CocoaSoils data interoperability vision

Data-generative approaches are becoming increasingly common in modern life science research. Agronomy, food, plant sciences, and biodiversity are examples of complementary scientific disciplines that can greatly benefit from the integration and re-sue of the data that they produce. For instance, at WENR ..

Development of an open-source toolbox for the analysis and visualization of remotely sensed time series

The GEONETCast data-dissemination system delivers free multi-source raw satellite images and processed products to users worldwide; from these data, users can construct long time series to study dynamic phenomena. To explore these dynamics, using an animation with few controls is common practice. But animations easily produce information overload leading to change blindness, a problem that can be addressed in various ways. We present a combination of analytical and visual functionalities to better support visual exploration of animated time series. Analytical pre-processing functions include slicing and tracking of objects of interest. Results of the slicing and the tracking are input to the visualization environment, which is further enriched by tools to make various time, attribute, and area selections and by options to visually enhance selections relative to their surroundings, visualize the path of moving objects, and multiple layers. The resulting toolbox is dedicated to visual exploration and analysis of dynamic phenomena in time series. A case study demonstrates, with a use scenario, how it works. Early exposure of some visualization functions to users has already led to improvements, but more extensive testing will follow after further enrichment of the toolbox. Directions of future research are described

Visual mining of moving flock patterns in large spatio-temporal data sets using a frequent pattern approach

The popularity of tracking devices continues to contribute to increasing volumes of spatio-temporal data about moving objects. Current approaches in analysing these data are unable to capture collective behaviour and correlations among moving objects. An example of these types of patterns is moving flocks. This article develops an improved algorithm for mining such patterns following a frequent pattern discovery approach, a well-known task in traditional data mining. It uses transaction-based data representation of trajectories to generate a database that facilitates the application of scalable and efficient frequent pattern mining algorithms. Results were compared with an existing method (Basic Flock Evaluation or BFE) and are demonstrated for both synthetic and real data sets with a large number of trajectories. The results illustrate a significant performance increase. Furthermore, the improved algorithm has been embedded into a visual environment that allows manipulation of input parameters and interactive recomputation of the resulting flocks. To illustrate the visual environment a data set containing 30 years of tropical cyclone tracks with 6 hourly observations is used. The example illustrates how the visual environment facilitates exploration and verification of flocks by changing the input parameters and instantly showing the spatio-temporal distribution of the resulting flocks in the Space-Time Cube and interactively selecting

A conceptual framework and taxonomy of techniques for analyzing movement

Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic information science, database technology, and data mining. We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake

A Descriptive Framework for Temporal Data Visualizations Based on Generalized Space-Time Cubes

International audienceWe present the generalized space-time cube, a descriptive model for visualizations of temporal data. Visualizations are described as operations on the cube, which transform the cube's 3D shape into readable 2D visualizations. Operations include extracting subparts of the cube, flattening it across space or time or transforming the cubes geometry and content. We introduce a taxonomy of elementary space-time cube operations and explain how these operations can be combined and parameterized. The generalized space-time cube has two properties: (1) it is purely conceptual without the need to be implemented, and (2) it applies to all datasets that can be represented in two dimensions plus time (e.g. geo-spatial, videos, networks, multivariate data). The proper choice of space-time cube operations depends on many factors, for example, density or sparsity of a cube. Hence, we propose a characterization of structures within space-time cubes, which allows us to discuss strengths and limitations of operations. We finally review interactive systems that support multiple operations, allowing a user to customize his view on the data. With this framework, we hope to facilitate the description, criticism and comparison of temporal data visualizations, as well as encourage the exploration of new techniques and systems. This paper is an extension of Bach et al.'s (2014) work

Особенности клинического течения, лабораторных и инструментальных маркеров сосудистого воспаления в киргизской когорте больных артериитом Такаясу

Lack of highly sensitive and specific methods of laboratory and instrumental diagnostics leads to difficulties in timely verification of Takayasu's arteritis (AT).Objective: to analyze the clinical course, laboratory and instrumental markers of vascular inflammation in the Kyrgyz cohort of patients with AT.Patients and methods. The study included 75 patients with a reliable diagnosis of AT, who were hospitalized and observed on an outpatient basis at the clinic of the National Center for Cardiology and Therapy named after acad. Mirsaida Mirrakhimova from January 2011 to April 2022. Patients were examined using clinical, laboratory and instrumental methods once every 2 years. The follow-up period was 1–5 years in 45 (60%) patients and 6–15 years in the remaining 30 (40%) patients. All patients underwent a clinical and standard laboratory work-up with CRP and interleukin 6 levels assessment, as well as ultrasound Dopplerography of peripheral arteries in the color Doppler mapping mode and multislice computed tomography-panaortography.Results and discussion. Lesions of the common carotid (85.33%) and subclavian (84%) arteries were detected more often. Involvement of the abdominal aorta was noted in 60% of patients and was accompanied by stenosis of the renal arteries in 100% of cases. The clinical picture of the disease was mainly represented by cardiac pathology in the form of arterial hypertension (84%) and aortic regurgitation (68%) with the development of decompensated chronic heart failure in 15% of patients. During the dynamic observation, significant improvement in the course of the disease, clinical symptoms, decrease in the severity of vascular changes were not revealed, with the exception of a decrease in the clinical activity of AT (p<0.05) in one third of patients (37.4%). Conclusion. The severity of clinical manifestations and the course of AT in the Kyrgyz cohort was due to cardiovascular pathology. As dynamic observation showed, the lack of significant improvement in the course of the disease was largely due to the long duration of chronic inflammation, late diagnosis, development of irreversible stenotic, occlusive and aneurysmal changes, as well as the fact that patients did not receive adequate pathogenetic therapy at the onset of the disease. Keywords: <0.05) in one third of patients (37.4%).Conclusion. The severity of clinical manifestations and the course of AT in the Kyrgyz cohort was due to cardiovascular pathology. As dynamic observation showed, the lack of significant improvement in the course of the disease was largely due to the long duration of chronic inflammation, late diagnosis, development of irreversible stenotic, occlusive and aneurysmal changes, as well as the fact that patients did not receive adequate pathogenetic therapy at the onset of the disease.Трудности своевременной верификации артериита Такаясу (АТ) обусловлены отсутствием высокочувствительных и специфических методов лабораторной и инструментальной диагностики.Цель исследования – анализ клинического течения, лабораторных и инструментальных маркеров сосудистого воспаления в киргизской когорте больных АТ.Пациенты и методы. В исследование включено 75 больных с достоверным диагнозом АТ, находившихся на стационарном лечении и наблюдавшихся амбулаторно в клинике Национального центра кардиологии и терапии им. акад. Мирсаида Миррахимова с января 2011 по апрель 2022 г. Обследование больных с использованием клинических, лабораторных и инструментальных методов проводилось 1 раз в 2 года. Срок наблюдения составил у 45 (60%) пациентов 1–5 лет и у остальных 30 (40%) 6–15 лет. Всем пациентам проведены клиническое и стандартное лабораторное обследование с определением уровня СРБ и интерлейкина 6, а также ультразвуковая допплерография периферических артерий в режиме цветового допплеровского картирования и мультиспиральная компьютерная томография-панаортография.Результаты и обсуждение. В основном выявлялось поражение общих сонных (85,33%) и подключичных (84%) артерий. Вовлечение брюшной аорты отмечалось у 60% больных и в 100% случаев сопровождалось стенозом почечных артерий. Клиническая картина заболевания была представлена преимущественно кардиальной патологией в виде артериальной гипертензии (84%) и аортальной регургитации (68%) с развитием декомпенсированной хронической сердечной недостаточности у 15% больных. При динамическом наблюдении значимого улучшения течения болезни, клинических симптомов, уменьшения выраженности сосудистых изменений не выявлено, за исключением снижения клинической активности АТ (p<0,05) у трети больных (37,4%). Заключение. Тяжесть клинических проявлений и течения АТ в киргизской когорте была обусловлена сердечно-сосудистой патологией. Как показало динамическое наблюдение, отсутствие значимого улучшения в течении болезни во многом было связано с большой длительностью хронического воспаления, поздней диагностикой, развитием необратимых стенотических, окклюзионных и аневризматических изменений, а также с тем, что больные не получали адекватную патогенетическую терапию в дебюте заболевания. Ключевые слова: артериит Такаясу; активность; аневризма; мониторинг; стеноз; окклюзия; ультразвуковая допплерография; томография. Контакты: Гулазык Маликовна Койлубаева; [email protected] Для ссылки: Койлубаева ГМ, Болотбекова АМ, Егорова ОН и др. Особенности клинического течения, лабораторных и инструментальных маркеров сосудистого воспаления в киргизской когорте больных артериитом Такаясу. Современная ревматология. 2022;16(5): 38–45. DOI: 10.14412/1996-7012-2022-5-38-45 Clinical course, laboratory and instrumental markers of vascular inflammation in the Kyrgyz cohort of patients with Takayasu's arteritis Koilubaeva G.M.1 , Bolotbekova A.M.1 , Egorova O.N.2 , Turatbekova A.T.1 , Tarasova G.M.2 , Suyunbai kyzy G.1 , Chukubaev M.A.1 , Turdukulov Z.E.1 , Usupbaeva D.A.1 1 National Center for Cardiology and Therapy named after acad. Mirsaida Mirrakhimova, Ministry of Health of the Kyrgyz Republic, Bishkek; 2 V.A. Nasonova Research Institute of Rheumatology, Moscow 1 3, Togoloka Moldo Street, Bishkek 720040, Kyrgyz Republic; 2 34A, Kashirskoe Shosse, Moscow 115522, Russia Lack of highly sensitive and specific methods of laboratory and instrumental diagnostics leads to difficulties in timely verification of Takayasu's arteritis (AT)><0,05) у трети больных (37,4%).Заключение. Тяжесть клинических проявлений и течения АТ в киргизской когорте была обусловлена сердечно-сосудистой патологией. Как показало динамическое наблюдение, отсутствие значимого улучшения в течении болезни во многом было связано с большой длительностью хронического воспаления, поздней диагностикой, развитием необратимых стенотических, окклюзионных и аневризматических изменений, а также с тем, что больные не получали адекватную патогенетическую терапию в дебюте заболевания

Visualizing the evolution of image features in time-series: supporting the exploration of sensor data

Sensor image repositories are becoming the fastest growing archives of spatio-temporal information and they are only projected to grow through the twenty-first century. This continuous data flow leads to large time-series and accordingly, geoscientists are often confronted with the amount of data that need to be explored and the phenomena, present in time-series, to be understood and modeled. In this study, an approach to visual exploration of time-series of sensor data has been proposed. The approach describes exploration as a process where attention, memory, graphics and behaviour of the represented phenomena interrelate. It outlines the framework of how graphics can assist memory and attention by representing image features and their evolution. The main role of graphics in data exploration is to facilitate memorization and to guide visual search in the sensor data. Reasons why the current graphics fall short in supporting the exploration process are also outlined. These are related to insufficient support for re-presentation of image features. The review is further supported by case studies of remote sensing data exploration where the users are primarily interested in identifying, tracing and perceiving the evolution of two highly dynamic image features. The cases dealt with rip channels and convective clouds. Because geoscientists are primarily interested in image features, a workable solution is to focus on just those features -- that is to automatically extract and track them. For that purpose, the feature extraction and tracking algorithms used in computer vision, image processing and scientific visualization are reviewed and a post-processing tracking approach based on the overlap measure is adopted. Computational preprocessing is, amongst others, used to generate the quantitative attributes of objects. The attributes of image features are emphasized in the visualizations with rich graphical and interactive exploratory functionality. Further, a research prototype - a multiple-view exploratory environment based on Space-Time Cube metaphor was proposed. The four views of the prototype are linked and enable object brushing and view manipulation. Dynamic linking enables progressive knowledge construction because users can easily switch between spatial, attribute and temporal--oriented feature analysis. With the interactivity, the users are supported to search for features of interest, sieve them to further reduce the complexity, and focus attention on the selected objects. In particular, exploration of the essence of the object's evolution and history were supported. It was important, however, to verify the concepts developed by user testing. Series of users test conducted involving expert and novice participants. Two exploratory tools were tested: `typical' animation and the research prototype developed during this study. Two case studies described have been used with similar set of exploratory question. The test participants provided faster and more complete and accurate answers using the prototype than the animation. They were also more satisfied with the prototype than with the animation when answering these questions. Thus overall, the test results supported the initial hypothesis - that representing image features and their evolution assist users in exploring the time-series of sensor data

Visualization of events in time - series of remote sensing data

The approach described here facilitates the exploration of time-series of remote sensing data by offering a set of interactive visual functions that allows studying the behaviour of dynamic phenomena, events and evolution of phenomena over time. Essentially we simulate the human visual system by applying an object tracking algorithm, which is based on attributes description of segmented regions: position, size, spatial overlap, centroid, and volume. The algorithm compares the attributes of each region in successive frames and finds the continuous paths of the object through time. These paths describe the characteristics of the object in each time step and for each object certain interesting ‘events ’ can be described. Examples of events are: continuation, appearance/disappearance, and split/merge of the phenomena. Based on the object paths, a visualization environment with ‘temporal functionality ’ is created with a wide range of tools to support interactive exploration of events and the object’s evolution. In particular, the event graph is proposed which in combination with other visualizations will make the process of detection and exploration of the dynamic phenomena independent of the perception and experience of the observer