Visual Analysis of a Large and Noisy Dataset

Author(s):  
Honour Chika Nwagwu ◽  
Constantinos Orphanides

Visual analysis has witnessed a growing acceptance as a method of scientific inquiry in the research community. It is used in qualitative and mixed research methods. Even so, visual data analysis is likely to produce biased results when used in analysing a large and noisy dataset. This can be evident when a data analyst is not able to holistically explore, all the values associated with the objects of interest in a dataset. Consequently, the data analyst may assess inconsistent data as consistent when contradiction associated with the data is not visualised. This work identifies incomplete analysis as a challenge in the visual data analysis of a large and noisy dataset. It considers Formal Concept Analysis (FCA) tools and techniques and prescribes the mining and visualisation of Incomplete or Inconsistent Data (IID) when dealing with a large and noisy dataset. It presents an automated approach for transforming IID from a noisy context whose objects are associated with mutually exclusive many-valued attributes, to a formal context.

2010 ◽  
Vol 58 (3) ◽  
pp. 393-401 ◽  
Author(s):  
R. Kruse ◽  
M. Steinbrecher

Visual data analysis with computational intelligence methodsVisual data analysis is an appealing and increasing field of application. We present two related visual analysis approaches that allow for the visualization of graphical model parameters and time-dependent association rules. When the graphical model is defined over purely nominal attributes, its local structure can be interpreted as an association rule. Such association rules comprise one of the most prominent and wide-spread analysis techniques for pattern detection, however, there are only few visualization methods. We introduce an alternative visual representation that also incorporates time since patterns are likely to change over time when the underlying data was collected from real-world processes. We apply the technique to both an artificial and a complex real-life dataset and show that the combined automatic and visual approach gives more and faster insight into the data than a fully-automatic approach only. Thus, our proposed method is capable of reducing considerably the analysis time.


2021 ◽  
Author(s):  
Marcel Meyer ◽  
Iuliia Polkova ◽  
Marc Rautenhaus

<p>We present the application of interactive 3-D visual analysis techniques using the open-source meteorological visualization framework Met.3D <strong>[1]</strong> for investigating ERA5 reanalysis data. Our focus lies on inspecting atmospheric conditions favoring the development of extreme weather events in the Arctic. Marine Cold Air Outbreaks (MCAOs) and Polar Lows (PLs) are analyzed with the aim of improving diagnostic indices for capturing extreme weather events in seasonal and climatological assessments. We adopt an integrated workflow starting with the interactive visual exploration of single MCAO and PL events, using an extended version of Met.3D, followed by the design and testing of new diagnostic indices in a climatological assessment. Our interactive visual exploration provides insights into the complex 3-D shape and dynamics of MCAOs and PLs. For instance, we reveal a slow wind eye of a PL that extends from the surface up into the stratosphere. Motivated by the interactive visual analysis of single cases of MCAOs, we design new diagnostic indices, which address shortcomings of previously used indices, by capturing the vertical extent of the lower-level static instability induced by MCAOs. The new indices are tested by comparison with observed PLs in the Barents and the Nordic Seas (as reported in the STARS data set). Results show that the new MCAO index introduced here has an important advantage compared with previously used MCAO indices: it is more successful in indicating the times and locations of PLs. We thus propose the new index for further analyses in seasonal climate predictions and climatological studies. The methods for interactive 3-D visual data analysis presented here are made freely available for public use as part of the open-source tool Met.3D. We thereby provide a generic tool that can be used for investigating atmospheric processes in ERA5 data by means of interactive 3-D visual data analysis. Met.3D can be used, for example, during an initial explorative phase of scientific workflows, as a complement to standard 2-D plots, and for detailed meteorological case-analyses in 3-D.</p><div><br><div> <p>[1] http://met3d.wavestoweather.de, https://collaboration.cen.uni-hamburg.de/display/Met3D/</p> </div> </div>


2022 ◽  
Vol 2146 (1) ◽  
pp. 012016
Author(s):  
Tianjun Wang ◽  
Cengceng Wang ◽  
Jiangtao Guo ◽  
dildar alim

Abstract Today, people are in an information explosion society, and visualization technology(VT) is an inevitable product of the development of the information society. With the emergence of multimedia products such as computers, networks, and communications, humans are paying more and more attention to data processing. Many countries in the world have already begun research in this area and have achieved remarkable results. VT is a core part of data analysis, also known as information processing and storage technology. It has a very extensive and important application in the field of data management. However, because the key information hidden in the data is often immersed in the massive data, it is necessary to filter the data information efficiently, and the visualization data analysis technology is a crucial part. This article adopts the experimental analysis method, which aims to provide a new method to solve the problems of traditional technology and the challenges that may arise in the future by further understanding the existing visual data analysis technology and development trend. According to the research results, the recognition rate of the optimized color visualization features under different classifiers is higher than that of the original emotional features. It can be seen that visual analysis technology is not limited to data sets with physical meaning, but can also be applied to abstract feature sets such as emotional features.


2021 ◽  
pp. 1-18
Author(s):  
Han Yang ◽  
Keyun Qin

The theory of three-way concept analysis has been developed into an effective tool for data analysis and knowledge discovery. In this paper, we propose neutrosophic three-way concept lattice by combining neutrosophic set with three-way concept analysis and present an approach for conflict analysis by using neutrosophic three-way concept lattice. Firstly, we propose the notion of neutrosophic formal context, in which the relationships between objects and attributes are expressed by neutrosophic numbers. Three pairs of concept derivation operators are proposed. The basic properties of object-induced and attribute-induced neutrosophic three-way concept lattices are examined. Secondly, we divide the neutrosophic formal context into three classical formal contexts and propose the notions of the candidate neutrosophic three-way concepts and the redundant neutrosophic three-way concepts. Two approaches of constructing object-induced (attribute-induced) neutrosophic three-way concept lattices are presented by using candidate, redundant and original neutrosophic three-way concepts respectively. Finally, we apply the neutrosophic formal concept analysis to the conflict analysis and put forward the corresponding optimal strategy and the calculation method of the alliance.


2021 ◽  
Vol 2 (3) ◽  
pp. 867-891
Author(s):  
Marcel Meyer ◽  
Iuliia Polkova ◽  
Kameswar Rao Modali ◽  
Laura Schaffer ◽  
Johanna Baehr ◽  
...  

Abstract. Recent advances in visual data analysis are well suited to gain insights into dynamical processes in the atmosphere. We apply novel methods for three-dimensional (3-D) interactive visual data analysis to investigate marine cold air outbreaks (MCAOs) and polar lows (PLs) in the recently released ERA5 reanalysis data. Our study aims at revealing 3-D perspectives on MCAOs and PLs in ERA5 and at improving the diagnostic indices to capture these weather events in long-term assessments on seasonal and climatological timescales. Using an extended version of the open-source visualization framework Met.3D, we explore 3-D perspectives on the structure and dynamics of MCAOs and PLs and relate these to previously used diagnostic indices. Motivated by the 3-D visual analysis of selected MCAO and PL cases, we conceptualize alternative index variants that capture the vertical extent of MCAOs and their distance to the dynamical tropopause. The new index variants are evaluated, along with previously used indices, with a focus on their skill as a proxy for the occurrence of PLs. Testing the association of diagnostic indices with observed PLs in the Barents and the Nordic seas for the years 2002–2011 shows that the new index variants based on the vertical structure of cold air masses are more skilful in distinguishing the times and locations of PLs, compared with conventional indices based on sea–air temperature difference only. We thus propose using the new diagnostics for further analyses in climate predictions and climatological studies. The methods for visual data analysis applied here are available as an open-source tool and can be used generically for interactive 3-D visual analysis of atmospheric processes in ERA5 and other gridded meteorological data.


2019 ◽  
Author(s):  
Rumen Manolov

The lack of consensus regarding the most appropriate analytical techniques for single-case experimental designs data requires justifying the choice of any specific analytical option. The current text mentions some of the arguments, provided by methodologists and statisticians, in favor of several analytical techniques. Additionally, a small-scale literature review is performed in order to explore if and how applied researchers justify the analytical choices that they make. The review suggests that certain practices are not sufficiently explained. In order to improve the reporting regarding the data analytical decisions, it is proposed to choose and justify the data analytical approach prior to gathering the data. As a possible justification for data analysis plan, we propose using as a basis the expected the data pattern (specifically, the expectation about an improving baseline trend and about the immediate or progressive nature of the intervention effect). Although there are multiple alternatives for single-case data analysis, the current text focuses on visual analysis and multilevel models and illustrates an application of these analytical options with real data. User-friendly software is also developed.


Author(s):  
Daniel Baum ◽  
Felix Herter ◽  
John Møller Larsen ◽  
Achim Lichtenberger ◽  
Rubina Raja

2021 ◽  
Vol 179 (3) ◽  
pp. 295-319
Author(s):  
Longchun Wang ◽  
Lankun Guo ◽  
Qingguo Li

Formal Concept Analysis (FCA) has been proven to be an effective method of restructuring complete lattices and various algebraic domains. In this paper, the notion of contractive mappings over formal contexts is proposed, which can be viewed as a generalization of interior operators on sets into the framework of FCA. Then, by considering subset-selections consistent with contractive mappings, the notions of attribute continuous formal contexts and continuous concepts are introduced. It is shown that the set of continuous concepts of an attribute continuous formal context forms a continuous domain, and every continuous domain can be restructured in this way. Moreover, the notion of F-morphisms is identified to produce a category equivalent to that of continuous domains with Scott continuous functions. The paper also investigates the representations of various subclasses of continuous domains including algebraic domains and stably continuous semilattices.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ting Qian ◽  
Ling Wei

As an important tool for data analysis and knowledge processing, formal concept analysis (FCA) has been applied to many fields. In this paper, we introduce a new method to find all formal concepts based on formal contexts. The amount of intents calculation is reduced by the method. And the corresponding algorithm of our approach is proposed. The main theorems and the corresponding algorithm are examined by examples, respectively. At last, several real-life databases are analyzed to demonstrate the application of the proposed approach. Experimental results show that the proposed approach is simple and effective.


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