By Natalia Andrienko
Exploratory information research (EDA) is ready detecting and describing styles, traits, and kinfolk in facts, stimulated by way of convinced reasons of research. As anything appropriate is detected in info, new questions come up, inflicting particular components to be seen in additional aspect. So EDA has an important charm: it includes speculation iteration instead of mere speculation testing.The authors describe intimately and systemize ways, suggestions, and strategies for exploring spatial and temporal info particularly. they begin by means of constructing a basic view of information constructions and features after which construct on best of this a normal activity typology, distinguishing among straight forward and synoptic projects. This typology is then utilized to the outline of current techniques and applied sciences, ensuing not only in concepts for selecting equipment yet in a suite of typical techniques for facts exploration. execs practising research will benefit from proven options - illustrated in lots of examples - for reuse within the catalogue of options offered. scholars and researchers will get pleasure from the targeted description and category of exploration concepts, which aren't constrained to spatial info in basic terms. additionally, the overall rules and techniques defined should be worthy for designers of recent equipment for EDA.
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Extra info for Exploratory analysis of spatial and temporal data: a systematic approach
Moreover, if a method for deriving attribute values for larger subsets from values for smaller subsets or individual elements is defined, it is possible to vary the level of detail on which the phenomenon is considered. This corresponds to the notion of “drilling” in data analysis, which is defined as a technique for navigating through levels of data granularity or detail. The term “drill up” or “roll up” means increasing the level of abstraction, and “drill down” means descending to finer granularity and more detail.
The set of earthquakes is a discrete referrer without ordering and without distances between the elements. 7 5 0 7 … 5 Characteristics Fig. 5. The structure of the dataset of earthquakes in the Marmara region (western Turkey) On the other hand, it is possible to treat space and time as referrers and the earthquakes as a phenomenon existing in space and time. In this case, both space and time have continuous value sets with distances between elements. The earthquakes are discrete phenomena, both spatially and temporally: they exist only at specific locations and specific time mo- 38 2 Data ments.
1998 … Prinzessin Sohn von Prinzessin Peterchen Penelope Prinzessin Sohn von Prinzessin Peterchen … 52q11c 52q00c 54q22c 54q00c 51q02c 50q96c 52q49c … References 12q09c 12q45c 21q30c 21q45c 15q31c 16q09c 24q66c … Characteristics Fig. 7. 1998 … Stork: Prinzessin Sohn von Prinzessin Peterchen Penelope none Prinzessin Sohn von Prinzessin Peterchen Penelope Prinzessin Sohn von Prinzessin Peterchen … Characteristics Fig. 8. Another view of the white stork migration dataset. 5 Weather in Germany This dataset contains monthly climate data measured at 43 locations in Germany (weather stations) during the period from January 1991 to May 2003.
Exploratory analysis of spatial and temporal data: a systematic approach by Natalia Andrienko