Fix #3 (wörk)

ThesTeX/content/2-state-of-the-art.tex

@@ -1,2 +1,2 @@
-\input{content/2.0-collection}
+%\input{content/2.0-collection}
 \input{content/2.1-text}

ThesTeX/content/2.1-text.tex

@@ -1,6 +1,9 @@
-\section{State of research}
+With an administrative background, the first approach to log processing which comes to mind are the various log processing frameworks.
+\autoref{sec:logproctheo} shows the current state of tools and processes for managing large volumes of log and time series data.
+An overview of the field of pedestrian track analysis is located in \autoref{sec:pedest}.
+Finally, in \autoref{sec:gametheo} the connection of spatial anaylses and digital game optimizations is showcased.
 
-\section{Log processing}
+\section{Log processing}\label{sec:logproctheo}
 System administrators and developers face a daily surge of log files from applications, systems, and servers.
 For knowledge extraction, a wide range of tools is in constant development for such environments.
 Currently, an architectural approach with three main components is most frequently applied.
@@ -51,7 +54,7 @@ Additional functionality can be added with plugins, e.g. for new data sources or
 The query languages of the data sources is abstracted by an common user interface.
 
 
-\section{Pedestrian traces}
+\section{Pedestrian traces}\label{sec:pedest}
 Analyzing pedestrian movement based on GPS logs is an established technique.
 In the following sections, \autoref{sssec:gps} provides an overview of GPS as data basis, \autoref{sssec:act} highlights some approaches to activity mining and \autoref{sssec:vis} showcases popular visualizations of tempo-spatial data.
 \nomenclature{\m{G}lobal \m{P}ositioning \m{S}ystem}{GPS}
@@ -75,37 +78,73 @@ Informations of this kind are relevant e.g. for improvements for tourist managem
 
 Beside points of interest (POIs), individual behaviour patterns can be mined from tracks, as described in \cite{ren2015mining}.
 Post-processing of these patterns with machine learning enables predictions of future trajectories \cite{10.1007/978-3-642-23199-5_37}.
-
+%TODO more??
 
 \subsection{Visualization}\label{sssec:vis}
+Visualizations help to understand data sets, especially for spatial data.
 
-\image{.81\textwidth}{../../PresTeX/images/strava}{Heatmap: Fitnesstracker\cite{strava}}{img:strava}
+\subsubsection{Heatmap}
+One of the most basic visualization of large amounts of spatial data is the heatmap.
+As the example in \autoref{img:strava} shows, it allows to identify areas with high densities of data points very quickly.
+This comes however with the loss of nearly all context information.
+For example, the temporal information - both the time slice and the relative order of the data points - is completely absent.
+A workaround is an external control element for such information to control the unerlying dataset.
 
-\image{.72\textwidth}{../../PresTeX/images/space-time}{Space-time cube examples\cite{bach2014review}}{img:spacetime}
+\image{\textwidth}{../../PresTeX/images/strava}{Heatmap: Fitnesstracker \cite{strava}}{img:strava}
 
-\image{\textwidth}{../../PresTeX/images/traj-pattern}{Flock and meet trajectory pattern\cite{jeung2011trajectory}}{img:traj-pattern}
+\subsubsection{Track attributes}
+An example of a rendering methodology including more attributes, \cite{stopher2002gps} details the possibilities using cartographic signatures as seen in \autoref{img:track-attr}.
+When track lines are used, there are some options to indicate attributes of the track, too.
+Besides the color, e.g. the width and stroke-type of the line can indicate certain attributes.
+A combination of these allows the visualization of multiple attributes at once.
+However, such views are limited in the amount of tracks and attributes to display before been confusing and ambiguous.
+
+\image{\textwidth}{track-attributes}{Track rendering with acceleration attributes \cite{stopher2002gps}}{img:track-attr}
+
+
+\subsubsection{Space-time cube}
+One way to address the lack of temporal context is the space-time cube concept reviewed in \cite{kraak2003space}.
+By mapping an additional temporal axis as third dimension on a two-dimensional map, tracks can be rendered in a three-dimensional context.
+The example in \autoref{img:spacetime} shows how such a rendering allows to identify individual movement patterns and locations of activity in between.
+However, it also demonstrates the problems of the difficult interpretation of the 3D map, especially with overlappig tracks.
+Beside from overcrouded ares, many people have difficulties of miss-interpreting the 3D movements.
+The space flattened alternative on the right tries to reduce this problem with a spatial abstraction.
+
+\image{\textwidth}{../../PresTeX/images/space-time}{Space-time cube examples \cite{bach2014review}}{img:spacetime}
+
+An approach for an time-aware heatmap utilizing space-time cubes is shown in \autoref{img:spacetime2}.
+This highlights hotspots of activity over an temporal axis.
+\image{\textwidth}{space-time-density}{Space-time cube density examples \cite{demvsar2015analysis}}{img:spacetime2}
+
+\subsubsection{Trajectory patterns and generalizations}
+To simplify the visualization of large amounts of indiviual tracks, the derivation of patterns applying to the tracks allows to highlight key areas.
+\autoref{img:traj-pattern} shows two examples of such patterns: Flock, where a group of tracks are aligned for some time, and meet, which defines an area of shared presence.
+It is possible to apply such pattern time aware or time agnostic, i.e. whether to take the simultaneous appearance into account. \cite{jeung2011trajectory}
+
+\image{\textwidth}{../../PresTeX/images/traj-pattern}{Flock and meet trajectory pattern \cite{jeung2011trajectory}}{img:traj-pattern}
+
+An approach for addressing the generalization aspects necessary to visualize massive movement data is described in \cite{adrienko2011spatial}.
+They work on traffic data as shown in \autoref{img:generalization}.
+With an increasing generalization parameter, the flows refine to more abstract representations of travel.
 
 \image{\textwidth}{../../PresTeX/images/generalization}{Trajectories and generalizations with varying radius parameter \cite{adrienko2011spatial}}{img:generalization}
 
 
-\section{Analyzing games}
+\section{Analyzing games}\label{sec:gametheo}
-\begin{itemize}
+Modern video games with always-on copyprotection or online masterservers allow game studios to collect metrics about players' performances.
-	\item there's more than heatmaps
+In \cite{Drachen2013}, the authors describe the use of GIS technologies for such environments.
-	\item combine position with game actions
+For example, \autoref{img:chatlogs} shows a correlation between the frequency of certain keywords in the chat messages and the players' current location.
-	\item identify patterns, balancing issues
+This indicates a possible bug in the game to look out for.
-	\item manual processes %\citetitle{Drachen2013}\citetitle{AHLQVIST20181}
-\end{itemize}
-%\image{.5\textwidth}{game-an}{chat logs with players location \cite{Drachen2013}}{img:chatlogs}
-%\image{.5\textwidth}{ac3-death}{identify critical sections \cite{Drachen2013}}{img:ac3death}
-\twofigures{0.5}{../../PresTeX/images/game-an}{Chat logs with players location}{img:chatlogs}{../../PresTeX/images/ac3-death}{Identify critical sections}{img:ac3death}{Game analytics \cite{Drachen2013}}{fig:gameanal}
 
+Not only technical problems, design errors or bad balancing can be visualized, too.
+\autoref{img:ac3death} uses a heatmap to highlight areas with high failure rates during playtesting.
+These failure hotspots points can then be addressed for a convienient game flow.
 
+\image{\textwidth}{../../PresTeX/images/game-an}{chat logs with players location \cite{Drachen2013}}{img:chatlogs}
+\image{\textwidth}{../../PresTeX/images/ac3-death}{identify critical sections \cite{Drachen2013}}{img:ac3death}
+%\twofigures{0.5}{../../PresTeX/images/game-an}{Chat logs with players location}{img:chatlogs}{../../PresTeX/images/ac3-death}{Identify critical sections}{img:ac3death}{Game analytics \cite{Drachen2013}}{fig:gameanal}
+
+In contrast to the complete virtual games above, \cite{AHLQVIST20181} describes the mining of spatial behaviour of players through an real-world base online game.
+With an focus on replicating the real world, players have to align social and natural resources.
+The results of these simulations can then be used to built agent-based simulations with realistic behaviour.
 
-\section{Summary}
-\begin{itemize}
-	\item Log processing: Powerful stacks
-	\item Movement analysis: Large field already explored (GPS influence, Patterns, Behavior recognition, …)
-	\item Track rendering: Track (with attributes), Space-time cube, Heatmap, …
-	\item Spatial analysis of digital games with GIS
-	\item Analysis of location based games: Laborious manual process
-\end{itemize}

ThesTeX/content/3-solution.tex

@@ -1,4 +1,4 @@
-With an administrative background, the first approach to log processing which comes to mind are the various log processing frameworks.
+With an administrative background, the first approach to log processing which comes to mind is the various log processing frameworks.
 The following chapter \autoref{sec:logproc} takes a dive into this world and evaluates the feasability of two such system for the scope of this thesis.
 Based on the findings, an alternative approach is then outlined in \autoref{sec:alternative-design}.
 

ThesTeX/content/appendix.tex

@@ -7,19 +7,19 @@
 
 \section{Containers}
 \subsection{Kibana test setup} \label{app:kibana}
-\lstinputlisting[language=yaml,caption={Docker-compose file for Kibana test setup},label=code:kibana]{code/kibana-docker-compose.yml}
+\lstinputlisting[language=yaml,caption={Docker-compose file for Kibana test setup},label=code:kibana,numbers=left]{code/kibana-docker-compose.yml}
 
 \subsection{Biogames server dockerized} \label{app:biogames}
 \image{\textwidth}{biogames.pdf}{Dockerized setup for biogames}{img:bd2gdocker}
-\lstinputlisting[language=yaml,caption={Docker-compose file for Biogames server},label=code:bd2s]{code/biogames/docker-compose.yml}
+\lstinputlisting[language=yaml,caption={Docker-compose file for Biogames server},label=code:bd2s,numbers=left]{code/biogames/docker-compose.yml}
-\lstinputlisting[language=yaml,caption={Dockerfile for Biogames server},label=code:bd2d]{code/biogames/Dockerfile}
+\lstinputlisting[language=yaml,caption={Dockerfile for Biogames server},label=code:bd2d,numbers=left]{code/biogames/Dockerfile}
-\lstinputlisting[language=bash,caption={Entrypoint for Biogames docker container},label=code:bd2e]{code/biogames/start.sh}
+\lstinputlisting[language=bash,caption={Entrypoint for Biogames docker container},label=code:bd2e,numbers=left]{code/biogames/start.sh}
 \subsection{Traefik reverse proxy}\label{app:traefik}
-\lstinputlisting[language=yaml,caption={Docker-compose file for Traefik reverse proxy},label=code:bd2t]{code/traefik.yml}
+\lstinputlisting[language=yaml,caption={Docker-compose file for Traefik reverse proxy},label=code:bd2t,numbers=left]{code/traefik.yml}
-\lstinputlisting[language=yaml,caption={Traefik reverse proxy configuration (traefik.toml)},label=code:bd2toml]{code/traefik.toml}
+\lstinputlisting[language=yaml,caption={Traefik reverse proxy configuration (traefik.toml)},label=code:bd2toml,numbers=left]{code/traefik.toml}
 
 \subsection{Geogame Log Analysis project setup}\label{app:dcs}
-\lstinputlisting[language=yaml,caption={Docker-compose file for Geogame Log Analysis project},label=code:gglap]{code/project.yml}
+\lstinputlisting[language=yaml,caption={Docker-compose file for Geogame Log Analysis project},label=code:gglap,numbers=left]{code/project.yml}
 
 \section{TODO}
 \subsection{Examples} %TODO ?!?!

ThesTeX/content/literature.bib

@@ -540,3 +540,20 @@ isbn="978-3-642-23199-5"
   author={Anselin, Luc},
   year={1989}
 }
+@inproceedings{kraak2003space,
+  title={The space-time cube revisited from a geovisualization perspective},
+  author={Kraak, Menno-Jan},
+  booktitle={Proc. 21st International Cartographic Conference},
+  pages={1988--1996},
+  year={2003}
+}
+@article{demvsar2015analysis,
+  title={Analysis and visualisation of movement: an interdisciplinary review},
+  author={Dem{\v{s}}ar, Ur{\v{s}}ka and Buchin, Kevin and Cagnacci, Francesca and Safi, Kamran and Speckmann, Bettina and Van de Weghe, Nico and Weiskopf, Daniel and Weibel, Robert},
+  journal={Movement ecology},
+  volume={3},
+  number={1},
+  pages={5},
+  year={2015},
+  publisher={BioMed Central}
+}