the map. This would help to identify when the technologies have been developed to differentiate those that are emerging vs. those that are declining in activity. The discovery of technology themes and time trends can be further refined with greater precision by first designing a “taxonomy” that predefines specific technology categories of inter- est and then categorizing each patent into one or more of these “buckets” through semantic and patent classifica- tions analysis. Figure 2 is an example of this deep-dive categorization, showing Fig. 2 — Detailed categorization of nanotechnology patents using pre-defined categories, 2000-2015.