VantagePoint is a professional-grade desktop text mining application offering Analysts a broad suite of powerful refining, analyzing, and reporting tools for scientific, technical, market and patent information.
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VantagePoint in Global Research: Books, Publications, and Case Studies
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VantagePoint is not locked into any one data source. Whether you are analyzing publications, patents, or internal data, VantagePoint’s import tools are designed to process information from a wide variety of sources. Browse the Library to see if your key data resources work with VantagePoint or Contact Us if you have a question about your data.
From Excel® to XML, and pretty much anything in between, from patent and publication databases to mining your own email, VantagePoint’s ability to import, refine, analyze and report enables you to transform analysis into insight.
Tech Mining extracts high value intelligence from science & technology (“S&T”) information resources, usually research publications or patents. We can perform Tech Mining on the topic or organization of interest to you.
Such Competitive Technical Intelligence (CTI) enables more effective technology management, including Open Innovation. That is, you can draw more effectively upon external R&D. And, vice-versa, you can identify who else could gain from licensing your intellectual property. Put another way, Tech Mining helps you answer Who? What? Where? and When? about emerging technologies that could pose vital threats and opportunities.
Here’s how it works:
Most of our Tech Mining is done for companies and is proprietary. But, to illustrate the sort of R&D profiling that we do, here’s snippets from a recent national level case analysis. Here, we spotlight US vs. Canada R&D publication comparisons (we also examined patents).
This case profiles photonics research to benchmark Canadian against American research. We devised a multi-part search strategy, informed by expert feedback, for this wide-ranging topic. Figure 1 shows 10-year R&D trends -- suggesting Canadian gains relative to the US.
Estimating the percentage of R&D from industry provides one of many possible innovation indicators (albeit with important nuances). Compare the Canadian and US sector breakouts for 2008 (Figure 2) -- corporate participation favors the US (12% vs. 7% for Canada). We probed further to investigate the extent of cross-sector collaboration. In the US, 11% of the academic papers also had an author with a corporate affiliation. Such cross-sectored research networking appears important for regional innovation initiatives (“clusters”).
We compare topical emphases at 3 levels of detail: key words & extracted title phrases, subject categories & macro-disciplines. We found differences -- e.g., relatively more Canadian (vs. US) photonics research in Physics (45 vs. 38%) and less in Materials Science (33 vs. 38%).
We also examined particular research institutions to discern special strengths. Tech Mining allows us to break out whatever available fields of information we want, for selected organizations. This table profiles photonics research activity for three leading US “institutes of technology.”
The research profiles break out for each organization:
Not shown here, we also compared macro-disciplines; Caltech emphasizes Physics, while Georgia Tech evidences more Materials Science. We also provided a “quality metric” (not shown here) – the extent to which each organization’s research is cited by others (all three were close).
Figure 3 overlays the photonics research concentrations on a base map of science. Here we quickly grasp that photonics research reaches into many fields. So, if you want to bolster R&D leading to economic returns, promote cross-field collaboration.
So, do you need to know what’s happening in certain emerging technologies?
What a competitor is pursuing?
SEARCH TECHNOLOGY, Inc., provides empirical Science, Technology & Innovation (ST&I) research & analyses for government and industry.
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VantagePoint is a powerful desktop text-mining tool that helps you quickly navigate through large volumes of structured text to see patterns and relationships.
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