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Journal articles on the topic 'Design for data'

Author: Grafiati

Published: 7 July 2024

Last updated: 19 July 2025

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1

Fatima, Neha, and Prof S. A. Madival. "A Design of Lightweight Secure Data Sharing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 1965–70. http://dx.doi.org/10.31142/ijtsrd14520.

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2

Rusdiana, Komang Ery, linawati linawati, and I. Made Oka Widyantara. "Green Data Center Design of Udayana University." Majalah Ilmiah Teknologi Elektro 15, no. 2 (2016): 39–44. http://dx.doi.org/10.24843/mite.1502.07.

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3

王, 倩. "Analysis of Wardrobe User Needs Based on Data Statistics." Design 09, no. 03 (2024): 846–53. http://dx.doi.org/10.12677/design.2024.93391.

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4

张, 鸿莉. "Data-Based Interior Design: Practice and Application of Machine Learning." Design 09, no. 03 (2024): 1015–22. http://dx.doi.org/10.12677/design.2024.93412.

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5

李, 月恩. "Research on Product Design Methods Based on Image Data Mining." Design 08, no. 04 (2023): 2198–204. http://dx.doi.org/10.12677/design.2023.84265.

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6

Banks, David L., and Colin L. Mallows. "Design, Data, Analysis." Journal of the American Statistical Association 83, no. 404 (1988): 1214. http://dx.doi.org/10.2307/2290162.

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7

Golbeck, Jennifer. "Data meets design." Science 347, no. 6217 (2015): 36. http://dx.doi.org/10.1126/science.aaa0421.

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8

Sherwin, David John. "Design from data." New Scientist 204, no. 2732 (2009): 28–29. http://dx.doi.org/10.1016/s0262-4079(09)62875-x.

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9

Nethercot, D. A. "Design data sheet." Journal of Constructional Steel Research 7, no. 1 (1987): 75–77. http://dx.doi.org/10.1016/0143-974x(87)90035-6.

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10

Clark, R. G. "Sample Design Using Imperfect Design Data." Journal of Survey Statistics and Methodology 1, no. 1 (2013): 6–23. http://dx.doi.org/10.1093/jssam/smt002.

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11

李, 怡龙. "Research on Nanjing Xiaoxihu Neighborhood Vitality Strategy Based on Multi-Source Data." Design 09, no. 03 (2024): 356–63. http://dx.doi.org/10.12677/design.2024.93327.

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12

M. Marvin Newhouse for the MPS Coor. "Data entry design and data quality." Controlled Clinical Trials 6, no. 3 (1985): 229. http://dx.doi.org/10.1016/0197-2456(85)90036-4.

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13

Jin, Y., and Y. Ishino. "DAKA: design activity knowledge acquisition through data-mining." International Journal of Production Research 44, no. 14 (2006): 2813–37. http://dx.doi.org/10.1080/00207540600654533.

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14

Suresh, Geetha, SanjeevV Thomas, and Karthik Suresh. "Design and data analysis 1 study design." Annals of Indian Academy of Neurology 15, no. 2 (2012): 76. http://dx.doi.org/10.4103/0972-2327.94987.

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15

Akin, Ömer, and Chengtah Lin. "Design protocol data and novel design decisions." Design Studies 16, no. 2 (1995): 211–36. http://dx.doi.org/10.1016/0142-694x(94)00010-b.

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16

Facklam, Ferdinand, and Felipe Pecegueiro do Amaral Curado. "Data driven parametric design." PARC Pesquisa em Arquitetura e Construção 2, no. 7 (2011): 49. http://dx.doi.org/10.20396/parc.v2i7.8634582.

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The focus of this paper is that we want to give a brief introduction about the idea of Parametric Design (PD) and the use of data to inform the design process. The digital fabrication is not covered in detail in this document. In the case study “Live Building” explains a sensory process. The project shows how to collect data, transformed and transported into a shape. Innovation is not only the approach of the draft, but the systematic procedure and the resulting diversity of solutions. The search for the geometric shape and the key to the concept will be answered in detail.

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17

Van Ameijde, Jeroen. "Data-driven Urban Design." SPOOL 9, no. 1 (2022): 35–48. http://dx.doi.org/10.47982/spool.2022.1.03.

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Nicholas Negroponte and MIT’s Architecture Machine Group speculated in the 1970s about computational processes that were open to participation, incorporating end-user preferences and democratizing urban design. Today’s ‘smart city’ technologies, using the monitoring of people’s movement and activity patterns to offer more effective and responsive services, might seem like contemporary interpretations of Negroponte’s vision, yet many of the collectors of user information are disconnected from urban policy making. This article presents a series of theoretical and procedural experiments conducted through academic research and teaching, developing user-driven generative design processes in the spirit of ‘The Architecture Machine’. It explores how new computational tools for site analysis and monitoring can enable data-driven urban place studies, and how these can be connected to generative strategies for public spaces and environments at various scales. By breaking down these processes into separate components of gathering, analysing, translating and implementing data, and conceptualizing them in relation to urban theory, it is shown how data-driven urban design processes can be conceived as an open-ended toolkit to achieve various types of user-driven outcomes. It is argued that architects and urban designers are uniquely situated to reflect on the benefits and value systems that control data-driven processes, and should deploy these to deliver more resilient, liveable and participatory urban spaces.

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18

Jiang, Lei Ge. "Visualization Design of Data." Applied Mechanics and Materials 325-326 (June 2013): 1564–66. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1564.

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With the explosion of information and the diversify of modern culture, the communication of information have changed a lot, especially the visualization design of data .This paper analyzed the status of Data Visualization in order to expound the significance of Data Visualization and the applications trend .

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19

Kemp, A. W., and C. L. Mallows. "Design, Data and Analysis." Biometrics 44, no. 3 (1988): 914. http://dx.doi.org/10.2307/2531608.

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20

Alho, Kari, Hannu Peltonen, Martti Mäntylä, and Rejio Sulonen. "A design data manager." ACM SIGMOD Record 17, no. 3 (1988): 202. http://dx.doi.org/10.1145/971701.50226.

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21

Wallis, Peter. "FROM DATA TO DESIGN." Applied Artificial Intelligence 25, no. 6 (2011): 530–48. http://dx.doi.org/10.1080/08839514.2011.587155.

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22

Hodgson, John. "Data-Directed Drug Design." Nature Biotechnology 9, no. 1 (1991): 19–21. http://dx.doi.org/10.1038/nbt0191-19.

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23

Cutts, D., J. S. Hoftun, R. T. Zeller, T. Trojak, R. Van Berg, and C. R. Johnson. "D0 Data Acquisition Design." IEEE Transactions on Nuclear Science 32, no. 4 (1985): 1473–78. http://dx.doi.org/10.1109/tns.1985.4333637.

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24

Churchill, Elizabeth F. "Data, design, and ethnography." Interactions 25, no. 1 (2017): 22–23. http://dx.doi.org/10.1145/3172893.

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25

Wong, Bang. "Design of data figures." Nature Methods 7, no. 9 (2010): 665. http://dx.doi.org/10.1038/nmeth0910-665.

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26

Baker, Michael J. "Data Collection – Questionnaire Design." Marketing Review 3, no. 3 (2003): 343–70. http://dx.doi.org/10.1362/146934703322383507.

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27

Becker, Robert, Laura Steffny, Thomas Bleistein, and Dirk Werth. "From Data to Design." atp magazin 66, no. 6-7 (2024): 80–87. http://dx.doi.org/10.17560/atp.v66i6-7.2738.

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This paper explores the application of Large Language Models (LLMs) in the automotive and supplier industries, with a particular focus on the use of retrieval-augmented generation (RAG) systems to streamline information retrieval from technical documentation. The research, part of the CoLab4DigiTwin project, investigates how digital twins supported by smart services can enhance interdisciplinary collaboration and reduce the reliance on manual data searches. We developed a pipeline utilizing a RAG architecture which uses a vector database for efficient data management and fast access to relevant information, eliminating the need for expensive computational resources. The performance of various open-source LLMs, which are finetuned on German, was evaluated, focusing on readability, clarity, and accuracy. The results show decent performance of the system without the need for model fine-tuning. Future research will aim to refine these processes and extend the applicability of RAG systems, highlighting the potential of Large Language Models to transform industrial data interaction.

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28

Burkett, Justin, and Maxwell Rosenthal. "Data-driven contract design." Journal of Economic Theory 221 (October 2024): 105900. http://dx.doi.org/10.1016/j.jet.2024.105900.

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29

Gupta, Rishi, and Tim Roughgarden. "Data-driven algorithm design." Communications of the ACM 63, no. 6 (2020): 87–94. http://dx.doi.org/10.1145/3394625.

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30

Ziegel, Eric. "Design, Data, and Analysis." Technometrics 31, no. 1 (1989): 118–19. http://dx.doi.org/10.1080/00401706.1989.10488488.

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31

Lockett, F. J. "Polymer data for design." Materials & Design 14, no. 4 (1993): 260. http://dx.doi.org/10.1016/0261-3069(93)90082-7.

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32

Bean, Jonathan, and Daniela Rosner. "Big data, diminished design?" Interactions 21, no. 3 (2014): 18–19. http://dx.doi.org/10.1145/2592267.

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33

Orman, Levent. "Functional data model design." Information Systems 11, no. 2 (1986): 123–35. http://dx.doi.org/10.1016/0306-4379(86)90002-5.

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34

König, Christine, Helmut Büttner, and Fritz Ebert. "Design Data for Cyclones." Particle & Particle Systems Characterization 8, no. 1-4 (1991): 301–7. http://dx.doi.org/10.1002/ppsc.19910080155.

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35

Lee, Hyun-Jhin. "Data Curation Framework for Data Driven Design - Focused on Design Research Process." JOURNAL OF THE KOREA CONTENTS ASSOCIATION 25, no. 6 (2025): 80–90. https://doi.org/10.5392/jkca.2025.25.06.080.

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36

Wided, Oueslati, and Akaichi Jalel. "Mobile Information Collectors Trajectory Data Warehouse Design." International Journal of Managing Information Technology (IJMIT) 2, no. 3 (2010): 1 to 20. https://doi.org/10.5281/zenodo.3341091.

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To analyze complex phenomena which involve moving objects, Trajectory Data Warehouse (TDW) seems to be an answer for many recent decision problems related to various professions (physicians, commercial representatives, transporters, ecologists …) concerned with mobility. This work aims to make trajectories as a first class concept in the trajectory data conceptual model and to design a TDW, in which data resulting from mobile information collectors’ trajectory are gathered. These data will be analyzed, according to trajectory characteristics, for decision making purposes, such as new products commercialization, new commerce implementation, etc.

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37

Churchill, Elizabeth F. "From data divination to data-aware design." Interactions 19, no. 5 (2012): 10–13. http://dx.doi.org/10.1145/2334184.2334188.

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38

杜, 亚洁. "Research on the Application of Visual Design in Data Journalism—Using The Paper’s “Meishuke” as an Example." Design 09, no. 05 (2024): 625–31. http://dx.doi.org/10.12677/design.2024.95597.

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39

Laznicka, Peter. "Design of an international data base of giant metal accumulations." Global Tectonics and Metallogeny 6, no. 3-4 (1998): 215–24. http://dx.doi.org/10.1127/gtm/6/1998/215.

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40

Ching-Hu Tsai, Ching-Hu Tsai, and Shih-Yang Yang Ching-Hu Tsai. "The Natural Formula Design Uses Mobile Application in Data Management." 電腦學刊 35, no. 6 (2024): 085–96. https://doi.org/10.53106/199115992024123506007.

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<p>The purpose of this study is to apply Unified Modeling Language (UML) to the development of commercial tube-feeding milk formulas and establish the most suitable processing method for natural formula tube feeding. The study also incorporates response surface methodology (RSM) to explore the UML workflow for formula design and optimize processing conditions. According to the formula design process, the raw material composition for each 300-kcal can consists of 5 grams of germ rice, 60 grams of potatoes, and 15 grams of corn flour. The optimal viscosity for passing through a nasogastric tube is 223 cps. The processing steps include fine grinding, sterilization, and sensory evaluation at different rotation speeds, temperatures, and durations. The optimal fine grinding conditions are 1500 rpm for 5 minutes, which allows 95% of the raw materials to pass through an 80-120 mesh sieve. Sterilization is best achieved at 121&deg;C for 20 minutes, which minimizes nutrient degradation. In a taste test, the egg formula had the highest acceptance rate. Overall, the use of UML modules for processing workflow and data analysis enables optimal operational procedures, precise data analysis, and the fulfillment of nutritional requirements.</p> <p>&nbsp;</p>

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41

Atri, Preyaa. "Design and Implementation of High-Throughput Data Streams using Apache Kafka for Real-Time Data Pipelines." International Journal of Science and Research (IJSR) 7, no. 11 (2018): 1988–91. http://dx.doi.org/10.21275/sr24422184316.

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42

叶, 昱蔚. "Research on Landscape Cultural Element Evaluation of Wuxi Grand Canal National Cultural Park Based on Network Data and Text Mining." Design 09, no. 06 (2024): 590–98. https://doi.org/10.12677/design.2024.96729.

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43

Shijitha, R., P. Karthigaikumar, and A. Stanly Paul. "Data Warehouse Design for Big Data in Academia." Computers, Materials & Continua 71, no. 1 (2022): 979–92. http://dx.doi.org/10.32604/cmc.2022.016676.

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44

Dash, Ranjan Kumar. "Design of data scoring model for big data." International Journal of Intelligent Enterprise 7, no. 1/3 (2020): 356. http://dx.doi.org/10.1504/ijie.2020.10026356.

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45

Dash, Ranjan Kumar. "Design of data scoring model for big data." International Journal of Intelligent Enterprise 7, no. 1/2/3 (2020): 356. http://dx.doi.org/10.1504/ijie.2020.104666.

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46

Green, David C. "Utility Data Web Page Design– Presenting the Data." Strategic Planning for Energy and the Environment 24, no. 2 (2004): 28–42. http://dx.doi.org/10.1080/10485230409509659.

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47

Green, David C., and Paul J. Allen. "Utility Data Web Page Design–Mining the Data." Strategic Planning for Energy and the Environment 25, no. 2 (2005): 46–59. http://dx.doi.org/10.1080/10485230509509686.

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48

Raisinghani, Mahesh S. "Adapting Data Modeling Techniques for Data Warehouse Design." Journal of Computer Information Systems 40, no. 3 (2000): 73–77. http://dx.doi.org/10.1080/08874417.2000.11647457.

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49

Nievergelt, J. "Data analysis-the key to data base design." Computer Compacts 4, no. 5 (1986): 173. http://dx.doi.org/10.1016/0167-7136(86)90011-9.

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50

Kansha, Yasuki, Yoshihiro Hashimoto, and Min-Sen Chiu. "Data-Based LQI Controller Design from Plant Data." JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 39, no. 7 (2006): 746–52. http://dx.doi.org/10.1252/jcej.39.746.

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