Gennady Andrienko

Gennady Andrienko
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS | IAIS · Knowledge Discovery (KD)

Prof. Dr.

About

343
Publications
102,408
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
13,421
Citations
Additional affiliations
July 1997 - present
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS
Position
  • lead scientist

Publications

Publications (343)
Article
Full-text available
With the objective to enhance human performance and maximize engagement during the performance of tasks, we aim to advance automation for decision making in complex and large-scale multi-agent settings. Towards these goals, this paper presents a deep multi agent reinforcement learning method for resolving demand - capacity imbalances in real-world...
Article
Currently, the methodological and technical developments in visual analytics, as well as the existing theories, are not sufficiently grounded by empirical studies that can provide an understanding of the processes of visual data analysis, analytical reasoning and derivation of new knowledge by humans. We conducted an exploratory empirical study in...
Article
We consider the general problem known as job shop scheduling, in which multiple jobs consist of sequential operations that need to be executed or served by appropriate machines having limited capacities. For example, train journeys (jobs) consist of moves and stops (operations) to be served by rail tracks and stations (machines). A schedule is an a...
Article
We propose an approach to underpin interactive visual exploration of large data volumes by training Learned Visualization Index (LVI). Knowing in advance the data, the aggregation functions that are used for visualization, the visual encoding, and available interactive operations for data selection, LVI allows to avoid time-consuming data retrieval...
Article
We introduce a new research area in visual analytics (VA) aiming to bridge existing gaps between methods of interactive machine learning (ML) and eXplainable Artificial Intelligence (XAI), on one side, and human minds, on the other side. The gaps are, first, a conceptual mismatch between ML/XAI outputs and human mental models and ways of reasoning,...
Article
Full-text available
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are bei...
Article
Full-text available
A correction to this paper has been published: https://doi.org/10.1007/s41060-021-00260-6
Article
Full-text available
Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach...
Article
Full-text available
How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and...
Article
Full-text available
The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different re...
Chapter
Full-text available
Visual analytics science develops principles and methods for efficient human–computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human analysts can effectively utilize their unique capabilities: the power of seeing, interpreting, linking, and reasoning. Visual analytics resear...
Chapter
Visual analytics techniques support the process of data analysis, reasoning, and knowledge building performed by a human analyst. The techniques combine interactive, human-controllable visual displays with interactive operations for data querying and filtering, data transformations, calculation of derived data, and application of computational tech...
Conference Paper
Background We are investigating access to sleep services for OSA knowing there are large numbers undiagnosed in the community. In the Track and Know project (EU-AG780754) we analysed referrals for OSA assessing the impact of social deprivation. Methods We tested the null hypotheses that: per capita equal numbers are referred from areas of high and...
Article
2020 Copyright for this paper by its author(s). In the context of data visualization and analytics, this report outlines some of the challenges and emerging applications that arise in the Big Data era. In particularly, fourteen distinguished scientists from academia and industry, and diverse related communities, i.e., Information Visualization, Hum...
Article
Data classification, i.e. organising data items in groups (classes), is a general technique widely used in data visualisation and cartography, in particular, for creation of choropleth maps. Conventionally, data are classified by dividing the data range into intervals and assigning the same symbol or colour to all data falling within an interval. F...
Article
Full-text available
A method for citywide traffic analysis is introduced based on the combination of visual and analytical approaches. Large volumes of GPS data collected from urban vehicles are utilized. In the method, a traffic condition map is constructed, composed of five different layers featuring traffic conditions, road linkage, travel patterns, congestion zone...
Article
Full-text available
The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable definition of the concept of a pattern in a data distribution as a combination of multiple interrelated elements of two or more data components that can be represented and treated as a...
Article
Full-text available
In various domains, there are abundant streams or sequences of multi-item data of various kinds, e.g. streams of news and social media texts, sequences of genes and sports events, etc. Comparison is an important and general task in data analysis. For comparing data streams involving multiple items (e.g., words in texts, actors or action types in ac...
Chapter
A graph is a mathematical model for representing a system of pairwise relationships between entities. The term “graph” or “graph data” is quite often used to refer, actually, to a system of relationships, which can be represented as a graph, rather than to the mathematical model itself. In line with this practice, the term “graph” is used in this c...
Chapter
Data scientists usually aim at building computer models. Computeroriented modelling methods and software tools are developed in statistics, machine learning, data mining, and various specialised disciplines, such as spatial statistics, transportation research, and animal ecology. However, valid and useful computerbased models cannot be obtained by...
Chapter
There are two major types of temporal data, events and time series of attribute values, and there are methods for transforming one of them into the other. For events, a general analysis task is to understand how they are distributed in time. For time series, as well as for events of diverse kinds, a general task is to understand how the attribute v...
Chapter
Texts are created for humans, who are trained to read and understand them. Texts are poorly suited for machine processing; still, humans need computer help when it is necessary to gain an overall understanding of characteristics and contents of large volumes of text or to find specific information in these volumes. Computer support in text analysis...
Chapter
We begin with a simple motivating example that shows how putting spatial data on a map and seeing spatial relationships can help an analyst to make important discoveries. We consider possible contents and forms of spatial data, the ways of specifying spatial locations, and how to use spatial references for joining different datasets. We discuss the...
Chapter
There are different kinds of spatio-temporal phenomena, including events that occur at different locations, movements of discrete entities, changes of shapes and sizes of entities, changes of conditions at different places and overall situations across large areas. Spatio-temporal data may specify positions, times, and characteristics of spatial ev...
Chapter
Visual analytics approaches combine interactive visualisations with the use of computational techniques for data processing and analysis. Combining visualisation and computation has two sides. One side is computational support to visual analysis: outcomes of computations are intended to provide input to human cognition; for this purpose, they are r...
Chapter
An illustrated example of problem solving is meant to demonstrate how visual representations of data support human reasoning and deriving knowledge from data.We argue that human reasoning plays a crucial role in solving non-trivial problems. Even when the primary goal of data analysis is to create a predictive model to be executed by computers, thi...
Chapter
Images and video recordings are commonly categorised as unstructured data, which means that they are not primarily suited for computer analysis. The contents of unstructured data cannot be adequately represented by numbers or symbols and require the power of human vision for extracting meaningful information. While images and video are well suited...
Chapter
In this chapter, we discuss how visual analytics techniques can support you in investigating and understanding the properties of your data and in conducting common data processing tasks. We consider several examples of possible problems in data and how they may manifest in visual representations, discuss where and why data quality issues can appear...
Chapter
We introduce the basic principles and rules of the visual representation of information. Any visualisation involves so-called visual variables, such as position along an axis, size, colour hue and lightness, and shape of a graphical element. The variables differ by their perceptual properties, and it is important to choose appropriate variables dep...
Chapter
One very common challenge that every data scientists has to deal with is to make sense of data sets with many attributes, where “many” can sometimes be tens, sometimes hundreds, and even thousands. Whether your goal is to do exploratory analysis on the relationships between the attributes, or to build models of the underlying phenomena, working wit...
Chapter
Analysis is always focused on a certain subject, which is a thing or phenomenon that needs to be understood and, possibly, modelled. The data science process involves analysis of three different subjects: data, real world phenomena portrayed in the data, and computer models derived from the data. A subject can be seen as a system composed of multip...
Chapter
This chapter very briefly summarises the main ideas and principles of visual analytics, while the main goal is to show by example how to devise new visual analytics approaches and workflows using general techniques of visual analytics: abstraction, decomposition, selection, arrangement, and visual comparison.We take an example of an analysis scenar...
Article
Visual analytics is a research discipline that is based on acknowledging the power and the necessity of the human vision, understanding, and reasoning in data analysis and problem solving. Visual analytics develops methods, analytical workflows, and software tools for analysing data of various types, particularly, spatio-temporal data, which can de...
Chapter
Visual analytics is a research discipline that is based on acknowledging the power and the necessity of the human vision, understanding, and reasoning in data analysis and problem solving. It develops a methodology of analysis that facilitates human activities by means of interactive visual representations of information. By examples from the domai...
Article
Full-text available
Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approac...
Preprint
Full-text available
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being...
Article
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are bei...
Chapter
The maritime ecosystem has undergone through changes due to the increasing use of information systems and smart devices. The newly introduced technologies give rise to new attack surface in maritime infrastructures. In this position paper, we propose the MAritime Threat INtelligence FRAMEwork (MAINFRAME), which is tailored towards collection and an...
Conference Paper
Full-text available
In the context of data visualization and analytics, this report out-lines some of the challenges and emerging applications that arise in the Big Data era. In particularly, fourteen distinguished scientists from academia and industry, and diverse related communities, i.e., Information Visualization, Human-Computer Interaction, Machine Learning, Data...
Book
This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with adv...
Book
This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail. The book begins by introducing the m...
Preprint
Full-text available
In this article, we report on the efficiency and effectiveness of multiagent reinforcement learning methods (MARL) for the computation of flight delays to resolve congestion problems in the Air Traffic Management (ATM) domain. Specifically, we aim to resolve cases where demand of airspace use exceeds capacity (demand-capacity problems), via imposin...
Article
Full-text available
As the number of moving objects increases, the challenges for achieving operational goals w.r.t. the mobility in many domains that are critical to economy and safety emerge dramatically. In domains such as air traffic management, this dictates a shift of operations’ paradigm from location based, as it is today, to trajectory based, where trajectori...
Article
A possible objective in analyzing trajectories of multiple simultaneously moving objects, such as football players during a game, is to extract and understand the general patterns of coordinated movement in different classes of situations as they develop. For achieving this objective, we propose an approach that includes a combination of query tech...
Conference Paper
Introduction Royal Papworth Hospital performs >10,000 home oximetry tests p.a. across a large area with challenging road-infrastructure. We have developed a distributed system of oximetry exchange facilities (EF’s) at outreach-clinics and GP surgeries over several years without a ‘masterplan’. As part of the Track and Know project (EU2020) we exami...
Preprint
Full-text available
The maritime ecosystem has undergone through changes due to the increasing use of information systems and smart devices. The newly introduced technologies give rise to new attack surface in maritime infrastructures. In this position paper, we propose the MAritime Threat INtelligence FRAMEwork (MAINFRAME), which is tailored towards collection and an...
Article
User behaviour analytics (UBA) systems offer sophisticated models that capture users' behaviour over time with an aim to identify fraudulent activities that do not match their profiles. Motivated by the challenges in the interpretation of UBA models, this paper presents a visual analytics approach to help analysts gain a comprehensive understanding...
Conference Paper
Full-text available
We present a big data framework for the prediction of streaming trajectory data, enriched from other data sources and exploiting mined patterns of trajectories, allowing accurate long-term predictions with low latency. To meet this goal, we follow a multi-step methodology. First, we efficiently compress surveillance data in an online fashion, by co...
Article
Full-text available
We propose an approach to interactive visual exploration of trajectories of moving objects in which trajectories are mapped onto different coordinate systems enabling the analyst to look at different aspects of the movement. Geographic visualization techniques can be applied to these coordinate systems in the same way as in usual geographic maps. M...
Article
Full-text available
Volunteered Geographic Information (VGI) in the form of actively and passively generated spatial content offers extensive potential for a wide range of applications. Realising this potential however requires methods which take account of the specific properties of such data, for example its heterogeneity, quality, subjectivity, spatial resolution a...
Article
The concept of place connectedness (traditionally termed 'accessibility') refers to the ability of people to reach various services and to participate in activities. Connectedness by public transport is especially important for underprivileged and elderly people while the active use of public transport by the general population contributes in reduc...
Article
We define behavior as a set of actions performed by some agent during a period of time. We consider the problem of analyzing a large collection of behaviors by multiple agents, more specifically, identifying typical behaviors as well as spotting behavior anomalies. We propose an approach leveraging topic modeling techniques -- LDA (Latent Dirichlet...
Article
Full-text available
Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques. Findings of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems...
Conference Paper
In air traffic management and control, movement data describing actual and planned flights are used for planning, monitoring and post-operation analysis purposes with the goal of increased efficient utilization of air space capacities (in terms of delay reduction or flight efficiency), without compromising the safety of passengers and cargo, nor ti...
Article
Full-text available
Data quality management, especially data cleansing, has been extensively studied for many years in the areas of data management and visual analytics. In the paper, we first review and explore the relevant work from the research areas of data management, visual analytics and human-computer interaction. Then for different types of data such as multim...
Article
Full-text available
We propose an approach to analyzing data in which texts are associated with spatial and temporal references with the aim to understand how the text semantics vary over space and time. To represent the semantics, we apply probabilistic topic modeling. After extracting a set of topics and representing the texts by vectors of topic weights, we aggrega...
Article
Full-text available
Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to acti...
Conference Paper
Full-text available
The emergence of Web 2.0 and ubiquitous mobile platforms makes it possible to collect a vast amount of information contributed by people (VGI). For example, crowd-sourcing applications collect information from domains such as biodiversity, urban planning, and risk management, and other sources such as social media connect citizens that exchange vol...
Article
In movement data analysis, there exists a problem of comparing multiple trajectories of moving objects to common or distinct reference trajectories. We introduce a general conceptual framework for comparative analysis of trajectories and an analytical procedure, which consists of (1) finding corresponding points in pairs of trajectories, (2) comput...
Article
Action sequences, where atomic user actions are represented in a labelled, timestamped form, are becoming a fundamental data asset in the inspection and monitoring of user behaviour in digital systems. Although the analysis of such sequences is highly critical to the investigation of activities in cyber security applications, existing solutions fai...
Article
Spatial time series is a common type of data dealt with in many domains, such as economic statistics and environmental science. There have been many studies focusing on finding and analyzing various kinds of events in time series; the term ‘event’ refers to significant changes or occurrences of particular patterns formed by consecutive attribute va...
Article
Full-text available
Transportation agencies have an opportunity to leverage increasingly-available trajectory datasets to improve their analyses and decision-making processes. However, this data is typically purchased from vendors, which means agencies must understand its potential benefits beforehand in order to properly assess its value relative to the cost of acqui...
Conference Paper
We propose an approach to interactive visual exploration of trajectories of moving objects in which trajectories are mapped onto different coordinate systems enabling the analyst to look at different aspects of the movement. Geographic visualization techniques can be applied to these coordinate systems in the same way as in usual geographic map dis...
Conference Paper
From¹ a set of trajectories of the players and the ball in a football (soccer) game, we computationally estimate, for each time frame, the pressure of the defending players upon the ball and the opponents. The extracted pressure relationships are visualized in detailed and summarized forms. Interactive filtering enables exploration of the pressure...
Article
To complement the currently existing definitions and conceptual fram