In his book entitled The Artful Universe (1995), John Barrow examines the origins of our sense of beauty, order, and other aesthetics in light of the underlying ...
Academic Journal of Science, CD-ROM. ISSN: 2165-6282 :: 2(2): 511-522 (2013) Copyright © 2013 by UniversityPublications.net
ENHANCING INTERACTIONS BETWEEN ARTISTS AND SCIENTISTS VIA A COMMON LANGUAGE D. L. Marrin Water Sciences & Insights, USA Artists and scientists have much to offer each other in perceiving and describing the world, as well as creatively addressing its many challenges. To enable a meaningful exchange, the data, theories, and mathematics of scientists must find common ground with the images, sounds, and forms of artists. A common language based on spatial and temporal patterns is a potential vehicle because patterns are more fundamental and recognizable than are numbers, words, or abstract symbols. Pattern languages developed for architecture, software design, music, and similar disciplines can be modified to enhance the communication between artists and scientists. An essential collection of patterns, their supporting components, and some basic rules for structure constitute a first step toward building a pattern language that will be continually amended by users. There is substantial commonality in the underlying spatial and temporal patterns of the arts and sciences that can be revealed and utilized in developing such a language. Keywords: Pattern, Language, Science, Art.
Introduction Many significant breakthroughs in the arts, sciences, and design fields have arisen, not from modifications of existing views, but from fundamentally different ways of perceiving the natural world —whether through the senses or intellect. Artists and scientists are well positioned via their respective training and creativities to view the world in different, but complementary, ways. Sharing interdisciplinary perceptions as a means of more creatively approaching or representing our challenges will necessarily encounter the hurdle of effective communication among diverse practitioners. The theories, mathematics, and data sets of scientists must find common ground with the images, sounds, and forms of artists to facilitate genuine interactions. Although art and science were closely linked during the time of Galileo and Leonardo, post18th century trends have defined art, design, engineering, and science as separate professions (Kemp 2006). Distinguishing artistic images from rigorous mathematical descriptions of the world has resulted in less and less interaction between the two groups. There is optimism among many art-science enthusiasts that the rapidly expanding realm of digital media, including an international open-source movement, will assist in addressing a common language (Wilson 2010); however, a shared computer literacy alone is unlikely to bridge the profession-specific jargon gap. Although acknowledged similarities underlie the work of artists and scientists in perceiving and describing the world, there are few formalized or easily recognized methods to utilize those commonalities for enhancing art-science collaborations. Recent interest in art-science collaborations seems to have focused on how artists can benefit from technological advancements in creating their works and how scientists can use
511
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
graphic artists to more effectively portray their results. But interactions between science/engineering and art/design can extend beyond the former providing novel technologies for latter or the latter providing clever ways to display the former. Long-standing arguments as to whether artists can accurately portray the intricacies of scientific theories or whether scientists are able to recognize the expressive nuances and subtle messages of artistic works may be moot. David Bohm (1996) noted that the value of art to a scientist is not the artist’s statement, but rather a perception of the world that sidesteps entrenched thoughts or approaches. Similarly, he saw the value of science to artists not as capturing theories in artistic works, but pondering scientific understandings as a means of expanding perspectives on art and the world. When considering communication among practitioners from different fields, words or numbers are often proposed as the best candidates for a common language, but this may not be the case. Spatial and temporal patterns may be better candidates simply because they are more universal. The notion that pattern could represent a language for scientists, artists, and designers is certainly not a new one. Pattern languages have been applied to both technological and natural systems, while art and music have been described in terms of pattern and rhythm (representing a temporal pattern) as a combination of elements that are repeated in a predictable or unpredictable fashion. This paper explores pattern languages as one possible means of enhancing collaborations among various practitioners (e.g., artists, scientists, designers) and interested laypersons.
Commonality and Universality In his book entitled The Artful Universe (1995), John Barrow examines the origins of our sense of beauty, order, and other aesthetics in light of the underlying spatial and temporal patterns of the physical world. In fact, we humans embody many of the same patterns (at least on a physical level) as those we perceive and appreciate (either consciously or unconsciously) in the world around us. Martin Kemp’s book Seen/Unseen (2006) discusses in detail the ways in which major scientific theories throughout history have been influenced by visualization and the ability of scientists to create visual models and to take inspiration from images they encounter. Similarly, auditory cues from nature and music have served as inspiration for scientific breakthroughs and for insightful perspectives on natural phenomena. Although only certain branches of science specifically focus on patterns and rhythms, data from many scientific fields can be expressed in terms of cycles, frequencies, and common descriptors of temporal patterns, as well as distributions, geometries, shapes, and other descriptors of spatial patterns. Generally regarded as the fundamental language of both science and engineering, mathematics is commonly linked to rhythmic sounds and movements that have been used to teach otherwise abstract subjects such as arithmetic (Alton 1998). Steen (1988) observed that mathematicians often seek patterns within science and, in fact, use mathematics to explain the relationships among patterns that describe and predict natural phenomena. A hierarchy of diverse patterns may be an ideal way to describe nature because humans are adept at distinguishing and characterizing the patterns in their environment (Mehaffy and Salingaros 2012). What kind of beauty permeates the geometries, cycles, symmetry, balance, and repeated patterns in nature that artists and musicians incorporate into their works and compositions and that scientists and engineers reveal in their theories and mathematics? Although the answer remains a mystery, there are an astonishing number of physical, social, and related systems that can be described by fractal relationships, 1/f structures, and hierarchical designs (Chen 2011). 512
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Fractals suggest underlying spatial and temporal patterns that often appear random or disordered at first glance, but are exquisitely ordered and appear in everything from music and art to landscapes and heartbeats. Is our perception of beauty related to the hierarchy of patterns (perhaps fractal-like) that lie within and all around us? In his book The Self-Made Tapestry, Philip Ball (1999) investigated the appearance and causes of patterns in nature and found that similar patterns within the physical, biological, and chemical worlds could be attributed to many different forces or mechanisms. As such, patterns seem to transcend their hypothesized causal mechanisms. Perhaps fractality, chaos, complexity, and self-organization simply represent different lenses through which we choose to perceive nature’s patterns—and then to portray or utilize them. Ball noted that similarities among patternforming systems serve to dissolve the division among disciplines, thus permitting scientists, economists, engineers, and others to communicate in the same language.
Pattern and Language The idea that pattern could, in and of itself, represent a form of communication or a language among professionals from different fields has been explored from several angles. Architect Christopher Alexander et al. (1977) introduced a pattern language consisting of hierarchically arranged parts, or design components, that are linked together by patterns capable of addressing and solving problems associated with each of its parts. The patterns themselves can be scaled up or down, creating what might be termed a hierarchical network that often reveals information on higher levels not present on lower ones. These patterns, which express possible relationships among parts, consist of rules that work equally well for the natural and designed worlds. It is the link among parts or components that facilitates a pattern language. Alexander’s use of the word “pattern” differs from the spatial arrangements discussed in the previous section inasmuch as the parts, which may or may not represent visible and/or auditory patterns, can be combined and assembled in countless ways to solve a problem, understand a system, or create a design. Pattern languages serve to enhance the communication among disciplines and to permit non-specialists to participate in design and decision-making processes (Ulrich 2006). Other benefits of pattern languages include encouraging people to truly observe the world and enabling researchers to link scientific research with practical solutions. Ulrich (2007) noted that Alexander was working toward providing a theoretical foundation for using pattern languages in the natural sciences, as well as for understanding order and complexity. The complexity of a system can be described geometrically as a result of interactions occurring on different scales within its hierarchy (Ay et al. 2011). Expanding on Alexander’s work, Nikos Salingaros (2000) explained that pattern languages assist in addressing the complexity inherent in a wide range of natural and human-designed systems. He also described a method to develop and validate pattern languages for different systems so that they can adapt to or even change our environment. Although patterns are distinct from scientific theories in their being derived from observations, rather than from first principles, they do provide a basis from which scientific theories can emerge and natural phenomena can be described (Salingaros 2000). Pattern language is applicable to many natural systems depicted by complex networks composed of individual components, or nodes, that connect and disconnect to one another according to a set of rules in achieving self-organization. The “language” of art is generally considered to include color, line, shape, form, texture, and space, whereas the “language” of design normally includes balance, emphasis, movement, proportion, rhythm, and variety (MMA 1992). Line, shape, form, texture, balance, proportion, 513
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
and variety are descriptions of pattern, whether related to geometry, repetition, orientation, scale, or symmetry. Movement, emphasis, and rhythm are patterns in time, rather than space, that can described dance, music, art and design. In fact, much of the music composed over the last four centuries displays fractal mathematics in both its rhythm and pitch, providing an aesthetically pleasing experience for listeners—perhaps because 1/f fractal relationships are a feature of human cognition (Levitin et al. 2012). Not surprisingly, geometric and pattern languages have been devised for music, permitting both rhythm and pitch to be described as transformations of sets of points within a musical network (Meredith 2012).
Examples The physical, chemical, biological, architectural, musical, and artistic worlds are replete with examples of systems described by patterns, rhythms, networks, and fractal-like relationships that are evident on scales ranging from the atomic to the cosmic. Even scientific data that are not specifically presented in terms of patterns, rhythms, or hierarchical relationships can often be perceived or interpreted in those terms or, at the very least, compared and contrasted with studies that do include such data (Marrin 2012a). Specific examples of employing spatial and temporal patterns to describe cross-disciplinary activities are provided in this section. Artistic Forensics. Artist Pamela Longobardi has documented and cleaned up plastic wastes carried by ocean currents to coastlines throughout the world. Her Drifters Project focuses on global-scale patterns created by the oceanic transport of plastics and on smaller-scale patterns of plastic wastes that are distributed along the world’s beaches (driftersproject.net). One facet of her art involves the use of selected plastic wastes to produce installations and exhibits on an even smaller scale that symbolically focus the viewer’s attention on the destructive usage and disposal of plastics (Longobardi 2010). Possessing a scientific background, she is able to approach each new site as a forensic researcher in distinguishing these patterns. Functional Art. Artist Mara Haseltine has created artificial reefs and other underwater habitats based on the geometry, patterning, and functionality of natural reefs and on the scalingup of microscopic structures in nature to facilitate the reintroduction of marine organisms. In addition to the structure of her reefs, she has experimented with various materials (e.g., glass, metal, porcelain) in order to select the optimal substrates for colonizing marine organisms (Haseltine 2013). Particularly interesting is her use of nature’s microscopic structures and patterns to create macroscopic designs (e.g., incorporating the patterns of fish gills in building artificial habitat structures for oysters). Her artwork incorporates geometries and patterns that serve valuable scientific/engineering purposes and that unite cultural and biological evolution through a practice known as “geotherapy” (calamara.com). Nature’s Rhythm Dance. Choreographer Kimi Eisele arranges various performances that experientially link audiences to local environmental issues and, in doing so, changing the perceptions and behaviors of people through movement. Based upon the natural rhythm of water’s movement and of humans’ interacting with water, audiences are presented with the opportunity to perceive local water challenges differently. In essence, she connects human physicality and sensation to an awareness of environmental problems and their solutions (newarticulations.org). Dance also serves as a vehicle for transposing the rhythms of water’s flow or tidal cycles into the movements of the human body, thus creating a sensation of water within the dancer and a unique perception of water for the audience. Earth’s Surface Networks. Water and ice in the form of rivers, oceans, and glaciers have cut through the planet’s surface in ways that create irregular landscapes; however, the organic 514
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
patterns displayed by watersheds on a regional scale are nearly identical to much smaller ones observed within subsections of the landscape. Although these fractal-like patterns have been largely unrecognized or ignored in designing most man-made landscapes and altering natural ones, there is recent interest in emulating them to design sustainable and eco-compatible creations such as green roofs, artificial wetlands, and stormwater networks (Marrin 2012b). The intricate patterns created by water influence a landscape’s hydrologic regimes, water quality and quantity dynamics, and ability to buffer extreme natural events. Earth’s Surface Art. NASA’s Applied Sciences Program displays satellite images of earth in a recent art book, prompting people to look more closely at the Earth and to ask themselves how nature was able to create such patterns (Prince 2013). The colors in the photos are spectacular as a result of computer-enhanced images that highlight specific wavelengths of emitted light—the majority of which are not visible to humans. This unique art form has become a valuable tool for scientists, who can discern spatial and temporal patterns for everything from vegetation health and ground temperatures to rock types and ocean chemistry. Perceptions gained from this type of artwork have permitted researchers to recognize and understand complex connections among global phenomena that would have otherwise gone unnoticed. Underlying Geometries. Platonic solids (see Figure 1) are the only angular 3-dimensional geometries composed entirely of regular polygons that create a sphere when spun around their center. Whereas this attribute may not seem significant, these five solids underlie a myriad of patterns in both nature and the arts. During the nineteenth century, mathematician Felix Klein identified an icosahedron as the “object” through which many branches of mathematics (e.g., projective geometry and differential equations) are connected. The interwoven icosahedrondodecahedron, first used by the ancient Greeks to map the earth and predict the equinoxes, was later adopted by Buckminster Fuller in designing his geodesic structures. Recently, physicist Garrett Lisi used the 248 vertices of a so-called E8 Lie geometry (based on an icosahedron) to describe the relationships among all known and predicted particles in nature (Merau 2007). Figure 1. Platonic solids include the tetrahedron (1), cube (2), octahedron (3), dodecahedron (4), and (5) icosahedron.
Art-Sci Ratios. Throughout history, architects and musicians have knowingly or unknowingly integrated the golden ratio (present in the five-fold symmetry of both an icosahedron and a dodecahedron) into their works, including the Parthenon and many classical 515
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
music pieces. The golden ratio is also ubiquitous in the natural world, where its mathematics underlies structures as diverse as the spiraling of seashells and galaxies, the branching of trees, and the proportions of the human body. Researchers have recently transposed the vibrational signatures of chemical mixtures, marine algae, and DNA molecules into the hearing range of humans to create their “nature-based” music (e.g., Alexjander and Deamer 1999). Similarly, inventor Jay Harman designed an impeller based on the spiral geometry of a whirlpool that is far more efficient than conventional pumps or stirrers for mixing large volumes of water (Van Vechten 2009). Data Representation. Whereas the use of patterns and rhythms to communicate art, music or dance is relatively straightforward, the use of spatial or temporal patterns to represent scientific data is not. Viegas and Wattenberg (2011) create data visualizations using colors and layers that feature personalized entry points for viewers, facilitating both their interest in and understanding of the data. Similar to conventional art, these authors have demonstrated (i) how scientists can learn from artists, (ii) how data can attain social, personal, or even emotional relevance, and (iii) how something as linear as text can be visualized as a network of words. Besides the data itself, the collective use of data in the form of physical samples or computer models possesses a rhythm related to scientists’ changing perceptions and behaviors (Chao 2012).
Components How might scientists and artists actually communicate with each other using either a temporal or spatial pattern language? To address this question, I return to the work of Christopher Alexander who designed his pattern language specifically for collaborations among people with different backgrounds or with limited knowledge of the subject (i.e., architecture). Pattern languages are popular among software developers specifically because they permit people to discuss strategies and problems without always referring to arcane programming codes (Ulrich 2006). Salingaros (2000) noted that pattern languages address two needs: understanding or controlling complex systems (natural and man-made) and designing a functionally coherent tool to solve problems. This paper focuses primarily on the former, although there is overlap between the two. Archetypal Patterns: Among the most fundamental patterns include the aforementioned Platonic solids, logarithmic spirals, and phi-based proportions that have been identified in nature, music, and art. As archetypes, their relationship to observed patterns may not be immediately obvious (e.g., relationships between the icosahedron and E8 Lie geometry or between the phi ratio and a human body). By contrast, certain crystals and biological structures display obvious archetypal patterns, which most often underlie structures that are easily recognizable, if not definable. Fractal Patterns: Patterns observed in the real world are largely complex, owing to the myriad processes that create them. The patterns are often fractal and recognized as organic, but are not necessarily identified with an archetype. The ability of humans to recognize fractal patterns has been attributed to their need to identify and contrast components of the environment, providing choices for their selecting and combining patterns to produce different outcomes (Mehaffy and Salingaros 2012). These authors associate fractal structures with sustainable environments, even though designers often impose a contrived order on their work that excludes fractality. Multiple Patterns: In addition to the fractal patterns appearing in art, design, music, and the entire natural world (over an almost infinite range of spatial and temporal scales), a larger 516
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
number of patterns are not truly fractals from a mathematical perspective, but are fractal-like and may appear more or less irregular. Of course, regular patterns also appear in architectural works and, occasionally, in nature. Patterns are frequently layered upon one another in a hierarchical manner, such that the building blocks of art or nature can be described by multiple patterns. Complex Networks: Networks are probably the most difficult patterns for people to recognize because the individual components and interactions between them can be either intangible or hidden. Nonetheless, perceiving and describing the world as complex networks sometimes permit a glimpse of their dynamics. Alexander et al. (1977) identified a pattern language itself as a network of patterns that are related to or dependent upon one another. Networks can display fractal or archetypal patterns on different scales and in countless combinations. Temporal Patterns: Arrangements in time, rather than space, create patterns that are identified by the same kinds of descriptors (e.g., archetypal, chaotic, fractal, regular, irregular, complex) previously discussed. Rhythmic archetypes for both music and dance commonly serve as a prototype for variations in pitch, timbre, and movement that underlie the diversity of expressions observed in different cultures (e.g., Burns 2010). Besides serving as descriptors of the natural world, temporal patterns (often in combination with spatial ones) are increasingly employed to elucidate, interpret, and clarify scientific data via the use of computer algorithms.
Structure So, how might the components of a language fit together to create a pattern language? This question has been addressed by a number of researchers who applied Alexander’s principles to their specific subject of interest. The patterns are often labeled or categorized in some manner to permit others to utilize a shared database and to discern pattern hierarchies. Kavanagh et al. (2006) introduced a conceptual framework that incorporates nature’s patterns, as well as ideal patterns conceptualized from nature and abstract patterns originating in the mind (see Figure 2). Essentially, the three types of patterns are linked together by the observer on the basis of his/her experience, training, personality, and culture. An abstract expression of a natural pattern, such as the arrangement of leaves on a tree, could be either artistic (based on a spatial interpretation) or rhythmic (based on a temporal interpretation). Similarly, the sequence of colors observed in a painting could be linked to an ideal pattern that is similar to the spectral lines for hydrogen. Obviously, the potential number of patterns to be labeled and categorized could be quite large initially; however, similarities in seemingly different patterns would likely reduce the number of ideal patterns over time. Moreover, it might become evident that many of the observed and ideal patterns (particularly the more complex ones) represent combinations of relatively simple ones. Distinguishing among natural, ideal, and abstract patterns would be a first step in categorization and could provide a useful framework for users to discern relationships among different forms of information (e.g., ideas, data, designs). The meaning to individual users is derived principally from relationships among patterns rather than from disconnected facts (Kavanagh et al. 2006). In addition to a general framework, most pattern languages possess a systematic approach to selecting, identifying, combining, and dissecting patterns that users can follow in understanding or investigating a particular subject.
517
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Figure 2. An example of the three types of patterns identified by Kavanagh et al. (2006) as applied to the natural formation of ice crystals from accumulated snowflakes.
Natural Pattern
Ideal Pattern
Abstract Patterns
Royalty-free images from 123RF
One of the most straightforward ways to systematically address pattern elements, types, and combinations is a hierarchy of collected patterns that are applied within specific contexts. The layering of collected patterns facilitates an understanding of how they can combine and how different combinations of lower-level patterns can create either similar or dissimilar higher-level patters. Connections between patterns exist both within and across levels, or layers, maintaining the connectivity that is essential to developing a pattern language (Salingaros 2000). A very simple diagram for pattern connectivity appears on Figure 3, whereby patterns are represented by short descriptions. Only the pattern of interest and its relative scale are required to communicate via a pattern language; however, other descriptors have proven to be valuable. Patterns languages are often created specifically to solve problems and usually include both syntactic and semantic definitions. A discussion of syntax is beyond the scope of this paper, but a number of semantic definitions provided by Borchers (2001) are provided in the context of understanding systems, rather than solving problems. Collected patterns include either novel or reoccurring patterns observed in nature or the arts. Each pattern is accompanied by references indicating how it has been linked to higher and lower levels within the hierarchy. Patterns are named (as are those in Figures 3 and 4) and ranked to assist users in discerning their universality and validity. Similarly, complex patterns are illustrated by photographs, diagrams, or symbolic patterns (as are those in Figures 2 and 5) to provide professionals and laypersons a glimpse of the full pattern. Examples (discussed in a previous section) accompany each pattern to indicate where the pattern has been previously encountered and how it has furthered an understanding of art, music, design, science, engineering, or any aspect of nature. Finally, a schematic or graphical sketch is created that outlines how patterns were either combined or separated into their component parts so that related subjects can be approached similarly using identical or different patterns. While these definitions formalize a model for pattern languages (Borchers 2001), the precise structure of any language will depend on the notations and formats that are ultimately selected by the users themselves. The nuances of language structure (i.e., the exact format for naming, ranking, illustrating, exemplifying, and referencing the patterns) will likely be less important than an unambiguous depiction of the collected patterns and their connections.
518
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Figure 3. A simple example of pattern connectivity among spatial and temporal elements (level 1) influencing the morphology or geometry of a watershed (level 2). Orienta4on of Stream Channels Historical Weather PaEerns
Dynamics of Ground Water Flow
Morphology of the Watershed
Loca4on of Grasses and Trees
Distribu4on of Soils and Rock Types
Figure 4. A simple example of a pattern hierarchy for the structure of molecular water that focuses on archetypal geometry, order, and perceived complexity.
Water Molecule Tetrahedral
Bulk Liquid Network Disordered
Liquid Water Clusters Icosahedral
Cluster Network Ordered
Liquid Water Clusters Dodecahedral
Possible structures that a pattern language could assume are shown on Figures 4 and 5 for molecular water. Individual water molecules serve as nodes for water’s primary network, which is sometimes contrasted with its secondary and tertiary networks that include water clusters and groupings of clusters. The molecules within water’s hierarchical networks change connections with one another as rapidly as a hundred trillion times per second and as slow as a few times per minute. Water displays layered geometries (e.g., icosahedral or dodecahedral clusters grouped fractally within a tetrahedral network) that exchange connections over a range of timescales. Whereas this description grossly oversimplifies molecular water, it demonstrates that otherwise intangible natural phenomena can be expressed as spatial and temporal patterns. 519
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Figure 5. A simple example of a flow diagram for the structure of molecular water that focuses on pattern illustration, rank, and periodicity in the form of connection exchange frequencies expressed as cycles per second (hertz).
Water Molecule Hundred trillion hertz Common -‐ 1
Bulk Water Network One trillion hertz Regular -‐ 3
Water Clusters One billion hertz Uncommon -‐ 5
Cluster Network One million hertz Irregular -‐ 9
Summary The technical and societal challenges we face at the dawn of the 21st century will likely require not only the continued development of 20th century technologies, strategies, and educational approaches, but also more fundamental shifts in the way that we perceive and relate to our world. Artists/designers and scientists/engineers are uniquely positioned via their respective training and creativities to view the world in different, but complementary, ways. A common language that bypasses their respective jargon, symbols, and styles would enhance such collaborations. One possibility is pattern languages, which have been applied to cross-disciplinary endeavors ranging from architecture to software design. Spatial and temporal patterns may be more universally recognized than are words or numbers and can be applied to describing, portraying, and even investigating both nature and human creations. Examples of artists using science and scientists using art to further their work or to reach a wider audience are numerous; however, formal or standardized approaches that encourage exchanges among practitioners lacking experience in both fields are rare. Identifying an essential collection of patterns, the supporting components, and some basic rules for structure is a first step toward building a common language that will continue to be altered and amended by the users. There is substantial commonality in the underlying spatial and temporal patterns of the arts and sciences that can be revealed and utilized in developing the language. We may find that the beauty of a painting, a musical score, a scientific theory, and a pristine landscape are related in a way that defies words, but not patterns.
520
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Acknowledgment Some of the material presented in this paper is based upon work supported by the National Science Foundation under Grant No. 1142510, Collaborative Research: EAGER: Network for Science, Engineering, Arts and Design (NSEAD) IIS, Human Centered Computing. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
References Alexander, Christopher, Sara Ishikawa, and Murray Silverstein. A Pattern Language. Oxford, UK: Oxford University Press (1977). Alexjander, Susan, and David Deamer. The infrared frequencies of DNA bases: science and art. Engineering in Medicine and Biology 18 (1999): 74. Alton, Cris Marie. The rhythm of mathematics. Classroom Compass 4 (1998): 2. Ay, N., E. Olbrich, N. Bertschinger, and J. Jost. A geometric approach to complexity. Chaos 21: 037103. Ball, Philip. The Self-Made Tapestry: Pattern Formation in Nature. University Press (1999).
Oxford, UK: Oxford
Barrow, John D. The Artful Universe. New York, NY: Oxford University Press (1995). Bohm, David. On Creativity. New York, NY: Routledge (1996). Borchers, J.O. A pattern approach to interaction design. Artificial Intelligence & Society 15 (2001): 359. Burns, James. Rhythmic archetypes in instrumental music from Africa and the Diaspora. Music Theory Online 16 (2010): 35 pp. Chao, Tiffany. Exploring the rhythms of scientific data use. Proceedings of the iConference on Culture, Design, and Society, University of Toronto (2012): 129. Chen, Yanguang. Zipf’s law, 1/f noise, and fractal hierarchy. Chaos, Solitons & Fractals 45 (2012): 63. Haseltine, Mara. Sustainable reef design to optimize habitat restoration. In: Innovative Methods of Marine Ecosystem Restoration, CRC Press (2013): in press. Kavanagh, S., C. Bartlett, and M. Marshall. Imagination in the natural sciences: pattern recognition, transformation, and expression. In: Proceedings of the 4th International Conference on Imagination and Education, Cape Breton University (2006): 10 pp. Kemp, Martin. Seen/Unseen: Art, Science, and Intuition from Leonardo to the Hubble Telescope. Oxford, UK: Oxford University Press (2006). Levitin, Daniel, Parag Chordia and Vinod Menon. Musical rhythm spectra from Bach to Joplin obey a 1/f power law. Proceedings of the National Academy of Sciences 109 (2012): 3716. Longobardi, Pamela. Drifters: Plastics, Pollution and Personhood. Milan, Italy: Charta (2010).
521
D. L. Marrin Enhancing Interactions Between Artists and Scientists Via a Common Language
Marrin, D.L. Hydromimicry: water as a model for technology and management. In: Energy Bulletin, Post Carbon Institute (11 August 2011): 9 pp. Marrin, D.L. Interactions among scientists/engineers and artists/designers in developing a common language and unique perspectives on today’s challenges. In: The SEAD Initiative for NSF Grant No. 1142510, Science-Engineering-Art-Design Network (2012a): 8 pp. Marrin, D.L. Water, fractals and watershed processes. In: Water Issues Related to Environmental Landscape Sustainability, Sousse University (2012b): 161. Mehaffy, Michael, and Nikos Salingaros. Science for designers: scaling and fractals. Metropolis Magazine (28 May 2012): POV. Merau, Zeeya. Is this the theory of everything? New Scientist (17 November 2007): 8. Meredith, David. A geometric language for representing structure in polyphonic music. In: Proceedings of the 13th ISMIR Conference, International Society for Music Information Retrieval (2012): 133. MMA. The Language of Art. Course material from the Morris Museum of Art website, Augusta, GA (1992): 10 pp. [http://www.themorris.org] Prince, Andrew. Earth as art: how did nature do that? National Public Radio (20 February 2013): 14 pp. Salingaros, Nikos. The structure of pattern languages. Architectural Research Quarterly 4 (2000): 149. Steen, Lynn Arthur. The science of patterns. Science 240 (1988): 611. Ulrich, Werner. The art of observation: understanding pattern languages. Journal of Research Practice 2 (2006): R1. Van Vechten, Amy. The flow of ideas. FLYP Discover 23 (February 2009): 6. Viegas, Fernanda, and Martin Wattenberg. How to make data look sexy. CNN Opinion (19 April 2011): 3 pp. Wilson, Stephen. Art meets science: speaking a lingua digica. New Scientist (13 May 2010): 41.
522
