Start Date

16-8-2018 12:00 AM

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A dataphore is akin to a species of animal within a biological biome. Humans facilitate the movement of information between dataphores by taking knowledge and insights from around us and transposing that knowledge into other dataphoric forms (Vicente and Rasmussen, 1990). Like the relationship between bees and flowers - pollen is the information that is exchanged between us (Margalef, 1957). We cultivate and mediate the flow of data within dataphoric space. Yet, our role as the predominant content mediator for our portion of dataphoric space is not a singular role as we have created artificial dataphores to assist in the cultivation of data (e.g., data crawlers, data recognizers, data scrapers, data cleansers). Like data contained within a genetic sequence; its topology drives its expression (Kay, 1998). From tiny cellular data forms up to the most complex of dataphora, the topology of the data contained within a dataphora also drives its expression (Fath, Cabezas, and Pawlowski, 2003). Using this ontology, information systems researchers will be able to create, observe and analyze species of dataphores within a dataphora across multiple domains of scientific inquiry (e.g., sociological, anthropological, biological, medical, legal…). As we move forward, we expect that our dataphoric terminology will expand over time to encompass more constructs (Zhongguo, Hongqi, Ali, and Yile, 2017). Physics points us towards a “science of information” (Brukner and Zeilinger, 2005; Shannon, 1948; Susskind, 2007). Biological information systems points us towards an evolutionary perspective of data (Hirata and Ulanowicz, 1984; Ulanowicz and Abarca-Arenas, 1997). Another path of inquiry becomes available if we allow ourselves to view information systems as biologically styled entities. Ultimately, we see our creation of dataphoric space as a stimulating development for information systems research.

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Aug 16th, 12:00 AM

Theory of Dataphoric Space: A Dataphoric Systems Theory

A dataphore is akin to a species of animal within a biological biome. Humans facilitate the movement of information between dataphores by taking knowledge and insights from around us and transposing that knowledge into other dataphoric forms (Vicente and Rasmussen, 1990). Like the relationship between bees and flowers - pollen is the information that is exchanged between us (Margalef, 1957). We cultivate and mediate the flow of data within dataphoric space. Yet, our role as the predominant content mediator for our portion of dataphoric space is not a singular role as we have created artificial dataphores to assist in the cultivation of data (e.g., data crawlers, data recognizers, data scrapers, data cleansers). Like data contained within a genetic sequence; its topology drives its expression (Kay, 1998). From tiny cellular data forms up to the most complex of dataphora, the topology of the data contained within a dataphora also drives its expression (Fath, Cabezas, and Pawlowski, 2003). Using this ontology, information systems researchers will be able to create, observe and analyze species of dataphores within a dataphora across multiple domains of scientific inquiry (e.g., sociological, anthropological, biological, medical, legal…). As we move forward, we expect that our dataphoric terminology will expand over time to encompass more constructs (Zhongguo, Hongqi, Ali, and Yile, 2017). Physics points us towards a “science of information” (Brukner and Zeilinger, 2005; Shannon, 1948; Susskind, 2007). Biological information systems points us towards an evolutionary perspective of data (Hirata and Ulanowicz, 1984; Ulanowicz and Abarca-Arenas, 1997). Another path of inquiry becomes available if we allow ourselves to view information systems as biologically styled entities. Ultimately, we see our creation of dataphoric space as a stimulating development for information systems research.