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Journal articles on the topic 'Exploration interactive de données'

Author: Grafiati

Published: 25 May 2024

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1

Contu, S., R. Schiappa, D. Culié, E. Seutin, T. Pace-Loscos, and E. Chamorey. "P30 - Structuration automatique des données des dossiers médicaux et exploration statistique interactive." Journal of Epidemiology and Population Health 72 (May 2024): 202470. http://dx.doi.org/10.1016/j.jeph.2024.202470.

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2

Gibbs, Bobby, Jonas Braasch, and Ted Krueger. "Interactive acoustical intimacy exploration." Journal of the Acoustical Society of America 121, no. 5 (May 2007): 3094. http://dx.doi.org/10.1121/1.4781976.

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3

Haag, Moritz P., Alain C. Vaucher, Maël Bosson, Stéphane Redon, and Markus Reiher. "Interactive Chemical Reactivity Exploration." ChemPhysChem 15, no. 15 (September 9, 2014): 3301–19. http://dx.doi.org/10.1002/cphc.201402342.

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4

Perdriset, Françoise. "Paroles volées, paroles données : l'enquête, une pratique interactive ?" Mots 23, no. 1 (1990): 100–106. http://dx.doi.org/10.3406/mots.1990.1523.

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5

Krone, M., M. Falk, S. Rehm, J. Pleiss, and T. Ertl. "Interactive Exploration of Protein Cavities." Computer Graphics Forum 30, no. 3 (June 2011): 673–82. http://dx.doi.org/10.1111/j.1467-8659.2011.01916.x.

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6

Elkhaldi, Maher, and Robert Woodbury. "Interactive Design Exploration with Alt.Text." International Journal of Architectural Computing 13, no. 2 (June 2015): 103–22. http://dx.doi.org/10.1260/1478-0771.13.2.103.

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7

Ponciano, Daniel, Marcos Seefelder, and Ricardo Marroquim. "Graph-based interactive volume exploration." Computers & Graphics 60 (November 2016): 55–65. http://dx.doi.org/10.1016/j.cag.2016.06.007.

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8

Exbrayat, Matthieu, and Lionel Martin. "Exploration interactive d'un espace d'écritures médiévales." Gazette du livre médiéval 56, no. 1 (2011): 101–18. http://dx.doi.org/10.3406/galim.2011.1984.

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9

Schulz, Adriana, Harrison Wang, Eitan Grinspun, Justin Solomon, and Wojciech Matusik. "Interactive exploration of design trade-offs." ACM Transactions on Graphics 37, no. 4 (August 10, 2018): 1–14. http://dx.doi.org/10.1145/3197517.3201385.

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10

Sunseri, Jocelyn, and David Ryan Koes. "Pharmit: interactive exploration of chemical space." Nucleic Acids Research 44, W1 (April 19, 2016): W442—W448. http://dx.doi.org/10.1093/nar/gkw287.

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11

Wang, Xinxi, Yi Wang, David Hsu, and Ye Wang. "Exploration in Interactive Personalized Music Recommendation." ACM Transactions on Multimedia Computing, Communications, and Applications 11, no. 1 (August 2014): 1–22. http://dx.doi.org/10.1145/2623372.

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12

Traore, Michael, and Christophe Hurter. "Interactive Exploration of 3D Scanned Baggage." IEEE Computer Graphics and Applications 37, no. 1 (January 2017): 27–33. http://dx.doi.org/10.1109/mcg.2017.10.

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13

Rost, U., and E. Bornberg-Bauer. "TreeWiz: interactive exploration of huge trees." Bioinformatics 18, no. 1 (January 1, 2002): 109–14. http://dx.doi.org/10.1093/bioinformatics/18.1.109.

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14

ANDRIENKO, GENNADY L., and NATALIA V. ANDRIENKO. "Interactive maps for visual data exploration." International Journal of Geographical Information Science 13, no. 4 (June 1999): 355–74. http://dx.doi.org/10.1080/136588199241247.

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15

Sarquis, A. M., and L. M. Woodward. "Alka Seltzer Poppers: An Interactive Exploration." Journal of Chemical Education 76, no. 3 (March 1999): 385. http://dx.doi.org/10.1021/ed076p385.

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16

Deng, Bailin, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg, and Mark Pauly. "Interactive design exploration for constrained meshes." Computer-Aided Design 61 (April 2015): 13–23. http://dx.doi.org/10.1016/j.cad.2014.01.004.

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17

Scharl, Theresa, and Friedrich Leisch. "gcExplorer: interactive exploration of gene clusters." Bioinformatics 25, no. 8 (February 18, 2009): 1089–90. http://dx.doi.org/10.1093/bioinformatics/btp099.

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18

Koenig, Pierre-Yves, and Guy Melançon. "DagMap : exploration interactive de relations d'héritage." Revue d'intelligence artificielle 22, no. 3-4 (August 1, 2008): 353–68. http://dx.doi.org/10.3166/ria.22.353-368.

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19

Zizi, Mountaz, and Michel Beaudouin-Lafon. "Hypermedia exploration with interactive dynamic maps." International Journal of Human-Computer Studies 43, no. 3 (September 1995): 441–64. http://dx.doi.org/10.1006/ijhc.1995.1053.

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20

García, Roberto, Juan-Miguel López-Gil, and Rosa Gil. "Rhizomer: Interactive semantic knowledge graphs exploration." SoftwareX 20 (December 2022): 101235. http://dx.doi.org/10.1016/j.softx.2022.101235.

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21

Langer-Sautière, Laurence. "L’exploration interactive de données au service d’une démarche de participation." Cahiers de l’action N° 57, no. 1 (May 19, 2021): 52–60. http://dx.doi.org/10.3917/cact.057.0052.

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22

Toutin, Thierry, Clément Nolette, Yves Carbonneau, and Paul-André Gagnon. "STÉRÉO-RESTITUTION INTERACTIVE DES DONNÉES SPOT: DESCRIPTION D'UN NOUVEAU SYSTÈME." Canadian Journal of Remote Sensing 19, no. 2 (April 1993): 146–51. http://dx.doi.org/10.1080/07038992.1993.10874542.

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23

Ribani, Cyril. "L’exploration interactive de données au service d’une démarche de participation." Action publique N° 13, no. 1 (January 1, 2022): 46. http://dx.doi.org/10.3917/aprp.013.0046.

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24

Le Guyader, Damien, and Matthieu Le Tixerant. "De multiples applications pour l’analyse des données AIS (Automatic Identification System) et la géovisualisation interactive de données." Annales des Mines - Responsabilité et environnement N° 94, no. 2 (2019): 54. http://dx.doi.org/10.3917/re1.094.0054.

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25

Jiang, Daxin, Jian Pei, and Aidong Zhang. "Towards interactive exploration of gene expression patterns." ACM SIGKDD Explorations Newsletter 5, no. 2 (December 2003): 79–90. http://dx.doi.org/10.1145/980972.980983.

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26

Lin, Hanfei, Siyuan Gao, David Gotz, Fan Du, Jingrui He, and Nan Cao. "RCLens: Interactive Rare Category Exploration and Identification." IEEE Transactions on Visualization and Computer Graphics 24, no. 7 (July 1, 2018): 2223–37. http://dx.doi.org/10.1109/tvcg.2017.2711030.

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27

Berseth, Glen, Brandon Haworth, Muhammad Usman, Davide Schaumann, Mahyar Khayatkhoei, Mubbasir Kapadia, and Petros Faloutsos. "Interactive Architectural Design with Diverse Solution Exploration." IEEE Transactions on Visualization and Computer Graphics 27, no. 1 (January 1, 2021): 111–24. http://dx.doi.org/10.1109/tvcg.2019.2938961.

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28

Orr, Laurel, Magdalena Balazinska, and Dan Suciu. "Probabilistic database summarization for interactive data exploration." Proceedings of the VLDB Endowment 10, no. 10 (June 2017): 1154–65. http://dx.doi.org/10.14778/3115404.3115419.

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29

Huttenhower, Curtis, Sajid O. Mehmood, and Olga G. Troyanskaya. "Graphle: Interactive exploration of large, dense graphs." BMC Bioinformatics 10, no. 1 (2009): 417. http://dx.doi.org/10.1186/1471-2105-10-417.

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30

Liu, Tiecheng, and Ravi Katpelly. "An interactive system for video content exploration." IEEE Transactions on Consumer Electronics 52, no. 4 (November 2006): 1368–76. http://dx.doi.org/10.1109/tce.2006.273158.

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31

Kerbel, Gary D., Tim Pierce, J. L. Milovich, Dan E. Shumaker, Alan Verlo, Ronald E. Waltz, Gregory W. Hammett, Mike A. Beer, and Bill Dorland. "Interactive Scientific Exploration of Gyrofluid Tokamak Turbulence." International Journal of Supercomputer Applications and High Performance Computing 10, no. 2-3 (June 1996): 182–98. http://dx.doi.org/10.1177/109434209601000206.

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32

Cao, Lei, Qingyang Wang, and Elke A. Rundensteiner. "Interactive outlier exploration in big data streams." Proceedings of the VLDB Endowment 7, no. 13 (August 2014): 1621–24. http://dx.doi.org/10.14778/2733004.2733045.

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33

Joglekar, Manas, Hector Garcia-Molina, and Aditya Parameswaran. "Interactive Data Exploration with Smart Drill-Down." IEEE Transactions on Knowledge and Data Engineering 31, no. 1 (January 1, 2019): 46–60. http://dx.doi.org/10.1109/tkde.2017.2685998.

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34

Hori, Takaaki, Yasuyuki Nakamura, Naoki Aratani, and Atsuhiro Osuka. "Exploration of electronically interactive cyclic porphyrin arrays." Journal of Organometallic Chemistry 692, no. 1-3 (January 2007): 148–55. http://dx.doi.org/10.1016/j.jorganchem.2006.08.044.

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35

Fruchter, Renate, Kushagra Saxena, Matt Breidenthal, and Peter Demian. "Collaborative design exploration in an interactive workspace." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 3 (August 2007): 279–93. http://dx.doi.org/10.1017/s0890060407000285.

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AbstractArchitecture, engineering, and construction team members, while collaborating on building projects, rely on past experiences and content through the use of project design archives (whether in paper or digital format). Underutilization of potential knowledge in the decision-making process of data, information, and knowledge reuse is limited by access to these archives, because of sheer size, decontextualized content, and inconvenient access and presentation. This paper presents an integrated solution called CoMem–iRoom that leverages two technologies Corporate Memory (CoMem) and interactive Room (iRoom) developed at Stanford. CoMem–iRoom addresses critical limitations (content, context, visualization, and interactivity) constraining the process of collaborative exploration toward knowledge reuse and decision making.

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36

Li, Zhongyu, Dimitris N. Metaxas, Aidong Lu, and Shaoting Zhang. "Interactive Exploration for Continuously Expanding Neuron Databases." Methods 115 (February 2017): 100–109. http://dx.doi.org/10.1016/j.ymeth.2017.02.005.

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37

Lum, Eric B., James Shearer, and Kwan-Liu Ma. "Interactive multi-scale exploration for volume classification." Visual Computer 22, no. 9-11 (August 24, 2006): 622–30. http://dx.doi.org/10.1007/s00371-006-0049-8.

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38

Smellie, Andrew. "General Purpose Interactive Physico-Chemical Property Exploration." Journal of Chemical Information and Modeling 47, no. 3 (May 2007): 1182–87. http://dx.doi.org/10.1021/ci060052t.

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39

Shamir, Ariel, and Alla Stolpnik. "Interactive visual queries for multivariate graphs exploration." Computers & Graphics 36, no. 4 (June 2012): 257–64. http://dx.doi.org/10.1016/j.cag.2012.02.006.

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40

Berthold, Michael R., Bernd Wiswedel, and David E. Patterson. "Interactive exploration of fuzzy clusters using Neighborgrams." Fuzzy Sets and Systems 149, no. 1 (January 2005): 21–37. http://dx.doi.org/10.1016/j.fss.2004.07.009.

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41

Pham, Nguyen_Khang, Thang-Ghi Do, François Poulet, and Annie Morin. "TreeView, exploration interactive des arbres de décision." Revue d'intelligence artificielle 22, no. 3-4 (August 1, 2008): 473–87. http://dx.doi.org/10.3166/ria.22.473-487.

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42

Cybulski, Jacob L., Susan Keller, and Dilal Saundage. "Interactive Exploration of Data with Visual Metaphors." International Journal of Software Engineering and Knowledge Engineering 25, no. 02 (March 2015): 231–52. http://dx.doi.org/10.1142/s0218194015400082.

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Visual Analytics (VA) is an approach to data analysis by means of visual manipulation of data representation, which relies on innate human abilities of perception and cognition. Even though current visual toolkits in the Business Analytics (BA) domain have improved the effectiveness of data exploration, analysis and reporting, their features are often not intuitive, and can be confusing and difficult to use. Moreover, visualizations generated from these toolkits are mostly accessible to specialist users. Thus, there is a need for analytic environments that support data exploration, interpretation and communication of insight that do not add to the cognitive load of the analyst and their non-technical clients. In this conceptual paper, we explore the potential of primary metaphors, which arise out of human lived and sensory-motor experiences, in the design of immersive visual analytics environments. Primary metaphors provide ideas for representation of time, space, quantity, similarity, actions and team work. Using examples developed in our own work, we also explain how to combine such metaphors to create complex and cognitively acceptable visual metaphors, such as 3D data terrains that approximate our intuition of reality and create opportunities for data to be viewed, navigated, explored, touched, changed, discussed, reported and described to others, individually or collaboratively.

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43

Loher, Phillipe, and Isidore Rigoutsos. "Interactive exploration of RNA22 microRNA target predictions." Bioinformatics 28, no. 24 (October 16, 2012): 3322–23. http://dx.doi.org/10.1093/bioinformatics/bts615.

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44

Ladstädter, Florian, Andrea K. Steiner, Bettina C. Lackner, Barbara Pirscher, Gottfried Kirchengast, Johannes Kehrer, Helwig Hauser, Philipp Muigg, and Helmut Doleisch. "Exploration of Climate Data Using Interactive Visualization*." Journal of Atmospheric and Oceanic Technology 27, no. 4 (April 1, 2010): 667–79. http://dx.doi.org/10.1175/2009jtecha1374.1.

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Abstract In atmospheric and climate research, the increasing amount of data available from climate models and observations provides new challenges for data analysis. The authors present interactive visual exploration as an innovative approach to handle large datasets. Visual exploration does not require any previous knowledge about the data, as is usually the case with classical statistics. It facilitates iterative and interactive browsing of the parameter space to quickly understand the data characteristics, to identify deficiencies, to easily focus on interesting features, and to come up with new hypotheses about the data. These properties extend the common statistical treatment of data, and provide a fundamentally different approach. The authors demonstrate the potential of this technology by exploring atmospheric climate data from different sources including reanalysis datasets, climate models, and radio occultation satellite data. Results are compared to those from classical statistics, revealing the complementary advantages of visual exploration. Combining both the analytical precision of classical statistics and the holistic power of interactive visual exploration, the usual workflow of studying climate data can be enhanced.

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45

Calvani, Antonio. "Hypermedia: Interactive Exploration of a Medieval Town." Educational and Training Technology International 27, no. 1 (February 1990): 51–57. http://dx.doi.org/10.1080/1355800900270107.

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46

Miki, Masaaki, and Toby Mitchell. "Interactive Exploration of Tension-Compression Mixed Shells." ACM Transactions on Graphics 41, no. 6 (November 30, 2022): 1–14. http://dx.doi.org/10.1145/3550454.3555438.

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Achieving a pure-compression stress state is considered central to the form-finding of shell structures. However, the pure-compression assumption restricts the geometry of the structure's plan in that any free boundary edges cannot bulge outward. Allowing both tension and compression is essential so that overhanging leaves can stretch out toward the sky. When performing tension-compression mixed form-finding, a problem with boundary condition (BC) compatibility arises. Since the form-finding equation is hyperbolic, boundary information propagates along the asymptotic lines of the stress function. If conflicting BC data is prescribed at either end of an asymptotic line, the problem becomes ill-posed. This requires a user of a form-finding method to know the solution in advance. By contrast, pure-tension or pure-compression problems are elliptic and always give solutions under any BCs sufficient to restrain rigid motion. To solve the form-finding problem for tension-compression mixed shells, we focus on the Airy's stress function, which describes the stress field in a shell. Rather than taking the stress function as given, we instead treat both the stress function and the shell as unknowns. This doubles the solution variables, turning the problem to one that has an infinity of different solutions. By enforcing equilibrium in the shell interior and prescribing the correct matching pairs of BCs to both the stress function and the shell, a stress function and shell can be simultaneously found such that equilibrium is satisfied everywhere in the shell interior and thus automatically has compatible BCs by construction. The problem of a potentially over-constrained form-finding is thus avoided by expanding the solution space and creating an under-determined problem. By varying inputs and repeatedly searching for stress function-shell pairs that fall within the solution space, a user is allowed to interactively explore the possible forms of tension-compression mixed shells under the given plan of the shell.

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47

Ogg, Jim, and Sylvie Renaut. "Activité et retraite en Europe : une exploration des données SHARE." Espace populations sociétés, no. 2013/3 (December 31, 2013): 91–104. http://dx.doi.org/10.4000/eps.5565.

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48

Paillou, Ph, F. Bonnarel, F. Ochsenbein, and M. Crézé. "Aladin: An Interactive Deep Sky Mapping Facility." Symposium - International Astronomical Union 161 (1994): 347–51. http://dx.doi.org/10.1017/s0074180900047628.

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Any astronomer, whether preparing observation runs or reducing data, requires access to information concerning the objects under investigation. Ideally the data should be from several wavelengths and should be as quantitative as possible. This leads to the concept of developing simultaneous interactive access to sky surveys, initially at optical wavelengths, and with state-of-the-art information systems for all field objects. In order to satisfy this requirement, the CDS (Centre de Données astronomiques de Strasbourg) is developing a ‘Deep Sky Mapping Facility’ project, Aladin, which aims to connect the data stored at CDS (astronomical catalogues and Simbad), to pixel data from continuously updated deep optical sky surveys.

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49

Parkan, Matthew. "Données LiDAR aériennes: pertinence de l'interprétation visuelle pour la foresterie." Schweizerische Zeitschrift fur Forstwesen 168, no. 3 (March 1, 2017): 127–33. http://dx.doi.org/10.3188/szf.2017.0127.

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Airborne LiDAR data: relevance of visual interpretation for forestry Airborne LiDAR surveys are particularly well adapted to map, study and manage large forest extents. Products derived from this technology are increasingly used by managers to establish a general diagnosis of the condition of forests. Less common is the use of these products to conduct detailed analyses on small areas; for example creating detailed reference maps like inventories or timber marking to support field operations. In this context, the use of direct visual interpretation is interesting, because it is much easier to implement than automatic algorithms and allows a quick and reliable identification of zonal (e.g. forest edge, deciduous/persistent ratio), structural (stratification) and point (e.g. tree/stem position and height) features. This article examines three important points which determine the relevance of visual interpretation: acquisition parameters, interactive representation and identification of forest characteristics. It is shown that the use of thematic color maps within interactive 3D point cloud and/or cross-sections makes it possible to establish (for all strata) detailed and accurate maps of a parcel at the individual tree scale.

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50

Jensen, Mads Brath, Isak Worre Foged, and Hans Jørgen Andersen. "A framework for interactive human–robot design exploration." International Journal of Architectural Computing 18, no. 3 (March 16, 2020): 235–53. http://dx.doi.org/10.1177/1478077120911588.

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This study seeks to identify key aspects for increased integration of interactive robotics within the creative design process. Through its character as foundational research, the study aims to contribute to the advancement of new explorative design methods to support architects in their exploration of fabrication and assembly of an integrated performance-driven architecture. The article describes and investigates a proposed design framework for supporting an interactive human–robot design process. The proposed framework is examined through a 3-week architectural studio, with university master students exploring the design of a brick construction with the support of an interactive robotic platform. Evaluation of the proposed framework was done by triangulation of the authors’ qualitative user observations, quantitative logging of the students’ individual design processes, and through questionnaires completed after finishing the studies. The result suggests that interactive human–robot fabrication is a relevant mode of design with positive effect on the process of creative design exploration.

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