Relevant bibliographies by topics / Data Product

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data Product'

Author: Grafiati
Published: 7 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Data Product"

1

Do, Namchul. "Education and Training of Product Data Analytics using Product Data Management System." Korean Journal of Computational Design and Engineering 22, no. 1 (2017): 80–88. http://dx.doi.org/10.7315/cde.2017.080.

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Vineetha Sasikumar. "Product data science: Bridging data and product innovation." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 1813–21. https://doi.org/10.30574/wjarr.2025.26.1.1170.

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The rapid evolution of product data science has transformed the digital landscape, empowering organizations to harness vast volumes of user data for strategic decision-making. By combining advanced analytical techniques with deep domain expertise, Product Data Scientists uncover actionable insights that drive innovation, optimize user experiences, and enhance business outcomes. From behavioral segmentation and interaction mapping to predictive modeling and causal inference, these emerging methodologies enable organizations to navigate complex market dynamics with unprecedented precision. The c
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Leong, K. K., K. M. Yu, and W. B. Lee. "Product data allocation for distributed product data management system." Computers in Industry 47, no. 3 (2002): 289–98. http://dx.doi.org/10.1016/s0166-3615(01)00152-x.

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Do, Namchul. "Integration of Social Media with Product Data Management for Collaborative Product Design." Journal of Korean Institute of Industrial Engineers 42, no. 1 (2016): 50–56. http://dx.doi.org/10.7232/jkiie.2016.42.1.050.

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Shaw, N. K., M. Susan Bloor, and A. de Pennington. "Product data models." Research in Engineering Design 1, no. 1 (1989): 43–50. http://dx.doi.org/10.1007/bf01580002.

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Vergeest, JSM. "Product Data Exchange." Computer-Aided Design 28, no. 8 (1996): 665. http://dx.doi.org/10.1016/0010-4485(96)86818-7.

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MOCHIZUKI, Tatsuya. "Product Data Management." Journal of the Japan Society for Precision Engineering 72, no. 2 (2006): 161–64. http://dx.doi.org/10.2493/jjspe.72.161.

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Silvola, Risto, Arto Tolonen, Janne Harkonen, Harri Haapasalo, and Tarja Mannisto. "Defining one product data for a product." International Journal of Business Information Systems 30, no. 4 (2019): 489. http://dx.doi.org/10.1504/ijbis.2019.099308.

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Mannisto, Tarja, Arto Tolonen, Harri Haapasalo, Janne Harkonen, and Risto Silvola. "Defining one product data for a product." International Journal of Business Information Systems 30, no. 4 (2019): 489. http://dx.doi.org/10.1504/ijbis.2019.10020637.

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Do, Namchul, HyunChul Kang, and Heechul Bae. "Product Development Processes and Product Data Model for Supporting Development of Smart, Connected Products." Journal of the Korean Institute of Industrial Engineers 46, no. 2 (2020): 82–93. http://dx.doi.org/10.7232/jkiie.2020.46.2.082.

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Dissertations / Theses on the topic "Data Product"

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Morshedzadeh, Iman. "Data Classification in Product Data Management." Thesis, Högskolan i Skövde, Institutionen för teknik och samhälle, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-14651.

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This report is about the product data classification methodology that is useable for the Volvo Cars Engine (VCE) factory's production data, and can be implemented in the Teamcenter software. There are many data generated during the life cycle of each product, and companies try to manage these data with some product data management software. Data classification is a part of data management for most effective and efficient use of data. With surveys that were done in this project, items affecting the data classification have been found. Data, attributes, classification method, Volvo Cars Engine f
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Čvančarová, Lenka. "MDM of Product Data." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-150246.

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This thesis is focused on Master Data Management of Product Data. At present, most publications on the topic of MDM take into account customer data, and a very limited number of sources focus solely on product data. Some resources actually do attempt to cover MDM in full-depth. Even those publications are typically are very customer oriented. The lack of Product MDM oriented literature became one of the motivations for this thesis. Another motivation was to outline and analyze specifics of Product MDM in context of its implementation and software requirements for a vendor of MDM application so
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Parviainen, A. (Antti). "Product portfolio management requirements for product data management." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201409021800.

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In large organisations today the amount of products is numerous and it is challenging for senior management to have proper control and understanding over all products. As the product is the most important aspect for an organisation to consider, senior management must have ability to manage investments on products and follow development of product related indicators. Managing products as investment on portfolio level, where products are divided into a limited amount of portfolios is a solution for achieving decent control over product investments on senior management level. Product portfolio m
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Flankegård, Filip. "The use of data within Product Development of manufactured products." Thesis, Mälardalens högskola, Innovation och produktrealisering, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-35084.

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Antonov, Anton. "Product Information Management." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-150108.

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Product Information Management (PIM) is a field that deals with the product master data management and combines into one base the experience and the principles of data integration and data quality. Product Information Management merges the specific attributes of products across all channels in the supply chain. By unification, centralization and standardization of product information into one platform, quality and timely information with added value can be achieved. The goal of the theoretical part of the thesis is to construct a picture of the PIM, to place the PIM into a broader context, to
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Hannila, H. (Hannu). "Towards data-driven decision-making in product portfolio management:from company-level to product-level analysis." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526224428.

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Abstract Products and services are critical for companies as they create the foundation for companies’ financial success. Twenty per cent of company products typically account for some eighty per cent of sales volume. Nevertheless, the product portfolio decisions — how to strategically renew company product offering — tend to involve emotions, pet products and who-shout-the-loudest mentality while facts, numbers, and quantitative analyses are missing. Profitability is currently measured and reported at a company level, and firms seem unable to measure product-level profitability in a constant
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Hooi, Leng Lee. "Application of product data management within the product development process." Thesis, University of Huddersfield, 2002. http://eprints.hud.ac.uk/id/eprint/14688/.

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Manufacturing companies need to be able to respond to customer demand quickly and accurately. This requires the capability to manage product data effectively. Product Data Management (PDM) systems have been identified as a solution to deliver this capability by providing the right information to the right people at the right time and in the right format. The foundation of this research is that the concept of PDM is relevant and important within the product development process. This research focuses upon how the PDM concept is applied in practice to define and configure products and how it can
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Sun, Tao. "Product Context Analysis with Twitter Data." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13526.

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Context. For the product manager, the product context analysis, which aims to align their products to the market needs, is very important. By understanding the market needs, the product manager knows the product context information about the environment the products conceived and the business the products take place. The product context analysis using the product context information helps the product manager find the accurate position of his/her products and support the decision-making of the products. The product context information generally could be found in the user feedbacks. And the trad
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Romaniuk, Helena. "Analysis of product usage panel data." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326798.

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Hines, Erisa K. (Erisa Kimberly). "Lifecycle perspectives on product data management." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34141.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2005.<br>Includes bibliographical references (p. 106-109).<br>Implementing a new IT system often requires the enterprise to transform in order to maximally leverage the capabilities generated by the new system. The challenge in using IT as an enabler to change arises from the need to synergistically redesign processes, develop and implement a solution using internal talent and external suppl
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Books on the topic "Data Product"

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CIMdata. Product-data management. Department of Trade and Industry, 1994.

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Corporation, Dallas Semiconductor. Product data book. Dallas Semiconductor Corporation., 1987.

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1957-, Owen Jon, ed. Product data exchange. UCL Press, 1995.

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(Firm), Harris Semiconductor. Digital product data book. Harris Semiconductor, 1988.

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Limited, IQD. Crystal product data book. IQD Limited, 1994.

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Limited, IQD. Crystal product data book. IQD Limited, 1995.

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Corporation, Harris. Analog product data book. Harris, 1986.

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Corporation, ILC Data Device. Data converters product catalog. ILC DDC, 1989.

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(Firm), Shell UK Oil. Product safety data sheet. Shell UK oil, 1985.

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Ohio-Kentucky-Indiana Regional Council of Governments and Ohio-Kentucky-Indiana Regional Council of Governments. Decision Resources Center, eds. Regional data product catalog. Ohio-Kentucky-Indiana Regional Council of Governments, 1988.

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Book chapters on the topic "Data Product"

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Stark, John. "Product Data." In Decision Engineering. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-546-0_7.

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Stark, John. "Product Data." In Product Lifecycle Management (Volume 2). Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24436-5_8.

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Martens, Jan. "Data Analytics." In Digital Product Management. Springer Fachmedien Wiesbaden, 2024. http://dx.doi.org/10.1007/978-3-658-44276-7_19.

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Yin, Yong, Ikou Kaku, Jiafu Tang, and JianMing Zhu. "Product Architecture and Product Development Process for Global Performance." In Data Mining. Springer London, 2011. http://dx.doi.org/10.1007/978-1-84996-338-1_8.

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Mechlinski, Thomas, and Andreas Schreiber. "Product Data Management." In IFIP Advances in Information and Communication Technology. Springer US, 1999. http://dx.doi.org/10.1007/978-0-387-35577-1_15.

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Sheth, Sharad. "Product Data Management." In CAD/CAM Robotics and Factories of the Future. Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-52320-5_75.

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Kerkhove, Louis-Philippe. "Managing Product Returns." In Data-driven Retailing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12962-9_6.

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Ball, Robert, and Brian Rague. "Final Product." In The Beginner's Guide to Data Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07865-1_11.

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Maoliniyazi, Aishan, Chaohong Ma, Xiaofeng Meng, and Yingtao Peng. "Enhanced Product Embedding with Sememe for Product Search." In Big Data and Social Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5803-6_23.

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Anderl, Reiner, and Martin Momberg. "Authentication of product data and product components." In Information Infrastructure Systems for Manufacturing II. Springer US, 1999. http://dx.doi.org/10.1007/978-0-387-35385-2_19.

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Conference papers on the topic "Data Product"

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Muramatsu, Kohta, Yoshiyuki Takeda, and Kazuhiko Kato. "Analysis of Purchasing Trends and Product Recommendations of Customer Clusters for Each Product Using Bayesian Network." In 2024 IEEE/ACIS 9th International Conference on Big Data, Cloud Computing, and Data Science (BCD). IEEE, 2024. http://dx.doi.org/10.1109/bcd61269.2024.10743121.

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Bryan, Daniel Alexander, Maria Susan Anggreainy, Devi Fitrianah, and Ajeng Wulandari. "Product Label Clustering Based on Search Keywords for Product Name Recommendations in Ecommerce." In 2024 5th International Conference on Artificial Intelligence and Data Sciences (AiDAS). IEEE, 2024. http://dx.doi.org/10.1109/aidas63860.2024.10730652.

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Maulina, Nadhira Riska, and Isti Surjandari. "Efficiency Measurement for Non-Profit Organizations in Halal Industry Using Data Envelopment Analysis." In 14th International Seminar on Industrial Engineering and Management. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-rtat0p.

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Consuming halal products has become part of today's lifestyle. In addition, product halal assurance is one of the basic requirements for Indonesian products to penetrate the global halal market. The government continues to encourage the existence of a new Halal Inspection Agency as a form of strengthening halal product guarantees as well as accelerating the development of the halal industry in Indonesia. The purpose of this study is to evaluate the efficiency of performance in each product group segment at one of the Halal Inspection Agency using Data Envelopment Analysis. Performed for 9 segm
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"GATHERING PRODUCT DATA FROM SMART PRODUCTS." In 10th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001700302520257.

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Attokurov, Ulukbek, Okan Kaya, and Mehmet Selman Sezgin. "Product Recommendation Based on Embeddings: People Who Viewed This Product Also Viewed These Products." In 2022 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2022. http://dx.doi.org/10.1109/bigcomp54360.2022.00063.

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Vrampas, George, Corey Kado, Xiaoou Yang, Elisabeth Kames, and Beshoy Morkos. "Collecting Product Design Data: Examining the Applicability of Utilizing Gaze Data to Obtain Customer Feedback on Product Designs." In ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/detc2023-117130.

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Abstract Studies have shown gaze path data to be helpful in gaining consumer feedback. This study examines the applicability of utilizing eye tracking in collecting consumer preference data on a product’s design. During the study, the subjects are asked to indicate their preferences textually and verbally; concurrently, eye-tracking software collects gaze data from the test subjects. Both datasets are compared for correlation. The robustness of the study is tested against three variables: (1) product type; (2) design fidelity; and (3) product features. The study determines whether gaze data ca
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Mitik, Merve, Ozan Korkmaz, Pinar Karagoz, Ismail Hakki Toroslu, and Ferhat Yucel. "Data Mining Based Product Marketing Technique for Banking Products." In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016. http://dx.doi.org/10.1109/icdmw.2016.0085.

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Micol, Alberto, Magda Arnaboldi, Nausicaa A. R. Delmotte, Laura Mascetti, and Joerg Retzlaff. "ESO science data product standard for 1D spectral products." In SPIE Astronomical Telescopes + Instrumentation, edited by Alison B. Peck, Robert L. Seaman, and Chris R. Benn. SPIE, 2016. http://dx.doi.org/10.1117/12.2232655.

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Entezari, Negin, Evangelos E. Papalexakis, Haixun Wang, Sharath Rao, and Shishir Kumar Prasad. "Tensor-based Complementary Product Recommendation." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671938.

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Yoshimura, Masataka, Tsutomu Nishimura, and Kazuhiro Izui. "Acquisition of Product Design Guidelines Considering User Kansei Data Pertaining to Product Environments." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85160.

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Recently, almost all industrially manufactured consumer goods have a high level of engineering excellence, and product designers face an increasingly difficult task of creating products that will stand out in a competitive marketplace. At present, users tend to base their purchasing decisions on the product’s degree of fitness to their preferences, not the degree of functional fulfillment that the product offers. The development of products that are more attractive to users requires the consideration of human preferences and sensibilities, so-called “Kansei,” as well as the skillful applicatio
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Reports on the topic "Data Product"

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Smith, Bradford M. Product data exchange:. National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.ir.89-4165.

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Altemueller, Jeffrey, Kelly Chi, Gary Baldridge, Lori Davis, and Phillip Dorr. Product Definition Data Interface (PDDI) Product Specification. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada239256.

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Abeye, Binyam, Edward Barkmeyer, and Peter Denno. Product data sheet ontology. National Institute of Standards and Technology, 2014. http://dx.doi.org/10.6028/nist.ir.8035.

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ENSR CONSULTING AND ENGINEERING FLORENCE AL. RAMP Product Data Translation System Printed Wiring Assembly Product Data Definition Document. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada251560.

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Brei, Marylouise. Exchange Standards for Electronic Product Data. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada205729.

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Smith, Bradford M. External representation of product definition data. National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.ir.89-4166.

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Carver, Gary P., and Howard M. Bloom. Concurrent engineering through product data standards. National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.4573.

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Parks, Curtis. Internet commerce for manufacturing product data. National Institute of Standards and Technology, 1999. http://dx.doi.org/10.6028/nist.ir.6320.

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Flater, David, and KC Morris. Testability of product data management interfaces. National Institute of Standards and Technology, 1999. http://dx.doi.org/10.6028/nist.ir.6429.

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Farrigan, Tracey, and Austin Sanders. The Poverty Area Measures data product. Economic Research Service, U.S. Department of Agriculture, 2024. https://doi.org/10.32747/2024.8754225.ers.

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The U.S. Department of Agriculture's Poverty Area Measures (PAM) data product is designed to improve understanding of the geography of poverty in the United States. This report contains historical and technical documentation from the November 2022 version of PAM. Examples provided in this report are from 1960 through 2019, but the lessons will be applicable to PAM data in the future. PAM includes four measures of poverty: high, extreme, persistent, and the newly developed measure of enduring poverty. The methodology for the 2022 version of PAM incorporates reliability metrics to account for ma
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