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The Intelligence Advanced Research Projects Activity recognized the scale problem in 2011, creating the research program Foresight and Understanding from Scientific Exposition. Under this program, SRI and other performers processed “the massive, multi-discipline, growing, noisy, and multilingual body of scientific and patent literature from around the world and automatically generated and prioritized technical terms within emerging technical areas, nominated those that exhibit technical emergence, and provided compelling evidence for the emergence.”<ref name="DNIIARPA11">{{cite web |url=https://www.dni.gov/index.php/newsroom/press-releases/press-releases-2011/item/327-iarpa-launches-new-program-to-enable-the-rapid-discovery-of-emerging-technical-capabilities |title=IARPA Launches New Program to Enable the Rapid Discovery of Emerging Technical Capabilities |publisher=Office of the Director of National Intelligence |date=27 September 2011}}</ref> The work presented here applies and extends that platform to efficiently identify and describe the past and present evolution of research on a given set of materials. This work applies text analytics to demonstrate how these computational tools can be used by analysts to analyze much larger sets of data and develop more iterative and adaptive material assessments to better inform and shape government and industry research strategy and resource allocation. | The Intelligence Advanced Research Projects Activity recognized the scale problem in 2011, creating the research program Foresight and Understanding from Scientific Exposition. Under this program, SRI and other performers processed “the massive, multi-discipline, growing, noisy, and multilingual body of scientific and patent literature from around the world and automatically generated and prioritized technical terms within emerging technical areas, nominated those that exhibit technical emergence, and provided compelling evidence for the emergence.”<ref name="DNIIARPA11">{{cite web |url=https://www.dni.gov/index.php/newsroom/press-releases/press-releases-2011/item/327-iarpa-launches-new-program-to-enable-the-rapid-discovery-of-emerging-technical-capabilities |title=IARPA Launches New Program to Enable the Rapid Discovery of Emerging Technical Capabilities |publisher=Office of the Director of National Intelligence |date=27 September 2011}}</ref> The work presented here applies and extends that platform to efficiently identify and describe the past and present evolution of research on a given set of materials. This work applies text analytics to demonstrate how these computational tools can be used by analysts to analyze much larger sets of data and develop more iterative and adaptive material assessments to better inform and shape government and industry research strategy and resource allocation. | ||
==Materials== | |||
===Ground truth=== | |||
The Department of Energy (DOE) has a specific interest in critical materials related to the energy economy. The DOE identifies critical materials through analysis of their use (demand) and supply. The approach balances an analysis of market dynamics (the vulnerability of materials to economic, geopolitical, and natural supply shocks) with technological analysis (the reliance of certain technologies on various materials). The DOE's R&D agenda is directly informed by assessments of material criticality. The DOE, the National Research Council, and the European Economic and Social Committee have all articulated a need for better measurements of material criticality. However, criticality depends on a multitude of different factors, including socioeconomic factors.<ref name="PoultonState13">{{cite journal |title=State of the World's Nonfuel Mineral Resources: Supply, Demand, and Socio-Institutional Fundamentals |journal=Annual Review of Environment and Resources |author=Poulton, M.M.; Jagers, S.C.; Linde, S. et al. |volume=38 |pages=345–371 |year=2013 |doi=10.1146/annurev-environ-022310-094734}}</ref> Various organizations across the world define resource criticality according to their own independent metrics and methodologies, and designations of criticality tend to vary dramatically.<ref name="CommitteeMinerals08">{{cite book |url=https://www.nap.edu/catalog/12034/minerals-critical-minerals-and-the-us-economy |title=Minerals, Critical Minerals, and the U.S. Economy |author=Committee on Critical Mineral Impacts on the U.S. Economy |publisher=National Academies Press |pages=262 |year=2008 |isbn=9780309112826 |doi=10.17226/12034}}</ref><ref name="CommitteeManaging08">{{cite book |url=https://www.nap.edu/catalog/12028/managing-materials-for-a-twenty-first-century-military |title=Managing Materials for a Twenty-first Century Military |author=Committee on Assessing the Need for a Defense Stockpile |publisher=National Academies Press |pages=206 |year=2008 |isbn=9780309177924 |doi=10.17226/12028}}</ref><ref name="ErdmannCritic11">{{cite journal |title=Criticality of non-fuel minerals: A review of major approaches and analyses |journal=Environmental Science and Technology |author=Erdmann, L.; Graedel, T.E. |volume=45 |issue=18 |pages=7620–30 |year=2011 |doi=10.1021/es200563g |pmid=21834560}}</ref><ref name="EurLex52011PC0025">{{cite web |url=https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52011DC0025 |title=Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Tackling the Challenges in Commodity Markets and on Raw Materials |work=Eur-Lex |publisher=European Union |date=02 February 2011}}</ref><ref name="PoultonState13" /><ref name="ECReport14">{{cite web |url=https://ec.europa.eu/docsroom/documents/10010/attachments/1/translations/en/renditions/pdf |format=PDF |title=Report on Critical Raw Materials for the E.U.: Report of the Ad hoc Working Group on defining critical raw materials |publisher=European Commission |pages=41 |date=May 2014}}</ref><ref name="GraedelCritic15">{{cite journal |title=Criticality of metals and metalloids |journal=Proceedings of the National Academy of Sciences of the United States of America |author=Graedel, T.E.; Harper, E.M.; Nassar, N.T. et al. |volume=112 |issue=14 |pages=4257-62 |year=2015 |doi=10.1073/pnas.1500415112 |pmid=25831527 |pmc=PMC4394315}}</ref> | |||
==References== | ==References== | ||
Revision as of 01:48, 22 May 2018
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| Full article title | Application of text analytics to extract and analyze material–application pairs from a large scientific corpus |
|---|---|
| Journal | Frontiers in Research Metrics and Analytics |
| Author(s) | Kalathil, Nikhil; Byrnes, John J.; Randazzese, Lucien; Hartnett, Daragh P.; Freyman, Christina A. |
| Author affiliation(s) | Center for Innovation Strategy and Policy and the Artificial Intelligence Center, SRI International |
| Primary contact | Email: christina dot freyman at sri dot com |
| Year published | 2018 |
| Volume and issue | 2 |
| Page(s) | 15 |
| DOI | 10.3389/frma.2017.00015 |
| ISSN | 2504-0537 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.frontiersin.org/articles/10.3389/frma.2017.00015/full |
| Download | https://www.frontiersin.org/articles/10.3389/frma.2017.00015/pdf (PDF) |
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Abstract
When assessing the importance of materials (or other components) to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of metadata analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. Approximately 438,000 titles and abstracts of scientific papers published from 1992 to 2011 were used to examine 16 materials. This analysis used coclustering text analysis to associate individual materials with specific clean energy applications, evaluate the importance of materials to specific applications, and assess their importance to clean energy overall. Our analysis reproduced the judgments of experts in assigning material importance to applications. The validated methods were then used to map the replacement of one material with another material in a specific application (batteries).
Keywords: machine learning classification, science policy, coclustering, text analytics, critical materials, big data
Introduction
Scientific research and technological development are inherently combinatorial practices.[1] Researchers draw from, and build on, existing work in advancing the state of the art. Increasing the ability of researchers to review and understand previous research can stimulate and accelerate scientific progress. However, the number of scientific publications grows exponentially every year both on the aggregate level and in an individual field.[2] It is impossible for any single researcher or organization to keep up with the vastness of new scientific publications. The ability to use text analytics to map the current state of the art to detect progress would enable more efficient analyses of data.
The Intelligence Advanced Research Projects Activity recognized the scale problem in 2011, creating the research program Foresight and Understanding from Scientific Exposition. Under this program, SRI and other performers processed “the massive, multi-discipline, growing, noisy, and multilingual body of scientific and patent literature from around the world and automatically generated and prioritized technical terms within emerging technical areas, nominated those that exhibit technical emergence, and provided compelling evidence for the emergence.”[3] The work presented here applies and extends that platform to efficiently identify and describe the past and present evolution of research on a given set of materials. This work applies text analytics to demonstrate how these computational tools can be used by analysts to analyze much larger sets of data and develop more iterative and adaptive material assessments to better inform and shape government and industry research strategy and resource allocation.
Materials
Ground truth
The Department of Energy (DOE) has a specific interest in critical materials related to the energy economy. The DOE identifies critical materials through analysis of their use (demand) and supply. The approach balances an analysis of market dynamics (the vulnerability of materials to economic, geopolitical, and natural supply shocks) with technological analysis (the reliance of certain technologies on various materials). The DOE's R&D agenda is directly informed by assessments of material criticality. The DOE, the National Research Council, and the European Economic and Social Committee have all articulated a need for better measurements of material criticality. However, criticality depends on a multitude of different factors, including socioeconomic factors.[4] Various organizations across the world define resource criticality according to their own independent metrics and methodologies, and designations of criticality tend to vary dramatically.[5][6][7][8][4][9][10]
References
- ↑ Arthur, W.B. (2009). The Nature of Technology: What It Is and How It Evolves. Simon and Schuster. p. 256. ISBN 9781439165782.
- ↑ National Science Board (11 January 2016). "Science and Engineering Indicators 2016" (PDF). National Science Foundation. pp. 899. https://www.nsf.gov/statistics/2016/nsb20161/uploads/1/nsb20161.pdf.
- ↑ "IARPA Launches New Program to Enable the Rapid Discovery of Emerging Technical Capabilities". Office of the Director of National Intelligence. 27 September 2011. https://www.dni.gov/index.php/newsroom/press-releases/press-releases-2011/item/327-iarpa-launches-new-program-to-enable-the-rapid-discovery-of-emerging-technical-capabilities.
- ↑ 4.0 4.1 Poulton, M.M.; Jagers, S.C.; Linde, S. et al. (2013). "State of the World's Nonfuel Mineral Resources: Supply, Demand, and Socio-Institutional Fundamentals". Annual Review of Environment and Resources 38: 345–371. doi:10.1146/annurev-environ-022310-094734.
- ↑ Committee on Critical Mineral Impacts on the U.S. Economy (2008). Minerals, Critical Minerals, and the U.S. Economy. National Academies Press. pp. 262. doi:10.17226/12034. ISBN 9780309112826. https://www.nap.edu/catalog/12034/minerals-critical-minerals-and-the-us-economy.
- ↑ Committee on Assessing the Need for a Defense Stockpile (2008). Managing Materials for a Twenty-first Century Military. National Academies Press. pp. 206. doi:10.17226/12028. ISBN 9780309177924. https://www.nap.edu/catalog/12028/managing-materials-for-a-twenty-first-century-military.
- ↑ Erdmann, L.; Graedel, T.E. (2011). "Criticality of non-fuel minerals: A review of major approaches and analyses". Environmental Science and Technology 45 (18): 7620–30. doi:10.1021/es200563g. PMID 21834560.
- ↑ "Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Tackling the Challenges in Commodity Markets and on Raw Materials". Eur-Lex. European Union. 2 February 2011. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52011DC0025.
- ↑ "Report on Critical Raw Materials for the E.U.: Report of the Ad hoc Working Group on defining critical raw materials" (PDF). European Commission. May 2014. pp. 41. https://ec.europa.eu/docsroom/documents/10010/attachments/1/translations/en/renditions/pdf.
- ↑ Graedel, T.E.; Harper, E.M.; Nassar, N.T. et al. (2015). "Criticality of metals and metalloids". Proceedings of the National Academy of Sciences of the United States of America 112 (14): 4257-62. doi:10.1073/pnas.1500415112. PMC PMC4394315. PMID 25831527. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4394315.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references alphabetically, but this version — by design — lists them in order of appearance.
