ViewConflicts: Software for Visualising Spatiotemporal Data on Armed Conflicts Jan Ketil Rød Division of Geomatics Norwegian University of Science and Technology (NTNU).
[email protected] Paper prepared for presentation at the workshop on Geography, Conflict and Cooperation ECPR Joint Session, Edinburgh, UK 28 March – 2 April 2003.
Abstract ViewConflicts is a software system designed to support visual exploration of a dataset on armed conflicts. This is a spatiotemporal dataset since each conflict is represented with a coordinate, a radius for its extension as well as “begin” and “end” year for when the conflict was active. Two basic exploration methods are available in ViewConflicts: multiple linked windows (brushing) and animation. Ongoing work tries to incorporate visualisation of other datasets recognised as affecting the risk, duration, type and location of armed conflicts. Datasets on armed conflicts as well as datasets on conflict generating factors have both a temporal and spatial dimension, consequently, it is important that the visualisation tool takes into account both time and space components. Keywords Geographic visualisation, spatiotemporal data, linked windows, brushing, animation
CARTOGRAPHIC VISUALISATION OF ARMED CONFLICTS During the last decade, increasing portions of scientific visualisation tool developments have been directed toward use of dynamic computer environment to facilitate processes of change through time (e.g., Slocum et al., 2000). An obvious reason for doing so is that most phenomena have both spatial and temporal components. Consequently, as MacEachren puts it, ‘if a problem has both spatial and temporal components, visualization tools that do not take both into account have the potential to do more harm than good’ (MacEachren, 1995: 422). MacEachren (1995) used the term geographic visualisation or geovisualisation to describe the act of exploring a dataset by visual means, which can then lead to formulation of research 1
questions or hypotheses. Maps and other visual representations are used in a private domain by a researcher in order to come up with new or improved understanding on a certain phenomena. The main issue for developments of scientific visualisation tools is how to transform large spatio-temporal data volumes into information and ultimately into knowledge. ‘To play this role effectively, the map needs two principal additions: interaction and dynamics’ (Andrienko and Andrienko, 1999: 357). Generally, it is acknowledged that if geographic visualization tools is to succeed, that is being useful in revealing unknowns, ‘interaction is paramount; the system should permit the user to do a wide variety of things to the data’ (MacEachren and Ganter, 1990: 74). Interactive visualisation is understood as a flexibility allowing the users to visualise their data in a numerous of ways. Efforts toward developing interactive visualisation tools started within the realm of statistical graphing where a technique called ‘scatterplot brushing’ was initially designed for comparing multiple potentially interrelated variables on a set of linked scatterplots (Becker and Cleveland, 1987). Monmonier (1989) extended the brushing technique to spatial data by linking the window showing scatterplots with a window showing a map. With this implementation of brushing, when an investigator selects points in a scatterplot, not only are points on other scatterplots highlighted, but their map locations as well. Scatterplot is only one of several diagrams that might be used in order to portray multivariate phenomena. As an alternative to the term scatterplot brushing, several authors (e.g. Kraak, 2001:14) use the term attribute brushing which includes other types of diagrams portraying both univariate and multivariate phenomena. This brushing technique is later on also called multiple dynamically linked windows. ‘These views do not necessarily contain maps: video, sound, text, etc. can all be included. Clicking an object in a particular view will show its spatial relationships to other objects or representations in all the other views’ (Kraak and Ormeling, 2003: 178) Within conflict research visualisation by the use of maps has generally been restricted to static maps that portray particular situations, regions or arenas of warfare, but maps have also been used to present results of an exploratory data analysis related to the role democratisation play as a conflict-generating factor (e.g. Gleditsch and Ward, 2000). Time series maps (O´Loughlin, 1998 et al.) and animation (www.colorado.edu/ IBS/GAD/spacetime.html) have been used in a project sponsored by the National Science Foundation (NSF) on the spatial and temporal diffusion of democracy from 1946 to 1994. During the last years, GIS has been used
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as a tool for generating new datasets essential for conflict research, for instance borders in international relations (Starr, 2002). Attempts to use GIS more extensively as a methodology in peace and conflict research have been made by Braithwaite (2001) regarding militarised interstate disputes, and by Buhaug and Gates (2002) regarding armed civil conflicts. The work presented here build on the efforts within interactive visualisation techniques applied for spatiotemporal datasets on armed conflicts and conflict generating factors. The aim is to provide conflict researchers and others, a better tool for investigating the origin and dynamics of armed conflicts. The main objective is to develop a scientific visualisation tool facilitating a better understanding of the origins and dynamics of armed conflicts. In order to solve existing or prevent future conflicts, it is essential to have knowledge of the causes and dynamics of conflicts. Although each conflict has its own dynamics and each region its own history, there are several general factors that may influence whether or not conflicts evolve. The visualisation tool aims to trigger a better understanding on questions like: -
Why do outbreaks of conflicts occur in certain locations?
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Why do some conflicts have a long duration while others are transitory?
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Why do conflicts spread?
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Why do some conflicts extend to huge areas while others have limited extension?
Figure 1. The ViewConflicts environment consists of six components: Menu bar, tool bar, map display, legend, status bar and time brush. Six themes are loaded, but only one is shown.
This work on interactive visualisation of armed conflicts has so far resulted in the software package developed at NTNU called ViewConflicts currently available at version 1.0. ViewConflicts is a software package that visualises the content of a spatiotemporal dataset on armed conflicts collected by various conflict researchers (Gleditsch et al. 2002). A screen 3
dump from this program showing all conflicts in the after cold war period are shown in Figure 1. During the last few years the International Peace Research Institute, Oslo (PRIO) has collaborated with the Department of Peace and Conflict Research at Uppsala University and the Department of Sociology and Political Science at the Norwegian University of Science and Technology (NTNU) to establish a database on armed conflicts from 1946 to the present (Gleditsch et al. 2002). The armed conflicts are in this dataset categorised into four types: extra systemic, interstate, internal and internationalised. The database is updated annually in Uppsala. As of September 2002 there were 552 armed conflicts registered in the database for the period 1946–2001. As each conflict is stored with a coordinate value for its centre, a radius value for its extension as well as a starting and an ending point in time, this spatiotemporal dataset can be viewed in a dynamic cartographic visualisation environment. ViewConflicts is developed for this purpose.
VIEWCONFLICTS The programming language Visual Basic from Microsoft is used for developing ViewConflicts, and MapObjects, a so-called OCX or ActiveX, from ESRI is used to ease the handling and display of geographic data (a 90 days evaluation version of MapObjects 2.1 is offered by ESRI at www.esri.com). Visual Basic version 6.0 with service pack 5 and MapObjects Windows Edition version 2.0 were used for implementing ViewConflicts. Using Visual Basic combined with MapObjects does indeed make the development of an interactive user interface easy and the waste number of examples codes available do simplify implementation. This principle of open source is also carried out for ViewConflicts whose source code is freely available for download via www.geomatikk.ntnu.no/konflikt. However, due to distributional restrictions on the MapObjects component, the distributed version is password protected1. The dataset on armed conflicts is populated with a pair of latitude and longitude co-ordinates where each pair represents the centre of the conflict area. In addition to position, Buhaug and Gates (2002) have populated the database with a radius value defining each conflict’s geographical extension. Based on the pair of coordinates representing the conflict’s centre
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Enter user name “ViewConflicts” and password “PeaceNow!” to download the distributed version.
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point and the radius representing the geographical extension, ViewConflicts are used to generate five shape theme layers: one for each of the four types of conflicts (point themes) and one for the conflicts extensions (polygon theme). The geometry of each feature is defined by a set of coordinates. In this context, a coordinate system is used as the frame of reference. There are two types of coordinate systems: geographic coordinate systems (latitudes and longitudes) and projected coordinate systems. Typical GIS operations involving distance or area measures (like buffer and overlay operations) should be performed on projected coordinate systems. The latitudes and longitudes coordinate representing the conflicts points are therefore transformed to coordinates defined by an equal area projection in order to perform buffer and overlay operations.
Buffer Conflict point Conflict extension
Intersect
Clipped conflict extension
Country border Figure 2. From a point feature representing the conflict’s centre to a clipped, circular polygon feature representing the conflict’s extension.
A buffer is a zone of specified distance around features like for instance points representing armed conflicts. Both constant- and variable- width buffers can be generated. The latter was used based on each of the internal and internationalised conflict’s radius value. As internal and internationalised conflicts are defined to occur within the state, the buffer generated polygon is clipped towards the state borders for the country. The intersect command is used for this purpose as it returns a shape that represents the geometric intersection of one shape object (the country polygon) with another shape object (the buffer polygon for the conflict’s extension). An illustration of this process is given in Figure 2 and some resulting circular polygons representing the extension of armed conflicts are shown in Figure 3 and 4.
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Buhaug and Gates (2002) defined the conflict zones as being circular and centred around the conflict centre point; the radius of the conflict zone equals half the distance between the two most separated conflict locations, rounded upwards to the nearest 50-km interval to ensure that all significant battle zones were covered. Conflicts that took place within a single location (city), like for instance the internal conflict in Togo 1991 (see Figure 3), were assigned a 50km radius.
Figure 3. The geographical extension of armed conflicts has a minimum radius of 50 km as for the conflict in Lomé, Togo 1991.
Buhaug and Gates (2002) recognise an essential negative consequence of simplifying the representation of conflict zones by circular shapes. The measured scope inevitably covers some areas not affected by the conflict, thus overestimating the total area of the geographical extension of a civil war − particularly effective for the representation of the geographical extension of the conflict in the Democratic Republic of Congo in 1996 (see Figure 4). The conflict seems to cover most of the country, but the conflict actually took place in some restricted areas in the south, east and northeast part of the country.
Figure 4. Representing armed conflicts with a circular shape have an overestimating effect on the total area being affected by conflict like in the Democratic Republic of Congo in 1996.
All conflict extensions are thus represented as circular, but on-going work will improve the geographic database by replacing the circular extension of conflicts by a collection of polygons covering the areas where the fighting actually took place. This work is especially
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relevant for the investigation of spatiotemporal relationships between conflicts and conflict generating factors (e.g. access to natural resources). ANIMATIONS AND DYNAMICALLY LINKED WINDOWS To develop visualisation tools useful for discovering new knowledge of spatiotemporal phenomena, it is recognised that animation and three sorts of brushing techniques should be included as multiple dynamically linked windows: a geographical brush where the map is the interface, an attribute brush where the diagram or table is the interface, and a temporal brush where the time line is the interface (e.g. www.itc.nl/~carto/division/ kraak/exploratory2.html). Animation Animation should be available in a manner allowing the user to control the speed, to pause or stop it, to play only parts of it, or to play the animation once or several times and in reverse. Several authors have evaluated whether or not non-interactive animations (often called ‘viewonly’ animations) are useful tools for cognition and have concluded negatively (e.g. Morrison et al., 2000). As Blok expresses it, to be able to control an animation is an essential prerequisite for exploratory use (Blok, 2002: 8). Animation is implemented in ViewConflicts according to the directives given by Blok (2002). The animation control from ViewConflicts is shown in Figure 5.
Figure 5. The animation control in two different situations: paused or stopped (left) and running (right). Five commands are available from the top of the control: stepwise backwards, backwards, forwards, pause and stepwise forward. Additionally, one may control the speed of the animation, the time interval and whether or not it should be repeated.
The user may control the animation regarding running and stopping the animation, the speed of the animation, backward running, repeated running, stepwise time shots in both direction and the ability to set the time interval for the animation. In addition, the user may zoom in the map at a particular region before or during animation. It is hoped that such an animation may be useful in separating long during conflict from conflicts of short duration as well as 7
identifying regions where conflicts frequently evolve. A series of map frames from an animation for Central America from 1989 to 2000 is given in Figure 6. The animation between 1989 and 2000 consists of 12 frames, one for each year. When the animation runs, one recognises temporal differences among the conflicts. The conflict in Columbia has a continuously duration, the conflict in Guatemala has a long duration while several other conflicts starts up but ends after a short duration. One also recognises from the animation that the number of conflicts decreases towards the end of the period.
Figure 6. Map frames from an animation for Central America from 1989 to 2000, one for each year.
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Temporal brushing Several researchers in the cartography/GIS community have developed highly interactive systems based on brushing techniques in order to allow for exploration of datasets (MacDougall, 1992; Egbert and Slocum, 1992; Andrienko and Andrienko, 1999). For spatialtemporal data, Monmonier (1990) suggested to add a temporal brush allowing the user to manipulate the data for which graphs and maps are depicted by moving a temporal scroll bar. ‘The viewer uses a mouse to point to the box in the scroll bar, and to change the time displayed on the map by ‘dragging’ this box to the left (to select an earlier time) or to the right (to select a later, more recent time)’ (Monmonier, 1990: 40). Scroll bars can be designed as discrete or continuous. An example of a discrete temporal scroll bar is shown in Figure 7.
Figure 7. A typical design of a discrete temporal scroll bar (temporal brush); for each slider position there is a corresponding map or “snap shot”. One may navigate to the wanted point in time by moving the slider or by pressing the command buttons, which will increment or decline the actual year with one year in the direction indicated.
Discrete temporal scroll bars might address time in years or decades and the maps produced by it are often denoted as ‘snapshots’. A ‘continuous scroll bar might provide a graphic scale and reference time more precisely, for example, in days, hours, minutes, or even seconds’ (Monmonier, 1990: 40).
Visualise snapshots (single year) When starting ViewConflicts, six themes opens: a theme showing the state borders, a theme showing the conflicts extensions and four themes showing the four types of armed conflicts. Initially, the layer showing the conflicts extensions is set to not visible and the symbol sizes for the armed conflicts are set to zero. Thus, all six themes are listed in the legend field, but only the state border theme is shown (see Figure 1). The other themes may be shown if the user click in the little box just left of the theme name in the legend field. As a results those conflicts being active in the year or years defined by the position of the scroll bar is shown in the map. Initially, when ViewConflicts is loaded, the scroll bar is situated to the left at the year 1946. Only those conflicts active in the year 1946 is shown. When the user moves the
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slider, the map updates and shows the conflict situation for the actual year. The user may also click on the command buttons left or right of the slider to, respectively, decline or increment the display with one year. These actions activate a SQL statement making a selection of a record set fulfilling the requirement of showing only those ongoing conflicts at the given year or period of years. For instance, if the slider is situated at the year 1989, the SQL statement resulting in a new record set called “Selection” is: Selection = "(Begin =1989) " All units from the conflict database not part of this selection are still represented with a point symbol of size zero, and thus not visible. However, all units fulfilling the query are represented with a point symbol of a particular size making the symbols visible, like in the map in Figure 8. In Figure 8, as only internal and internationalised conflicts are marked in the legend field – only units from those themes are being queried.
Figure 8. Map showing internal and internationalised conflicts, of all intensity levels, being active in 1989.
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By default, conflicts of all intensity level are shown. If the user wants to show only subset of the database, for instance only those conflicts having intensity level 3,2 he or she may do so by defining the subset to be viewed in one ViewConflict’s dialog boxes. The query perform for this selection will be: Selection = "(Begin =1989) AND Intensity = 3" The result is shown in Figure 9.
Figure 9. Map showing internal and internationalised conflicts, of intensity level 3, being active in 1989.
Visualise range of years If the slider is showing a range of year from 1989 to 2000 and the decision of only showing conflict with intensity level 3, the SQL statement resulting in a new record set called “Selection” is: Selection = "(NOT End < 1989) AND (NOT Begin > 2000) AND Intensity = 3" Again, a drawing command is activated which draw the point symbols representing all units from the selection with a particular size, form and colour. All other conflicts whose record set 2
Intensity level 3 means that at least 1000 persons are killed each year as a result of the conflict.
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do not fulfil this requirement are still shown with size equal zero. The result is shown in Figure 10.
Figure 10. Map showing internal and internationalised conflicts, of all intensity levels, being active in the period 1989 to 2000.
Geographical brush Geographical brushing is a collection of techniques responding to events the user has triggered while interacting with the map display. The traditional zoom, pan and information button are among these. For all themes loaded in the map display of ViewConflicts, you may use the identify button: Click on the button and move the cursor into the map window, situate it on the feature over the map feature you want to identify and click. The features in all visible layers under the pointer will be identified (see Figure 11).
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Figure 11. Eight features are found by clicking on a feature on the map representing a conflict in Columbia. The feature whose attributes are listed is the conflict being active at the selected point in time (left window). From the “drop-down” menu – attributes from other conflicts may be listed (window in middle). One of these eight features is from the layer with the country borders (right window).
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Attribute brushing In geographical information systems, geographical features are usually stored by separating geometry and attributes. The geometric features are point, lines and polygons. Variables that describe the geometric features are stored in tables referred to as attribute table. Attribute brushing is a collection of techniques responding to events the user has triggered while interacting with the attribute table or, most often, diagrams of its content. Attribute brushing is realised in ViewConflicts by linking the map with a table summarising the number of conflict at a certain year or period of years by type (see Figure 12). Map layers shown in the map are
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represented with a yellow row in the table while map layers not shown are represented with a white row. Conflict themes can be turned “on” and “off” by clicking in the row (in addition to clicking in the legend field).
Figure 12. Interstate and internationalised armed conflicts in 2001. The table summarises the number of conflicts and functions as a interface to the map as type of conflicts may be turned on and off.
The number of various conflicts during the period 1946 to 2001 can be visualised in a stacked diagram as done by Gleditsch et al (2002: 624) – see Figure 13. 60
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Internationalized Intrastate Intrastate
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Interstate Extrasystemic
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0 1946 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Figure 13. The four series covers (from above and downwards): internationalised internal, internal, interstate and extrasystemic armed conflicts (from Gleditsch et al. 2002: 624).
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In ViewConflicts, the same diagram is linked with the map and made interactive. Figure 14 (right part) shows a map showing conflicts active in 2001 – in the stacked diagram above, the stacked bars representing 2001 are highlighted with colours set in the lower left corner of the dialog box. By clicking in the diagram, at the position for the highest bar – the year 1992, the bar for this year are coloured, the table shows the number of conflicts active in this year while the map shows were they took place (see Figure 14 left part).
Figure 14. The stacked bar is highlighted for 2001 (right) and 1992 (left). 1992 was the year having the highest number of internal armed conflicts.
The user may select a range of year in the diagram in a similar manner as at the time brush. By indicating two points in time at the diagram, the diagram colours for the range of years selected and the map updates showing the type of conflicts selected (yellow rows) for the time period selected (see Figure 15).
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Figure 15. The stacked bar highlighted for the range of years 1989 – 2001 (above) and the map showing where those conflicts took place.
DATASET ON CONFLICT GENERATING FACTORS Several factors are by peace and conflict researchers identified as conflict generating factors. Among these are: poverty (expressed by GDP per capita) democracy access to valuable and easy-to-sell natural resources (e.g. diamonds) ethnicity violent history nearness to other conflict areas 16
If these factors shall be visualized and / or analyzed with geographical information systems, they need to be represented spatially. For poverty and democracy this may be easily done as this national variables that can be linked to the attribute table for the map on country borders. When this link is done, the country map can be symbolized based on the values in these variables3. In Figure 16 the map is symbolized based on level of GDP per capita4 according to the metaphor the darker green the poorer is the country. As Figure 16 shows, there is a close relationship between poverty and internal conflict and according to Gleditsch (2002) is it among the most robust findings in studies of the outbreak of civil war.
Figure 16. A screen dump showing the internal and the internationalised armed conflicts together with a background choropleth map showing the GDP levels (figures from 1995). The map visualise a correlation between poverty and presence of civil war.
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Unfortunately, linking the state border theme’s attribute table with an external table is not functioning in the distributed version of ViewConflicts. 4 The values are grouped into three near equal classes so that the lightest colour represent the 1/3 richest countries and the darkest colour represent the poorest.
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Natural resources Valuable natural resources are thought to affect the risk, duration, type and location of conflicts (Lujala and Buhaug, 2003). Alluvial diamonds in particular have served to finance civil wars (e.g. Sierra Leone, Angola, Liberia and the Democratic Republic of Congo). In Figure 17 the precious metal found in the digital maps produced by ESRI (1996) are shown together with the armed conflicts active in 2001.
Figure 17. A pattern of natural resources shown together with armed conflicts and their extensions. Does the pattern of natural resources correspond to the locations for the warfare?
Lujala and Buhaug (2003) have recognised that the ESRI dataset does only consider large deposits and, consequently, the geographic location is therefore not as detailed as they require. In order to investigate more generally whether or not there is a spatial relationship between location of natural resources and the extension of the conflicts, a more complete dataset of the former and a more accurate representation of the latter is needed (Lujala and Buhaug, 2003). An additional problem related to the natural resources is of temporal character. The Gilmore and Lujala (2003) dataset will most likely exclude the “end” year from the dataset on natural resources due to its ambiguity; mines close down and open
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continuously depending on marked prices available technology, political stability in the country etc. Concluding remarks Hopefully, ViewConflicts will provide useful addition for researchers and others who want to explore spatiotemporal datasets on armed conflicts, their extensions and possible relations with conflict generating factors. In developing ViewConflicts, I am addressing an objective to support high interaction with the maps and other data displays as well as dynamic visualisation methods in order to explore spatiotemporal datasets on armed conflicts. The work on enhancing dynamics and interactivity goes on, but I hope that the paper has demonstrated the usefulness of such a development.
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