Towards a Taxonomy of the Model-Ladenness of Data

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data

Shift-life interactive art: mixed-reality artificial ecosystem simulation

This article presents a detailed design, development and implementation of a Mixed Reality Art-Science collaboration project which was exhibited during Darwin’s bicentenary exhibition at Shrewsbury, England. As an artist-led project the concerns of the artist were paramount, and this article presents Shift-Life as part of an on-going exploration into the parallels between the non-linear human thinking process and computation using semantic association to link items into ideas, and ideas into holistic concepts. Our art explores perceptions and states of mind as we move our attention between the simulated world of the computer and the real-world we inhabit, which means that any viewer engagement is participatory rather than passive. From a Mixed Reality point of view, the lead author intends to explore the convergence of the physical and virtual, therefore the formalization of the Mixed Reality system, focusing on the integration of artificial life, ecology, physical sensors and participant interaction through an interface of physical props. It is common for digital media artists to allow viewers to activate a work either through a computer screen via direct keyboard or mouse manipulation, or through immersive means to activate their work, for “Shift-Life” the artist was concerned with a direct “relational” approach where viewers would intuitively engage with the installation’s everyday objects, and with each other, to fully experience the piece. The Mixed Reality system is mediated via physical environmental sensors, which affect the virtual environment and autonomous agents, which in turn reacts and is expressed as virtual pixels projected onto a physical surface. The tangible hands-on interface proved to be instinctive, attractive and informative on many levels, delivering a good example of collaboration between the Arts and Science

Petrophysical and rock physics analyses for characterization of complex sands in deepwater Niger delta, Nigeria

Characterization of complex sand reservoirs in deepwater of Niger Delta was carried out through petrophysical and rock physics evaluation of well log data from three wells. Petrophysical analysis to determine clay volume, porosity, lithologies and hydrocarbon saturation were made. Rock physics was studied in velocity-porosity plane to analyze the influence of depositional and diagenetic features on the reservoirs. Cross-plots of different elastic parameters, using linear regression and cluster analysis, were generated for lithologic and fluid fill identification and to differentiate between the hydrocarbon bearing sands, brine sands and shale. Variance attribute was extracted on seismic time slice in order to image the complex sand distribution in the area. Three reservoirs of turbidite origin were identified within the upper fan to lower fan area. Petrophysical results revealed gas bearing reservoir units with less than 20% shale volume and porosity of 25-31%. Lambda-Mu-Rho (LMR) cross-plots for the reservoirs show gas saturated data cloud and trend. Ratio-Difference (R-D) cluster analysis of elastic rock properties shows a distinct trend and data cloud that represents lithofacies units and fluid fills. The study concludes that the reservoirs simulated contact cement and friable models with properties that ranged from highly porous, well sorted and poorly consolidated sand to fairly sorted and highly cemented sands. The results provide a model that increases the possibility of finding reservoir sand, while mitigating the risk involved in finding hydrocarbons