CONFLICT DATABASE COMPASS codebook
DATAWAR, 29/10/2023
Databases are analyzed according to “metadata“: the presence or absence of a variable, its unit, its domain, information about the transparency of the database, its update status and its accessibility.
Metadata is divided into 8 groups:
I/ Conflict variable; II/ Time variable; III/ Space variable; IV/ Data structure; V/ All variables; VI/ Transparency; VII/ Update; VIII/ Access.
For each metadata, the choice is justified by a quotation from the codebook, a screenshot from the website, or an extract from the database. Feel free to criticize the results via the “Contact us” page.
I/ Conflict variable
I/1/ Unit of conflict
| Event (< 0 or 1 death) | Conflict (< 25 deaths) | War (< 100 deaths) | Episode (< 500 deaths) |
Event (< 0 or 1 death)
“The basic unit of analysis for the UCDP GED dataset is the “event”, i.e. an individual incident (phenomenon) of lethal violence occurring at a given time and place.
UCDP define an event as: An incident where armed force was used by an organised actor against another organized actor, or against civilians, resulting in at least 1 direct death at a specific location and a specific date” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 4)
UCDP define an event as: An incident where armed force was used by an organised actor against another organized actor, or against civilians, resulting in at least 1 direct death at a specific location and a specific date” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 4)
Conflict (< 25 deaths)
“The main unit in this dataset is a “State-based Armed Conflict” as defined by UCDP. […]
UCDP defines state-based armed conflict as: ‘a contested incompatibility that concerns government and/or territory where the use of armed force between two parties, of which at least one is the government of a state, results in at least 25 battle-related deaths in a calendar year.'” ([UCDP/PRIO] Armed Conflict Dataset (v. 22.1), codebook, p. 4)
UCDP defines state-based armed conflict as: ‘a contested incompatibility that concerns government and/or territory where the use of armed force between two parties, of which at least one is the government of a state, results in at least 25 battle-related deaths in a calendar year.'” ([UCDP/PRIO] Armed Conflict Dataset (v. 22.1), codebook, p. 4)
War (< 100 deaths)
“For a dyadic war to be present both states must meet one or both of the following conditions:
(1) the state must suffer 100 or more battle-related deaths in the battles with the other state, or
(2) the state must deploy 1,000 or more troops in battles against the other state.” ([COW] Dyadic Inter-State War Dataset (v. 3.0), codebook, p. 1)
(1) the state must suffer 100 or more battle-related deaths in the battles with the other state, or
(2) the state must deploy 1,000 or more troops in battles against the other state.” ([COW] Dyadic Inter-State War Dataset (v. 3.0), codebook, p. 1)
Episode (< 500 deaths)
“Major episodes of political violence are defined by the systematic and sustained use of lethal violence by organized groups that result in at least 500 directly-related deaths over the course of the episode.” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2012) (Full Set), codebook, p. 2)
I/2/ Conflict domain
| State-based conflict | Non-state conflict | One-sided violence | TO BE DETERMINED |
State-based conflict
“The Correlates of War (COW) Project has utilized a classification of wars that is based upon the status of territorial entities, in particular focusing on those that are classified as members of the inter-state system (referred to as “states”). Wars have been categorized by whether they primarily take place between/among states, between/among a state(s) and a non-state entity, and within states. This dataset encompasses wars in the first category (WarType #1)– wars that take place between or among states (members of the interstate system).” ([COW] Inter-State War Data (v. 4.0), codebook, p. 1)
Non-state conflict
“A non-state conflict is defined by the Uppsala Conflict Data Program (UCDP) as ‘the use of armed force between two organized armed groups, neither of which is the government of a state, which results in at least 25 battle-related deaths in a year.'” ([UCDP] Non-State Conflict Dataset (v. 22.1), codebook, p. 4)
One-sided violence
“One-sided violence is the use of armed force by the government of a state or by a formally organized group against civilians which results in at least 25 deaths.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 3)
II/ Time variable
II/1/ Unit of time
| Day | Year |
II/2/ Time domain
??
III/ Space variable
III/1/ Unit of space
| Coordinates | Country | Region | TO BE DETERMINED |
Coordinates
“Data in the UCDP GED is geo-referenced, meaning that each event is connected to a specific location defined by a pair of latitude and longitude coordinates.” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 19)
Country
“location
The countries where this episode of violence took place.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 6)
The countries where this episode of violence took place.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 6)
Region
“WhereFought – Region where combat occurred. Values are:
1 = W. Hemisphere
2 = Europe
4 = Africa
6 = Middle East
7 = Asia
9 = Oceania” ([COW] Non-State War Data (v. 4.0), codebook, p. 2)
1 = W. Hemisphere
2 = Europe
4 = Africa
6 = Middle East
7 = Asia
9 = Oceania” ([COW] Non-State War Data (v. 4.0), codebook, p. 2)
III/2/ Space domain
| Global | Mediterranean Sea and Sahel | TO BE DETERMINED |
Global
“GED 22.1 is a global dataset that covers the world between 1989-01-01 and 2021-12-31.” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 1)
Mediterranean Sea and Sahel
“Coding of data on cooperative and conflictive water-related events for all riparian countries of the Mediterranean Sea as well as all countries in the Sahel for the time-period 1997–2009″ ([PRIO] Water-Related Intrastate Conflict and Cooperation (WARICC) (v. 1.0), codebook, p. 1)
IV/ Data structure
| Variable 1 | Variable 2 | Etc. | |
| Observation 1 | Etc. | ||
| Observation 2 | |||
| Etc. |
IV/1/ Unit of observation
| Unit of conflict (UC) | UC-year | UC-actor | Country-year |
| Actor-year | Dyad-year | OTHER | TO BE DETERMINED |
Unit of conflict (UC)
“For each conflict, the dataset provides specific conflict information.” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
([HIIK] Conflict Barometer (v. 2021), HIIK_conflicts_2021.xlsx, 15/03/2022)
UC-year
“2. a conflict version, where each individual conflict has its individual entry.
Thus, each entry contains one side A (the contested party) and one or more contesters in a given year (each entry being one contested incompatibility).” ([UCDP] Battle-Related Deaths Dataset (Conflict version) (v. 22.1), codebook, p. 3)
Thus, each entry contains one side A (the contested party) and one or more contesters in a given year (each entry being one contested incompatibility).” ([UCDP] Battle-Related Deaths Dataset (Conflict version) (v. 22.1), codebook, p. 3)
([UCDP] Battle-Related Deaths Dataset (Conflict version) (v. 22.1), ucdp-brd-conf-221.xlsx, 18/05/2022)
UC-actor
“Overall, there is one initial record for a war, and war participants are listed as having fought on Side A or Side B of the war. Additional records are added for wars in which it was possible to identify more than one participant on a side.” ([COW] Intra-State War Data (v. 4.1), codebook, p. 6)
([COW] Intra-State War Data (v. 4.1), Intra-StateWarData_v4.1.csv, 19/08/2022)
Country-year
“The episode’s ‘magnitude of impact’ score is entered for each year of the designated time span and for each country considered to have been directly affected by the warfare experience. […]
The global system comprises a basically unchanging configuration of territorial units, termed countries or states (i.e., the state system).” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 2-3)
The global system comprises a basically unchanging configuration of territorial units, termed countries or states (i.e., the state system).” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 2-3)
([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), MEPVv2018.xls, 23/08/2022)
Actor-year
“This dataset is the result of an automatic filtering and aggregation of the UCDP Georeferenced Event Dataset from incident/event level to the actor-year level.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 8)
([UCDP] One-sided Violence Dataset (v. 22.1), ucdp-onesided-221.xlsx, 18/05/2022)
Dyad-year
“1. a dyadic version, where each individual conflict dyad (pair of two fighting actors) has its own individual entry in each year the conflict dyad was active;
Thus, each entry contains a single pair of opposing sides (one side A and one side B) in a given year.
Multiple dyads may form a single conflict, as a conflict is defined by its incompatibilities.” ([UCDP] Battle-Related Deaths Dataset (Dyadic version) (v. 22.1), codebook, p. 3)
Thus, each entry contains a single pair of opposing sides (one side A and one side B) in a given year.
Multiple dyads may form a single conflict, as a conflict is defined by its incompatibilities.” ([UCDP] Battle-Related Deaths Dataset (Dyadic version) (v. 22.1), codebook, p. 3)
([UCDP] Battle-Related Deaths Dataset (Dyadic version) (v. 22.1), ucdp-brd-dyadic-221.xlsx, 18/05/2022)
OTHER
“In general, there is one record for each state war participant, unless the state changed sides during the war, in which case there are two records.” ([COW] Inter-State War Data (v. 4.0), codebook, p. 3)
([COW] Inter-State War Data (v. 4.0), Inter-StateWarData_v4.0.csv, 20/08/2022)
IV/2/ Number of observations
??
V/ All variables
| Conflict name | Conflict type | Intensity |
| Outcome | Time | Space |
| Actor | Type of actor | Dyad |
| Coalition | Deaths | Non-conflit variables |
For your information, a database variable – can correspond to several of the variables listed below. For example: the variables “INTVIOL”, “INTWAR” etc. in [CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set) – correspond to both the “Conflict type” and “Intensity” variables.
Conflict name
Cf. I/1/ Unit of conflict.
“conflict_new_id
A unique conflict identification code for each individual conflict in the dataset.
conflict_name
Name of the UCDP conflict to which the event belongs. For non-state conflicts and one-sided violence this is the same as the dyad name.” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 6)
“conflict_new_id
A unique conflict identification code for each individual conflict in the dataset.
conflict_name
Name of the UCDP conflict to which the event belongs. For non-state conflicts and one-sided violence this is the same as the dyad name.” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 6)
Conflict type
Cf. I/2/ Conflict domain.
“conflict type
conflict type (inter-, sub-, intra-, transstate)” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
“INTVIOL (2-numeric)
Magnitude score of episode(s) of international violence involving that state in that year involving that state in that year
Scale: 1 (lowest) to 10 (highest) for each MEPV; Magnitude scores for multiple MEPV are summed;
0 denotes no episodes
INTWAR (2-numeric)
Magnitude score of episode(s) of international warfare involving that state in that year […]
CIVVIOL (2-numeric)
Magnitude score of episode(s) of civil violence involving that state in that year […]
CIVWAR (2-numeric)
Magnitude score of episode(s) of civil warfare involving that state in that year […]
ETHVIOL (2-numeric)
Magnitude score of episode(s) of ethnic violence involving that state in that year […]
ETHWAR (2-numeric)
Magnitude score of episode(s) of ethnic warfare involving that state in that year […]
INTTOT (2-numeric)
Total summed magnitudes of all interstate MEPV
INTTOT = INTVIOL + INTWAR
CIVTOT (2-numeric)
Total summed magnitudes of all societal MEPV
CIVTOT = CIVVIOL + CIVWAR + ETHVIOL + ETHWAR
ACTOTAL (2-numeric)
Total summed magnitudes of all (societal and interstate) MEPV
ACTOTAL = INTTOT + CIVTOT” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 3-4)
“conflict type
conflict type (inter-, sub-, intra-, transstate)” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
“INTVIOL (2-numeric)
Magnitude score of episode(s) of international violence involving that state in that year involving that state in that year
Scale: 1 (lowest) to 10 (highest) for each MEPV; Magnitude scores for multiple MEPV are summed;
0 denotes no episodes
INTWAR (2-numeric)
Magnitude score of episode(s) of international warfare involving that state in that year […]
CIVVIOL (2-numeric)
Magnitude score of episode(s) of civil violence involving that state in that year […]
CIVWAR (2-numeric)
Magnitude score of episode(s) of civil warfare involving that state in that year […]
ETHVIOL (2-numeric)
Magnitude score of episode(s) of ethnic violence involving that state in that year […]
ETHWAR (2-numeric)
Magnitude score of episode(s) of ethnic warfare involving that state in that year […]
INTTOT (2-numeric)
Total summed magnitudes of all interstate MEPV
INTTOT = INTVIOL + INTWAR
CIVTOT (2-numeric)
Total summed magnitudes of all societal MEPV
CIVTOT = CIVVIOL + CIVWAR + ETHVIOL + ETHWAR
ACTOTAL (2-numeric)
Total summed magnitudes of all (societal and interstate) MEPV
ACTOTAL = INTTOT + CIVTOT” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 3-4)
Intensity
“ntensity_level
The intensity level in the conflict per calendar year. The intensity variable is coded in two categories:
1= Minor: between 25 and 999 battle-related deaths in a given year. 2= War: at least 1,000 battle-related deaths in a given year.” ([UCDP/PRIO] Armed Conflict Dataset (v. 22.1), codebook, p. 8)
“INTVIOL (2-numeric)
Magnitude score of episode(s) of international violence involving that state in that year
involving that state in that year
Scale: 1 (lowest) to 10 (highest) for each MEPV; Magnitude scores for multiple MEPV are summed;
0 denotes no episodes
INTWAR (2-numeric)
Magnitude score of episode(s) of international warfare involving that state in that year […]
CIVVIOL (2-numeric)
Magnitude score of episode(s) of civil violence involving that state in that year […]
CIVWAR (2-numeric)
Magnitude score of episode(s) of civil warfare involving that state in that year […]
ETHVIOL (2-numeric)
Magnitude score of episode(s) of ethnic violence involving that state in that year […]
ETHWAR (2-numeric)
Magnitude score of episode(s) of ethnic warfare involving that state in that year […]
INTTOT (2-numeric)
Total summed magnitudes of all interstate MEPV
INTTOT = INTVIOL + INTWAR
CIVTOT (2-numeric)
Total summed magnitudes of all societal MEPV
CIVTOT = CIVVIOL + CIVWAR + ETHVIOL + ETHWAR
ACTOTAL (2-numeric)
Total summed magnitudes of all (societal and interstate) MEPV
ACTOTAL = INTTOT + CIVTOT” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 3-4)
The intensity level in the conflict per calendar year. The intensity variable is coded in two categories:
1= Minor: between 25 and 999 battle-related deaths in a given year. 2= War: at least 1,000 battle-related deaths in a given year.” ([UCDP/PRIO] Armed Conflict Dataset (v. 22.1), codebook, p. 8)
“INTVIOL (2-numeric)
Magnitude score of episode(s) of international violence involving that state in that year
involving that state in that year
Scale: 1 (lowest) to 10 (highest) for each MEPV; Magnitude scores for multiple MEPV are summed;
0 denotes no episodes
INTWAR (2-numeric)
Magnitude score of episode(s) of international warfare involving that state in that year […]
CIVVIOL (2-numeric)
Magnitude score of episode(s) of civil violence involving that state in that year […]
CIVWAR (2-numeric)
Magnitude score of episode(s) of civil warfare involving that state in that year […]
ETHVIOL (2-numeric)
Magnitude score of episode(s) of ethnic violence involving that state in that year […]
ETHWAR (2-numeric)
Magnitude score of episode(s) of ethnic warfare involving that state in that year […]
INTTOT (2-numeric)
Total summed magnitudes of all interstate MEPV
INTTOT = INTVIOL + INTWAR
CIVTOT (2-numeric)
Total summed magnitudes of all societal MEPV
CIVTOT = CIVVIOL + CIVWAR + ETHVIOL + ETHWAR
ACTOTAL (2-numeric)
Total summed magnitudes of all (societal and interstate) MEPV
ACTOTAL = INTTOT + CIVTOT” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2018) (not Full Set), codebook, pp. 3-4)
Outcome
“Outcome: coded as:
1 – Side A wins
2 – Side B wins
3 – Compromise
4 – The war was transformed into another type of war
5 – The war is ongoing as of 12/31/2007
6 – Stalemate
7 – Conflict continues at below war level” ([COW] Intra-State War Data (v. 4.1), codebook, p. 3)
“status
conflict status (active, inactive, closed)” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
1 – Side A wins
2 – Side B wins
3 – Compromise
4 – The war was transformed into another type of war
5 – The war is ongoing as of 12/31/2007
6 – Stalemate
7 – Conflict continues at below war level” ([COW] Intra-State War Data (v. 4.1), codebook, p. 3)
“status
conflict status (active, inactive, closed)” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
Time
Cf. II/1/ Unit of time.
“StartMonth1 – the month in which sustained combat began: -9 = month unknown
StartDay1 – the day on which sustained combat began: -9 = day unknown
StartYear1 – the year in which sustained combat began: -9 = year is unknown
EndMonth1 – the month in which sustained combat ended, or the month of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = month unknown
EndDay1- the day on which sustained combat ended, or the day after the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = day unknown
EndYear1 – the year in which sustained combat ended, or the year of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = year unknown
StartMonth2 – after a break in the fighting, the month in which sustained combat resumes: -9 = month unknown, -8 = not applicable
StartDay2- after a break in the fighting, the day on which sustained combat resumes: -9 = month unknown, -8 = not applicable
StartYear2 – after a break in the fighting, the year in which sustained combat resumes: -9 = year unknown, -8 = not applicable
EndMonth2 – after fighting resumes, the month in which sustained combat ended, or the month of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = month unknown, -8 = not applicable
EndDay2- after fighting resumes, the day on which sustained combat ended, or the day after the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = day unknown, -8 = not applicable
EndYear2 – after fighting resumes, the year in which sustained combat ended, or the year of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = year unknown, -8 = not applicable” ([COW] Inter-State War Data (v. 4.0), codebook, pp. 3-4)
“StartMonth1 – the month in which sustained combat began: -9 = month unknown
StartDay1 – the day on which sustained combat began: -9 = day unknown
StartYear1 – the year in which sustained combat began: -9 = year is unknown
EndMonth1 – the month in which sustained combat ended, or the month of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = month unknown
EndDay1- the day on which sustained combat ended, or the day after the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = day unknown
EndYear1 – the year in which sustained combat ended, or the year of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = year unknown
StartMonth2 – after a break in the fighting, the month in which sustained combat resumes: -9 = month unknown, -8 = not applicable
StartDay2- after a break in the fighting, the day on which sustained combat resumes: -9 = month unknown, -8 = not applicable
StartYear2 – after a break in the fighting, the year in which sustained combat resumes: -9 = year unknown, -8 = not applicable
EndMonth2 – after fighting resumes, the month in which sustained combat ended, or the month of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = month unknown, -8 = not applicable
EndDay2- after fighting resumes, the day on which sustained combat ended, or the day after the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = day unknown, -8 = not applicable
EndYear2 – after fighting resumes, the year in which sustained combat ended, or the year of the last major engagement after which fatalities declined below the war fatality threshold: -7 = war ongoing as if 12/31/2007, -9 = year unknown, -8 = not applicable” ([COW] Inter-State War Data (v. 4.0), codebook, pp. 3-4)
Space
Cf. III/1/ Unit of space.
“where_coordinates
Name of the location to which the event is assigned. Fully standardized and normalized. […]
where_decription
Comment on the location coded, sometimes left empty can include area of the capital or name of a village that has not been found […]
adm_1
Name of the first order (largest) administrative division where the event took place […]
adm_2
Name of the second order administrative division where the event took place […]
latitude
Latitude (in decimal degrees)
longitude
Longitude (in decimal degrees)
geom_wkt
An Open Geospatial Consortium textual representation of the location of each individual point. Formatted as OGC WKT (well known text) without SRID. […]
priogrid_gid
The PRIO-grid cell id (gid) in which the event took place. Compatibility with PRIO-grid (Tollefsen, 2012) is guaranteed for both PRIO-grid 1 and 2. […]
country
Name of the country in which the event takes place.
country_id
Gleditsch and Ward number of the country in which the event takes place. integer region Region where the event took place. One of following: {Africa, Americas, Asia, Europe, Middle East}” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, pp. 9-10)
“where_coordinates
Name of the location to which the event is assigned. Fully standardized and normalized. […]
where_decription
Comment on the location coded, sometimes left empty can include area of the capital or name of a village that has not been found […]
adm_1
Name of the first order (largest) administrative division where the event took place […]
adm_2
Name of the second order administrative division where the event took place […]
latitude
Latitude (in decimal degrees)
longitude
Longitude (in decimal degrees)
geom_wkt
An Open Geospatial Consortium textual representation of the location of each individual point. Formatted as OGC WKT (well known text) without SRID. […]
priogrid_gid
The PRIO-grid cell id (gid) in which the event took place. Compatibility with PRIO-grid (Tollefsen, 2012) is guaranteed for both PRIO-grid 1 and 2. […]
country
Name of the country in which the event takes place.
country_id
Gleditsch and Ward number of the country in which the event takes place. integer region Region where the event took place. One of following: {Africa, Americas, Asia, Europe, Middle East}” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, pp. 9-10)
Actor
“ACTOR1
The named actor involved in the event” ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 5)
“Government side in conflict episode (sidea)
Reports the government side of the conflict episode (SideA in UCDP/PRIO ACD). Opposition side in conflict episode (sideb) Reports the opposition side of the conflict episode (SideB in UCDP/PRIO ACD).” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 5)
The named actor involved in the event” ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 5)
“Government side in conflict episode (sidea)
Reports the government side of the conflict episode (SideA in UCDP/PRIO ACD). Opposition side in conflict episode (sideb) Reports the opposition side of the conflict episode (SideB in UCDP/PRIO ACD).” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 5)
Type of actor
“INTER1
A numeric code indicating the type of ACTOR1″ ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 5)
“Warolea
Role of state A in war
1 = primary initiator
2 = joiner on initiator’s side
3 = primary target
4 = joiner on target’s side” ([COW] Dyadic Inter-State War Dataset (v. 3.0), codebook, p. 2)
“is_government_actor
For some purposes, it may be necessary to disaggregate between government and non-governmental actors in the dataset. This variable records if the actor is the government of a state and is coded as 1 for government actors and 0 for non-governmental actors.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 6)
A numeric code indicating the type of ACTOR1″ ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 5)
“Warolea
Role of state A in war
1 = primary initiator
2 = joiner on initiator’s side
3 = primary target
4 = joiner on target’s side” ([COW] Dyadic Inter-State War Dataset (v. 3.0), codebook, p. 2)
“is_government_actor
For some purposes, it may be necessary to disaggregate between government and non-governmental actors in the dataset. This variable records if the actor is the government of a state and is coded as 1 for government actors and 0 for non-governmental actors.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 6)
Dyad
“dyad_name
Name of the conflict dyad creating the event. A dyad is the pair of two actors engaged in violence (in the case of one-sided violence, the perpetrator of violence and civilians). The two sides are separated by an ASCII dash (e.g. Government of Russia – Caucasus Emirate, Taleban – civilians).” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 7)
Name of the conflict dyad creating the event. A dyad is the pair of two actors engaged in violence (in the case of one-sided violence, the perpetrator of violence and civilians). The two sides are separated by an ASCII dash (e.g. Government of Russia – Caucasus Emirate, Taleban – civilians).” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 7)
Coalition
“coalition_components
If multiple actors are perpetrating violence together as a joint (temporary) coalition, the components of the coalition (in the form of a string of actor IDs) are listed here.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 5)
“coop:
dichotomous variable, which gets the value of 1 if an event is cooperative at any level, and 0 otherwise […]
direction:
this item shows whether a conflictive/cooperative event is directional or mutual. In other words, if the event is caused by one actor only, this variable takes the value of 1, if both/more sides are equally involved it takes the value of 2.” ([PRIO] Water-Related Intrastate Conflict and Cooperation (WARICC) (v. 1.0), codebook, p. 4)
If multiple actors are perpetrating violence together as a joint (temporary) coalition, the components of the coalition (in the form of a string of actor IDs) are listed here.” ([UCDP] One-sided Violence Dataset (v. 22.1), codebook, p. 5)
“coop:
dichotomous variable, which gets the value of 1 if an event is cooperative at any level, and 0 otherwise […]
direction:
this item shows whether a conflictive/cooperative event is directional or mutual. In other words, if the event is caused by one actor only, this variable takes the value of 1, if both/more sides are equally involved it takes the value of 2.” ([PRIO] Water-Related Intrastate Conflict and Cooperation (WARICC) (v. 1.0), codebook, p. 4)
Deaths
Cf. I/1/ Unit of conflit.
“deaths_b
The best estimate of deaths sustained by side b. Always 0 for one-sided violence events. […]
deaths_civilians
The best estimate of dead civilians in the event. For non-state or state-based events, this is the number of collateral damage resulting in fighting between side a and side b. For one-sided violence, it is the number of civilians killed by side a. […]
deaths_unknown
The best estimate of deaths of persons of unknown status.
best
The best (most likely) estimate of total fatalities resulting from an event. It is always the sum of deaths_a, deaths_b, deaths_civilians and deaths_unknown. integer high The highest reliable estimate of total fatalities
low
The lowest reliable estimate of total fatalities” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 11)
“BatDeaths –
the battle-related combatant fatalities suffered by the state: -9= data unknown” ([COW] Inter-State War Data (v. 4.0), codebook, pp. 3-4)
“deaths_b
The best estimate of deaths sustained by side b. Always 0 for one-sided violence events. […]
deaths_civilians
The best estimate of dead civilians in the event. For non-state or state-based events, this is the number of collateral damage resulting in fighting between side a and side b. For one-sided violence, it is the number of civilians killed by side a. […]
deaths_unknown
The best estimate of deaths of persons of unknown status.
best
The best (most likely) estimate of total fatalities resulting from an event. It is always the sum of deaths_a, deaths_b, deaths_civilians and deaths_unknown. integer high The highest reliable estimate of total fatalities
low
The lowest reliable estimate of total fatalities” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 11)
“BatDeaths –
the battle-related combatant fatalities suffered by the state: -9= data unknown” ([COW] Inter-State War Data (v. 4.0), codebook, pp. 3-4)
Non-conflit variables
“system/ideology
change of the national or international system / ideology with national or international scope
[…]
subnational predominance
de facto political, economic or cultural predominance
[…]
resources
natural resources” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
“Natural resource conflict: financing mechanism (finance)
A dummy variable recording whether the conflict episode had a natural resource financing mechanism. All types of natural resources may finance rebel groups, including illegal commodities such as drugs, hence we also code conflicts as having financing mechanisms if the rebel groups raise funds from trading illegal commodities. For example the Revolutionary United Front (RUF) rebel group fighting against the Sierra Leonean government between 1991 and 2000 (acdid 187) raised funds from illegal extraction and smuggling of diamonds, while in the Casamance conflict in Senegal (acdid 180) rebels have been able to raise funds by selling cashew nuts.
Among conflicts with financing mechanisms only cases where natural resources provided income for the opposition side are included. We assume that natural resources by default finance governments through taxes and state ownership in the same way as other types of income from, for example, tourism and industry; hence we do not expect that natural resource revenues would have a different effect on state-sponsored violence than other types of income.
0. no finance: If the conflict did not include the financing mechanism
1. finance: If the conflict did include the financing mechanism” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 4)
change of the national or international system / ideology with national or international scope
[…]
subnational predominance
de facto political, economic or cultural predominance
[…]
resources
natural resources” ([HIIK] Conflict Barometer (v. 2021), codebook, p. 2)
“Natural resource conflict: financing mechanism (finance)
A dummy variable recording whether the conflict episode had a natural resource financing mechanism. All types of natural resources may finance rebel groups, including illegal commodities such as drugs, hence we also code conflicts as having financing mechanisms if the rebel groups raise funds from trading illegal commodities. For example the Revolutionary United Front (RUF) rebel group fighting against the Sierra Leonean government between 1991 and 2000 (acdid 187) raised funds from illegal extraction and smuggling of diamonds, while in the Casamance conflict in Senegal (acdid 180) rebels have been able to raise funds by selling cashew nuts.
Among conflicts with financing mechanisms only cases where natural resources provided income for the opposition side are included. We assume that natural resources by default finance governments through taxes and state ownership in the same way as other types of income from, for example, tourism and industry; hence we do not expect that natural resource revenues would have a different effect on state-sponsored violence than other types of income.
0. no finance: If the conflict did not include the financing mechanism
1. finance: If the conflict did include the financing mechanism” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 4)
VI/ Transparency
VI/1/ Sources
| Intergovernmental organizations | Governmental organizations | Non-governmental organizations |
| Research organizations | Press media | Social media |
| Other databases | OTHER | TO BE DETERMINED |
Intergovernmental organizations
“UN, EU, AU and other IGO reports” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
Governmental organizations
“governmental publications (where considered reliable, such as those from Truth and Reconciliation Commissions)” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
Non-governmental organizations
“global NGO reports (such as those coming from Human Rights Watch or Amnesty International)” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
Research organizations
“* local monitoring and research organizations (such as SATP for India and Pakistan), […]
* research articles or books” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
* research articles or books” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
Press media
“In terms of sources, UCDP uses Reuters News, Agence France Presse (in English), Associated Press, Xinhua (in English) as well as BBC Monitoring.
[…] local monitoring of various local media (e.g. Press Trust of India for India, or EFE news agency for Latin America or Radio Okapi for DR. Congo)” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
[…] local monitoring of various local media (e.g. Press Trust of India for India, or EFE news agency for Latin America or Radio Okapi for DR. Congo)” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 13)
Social media
“selected social media accounts, including Twitter and Telegram” ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 34)
Other databases
“In addition the online UCDP database and the United States Library of Congress Country Studies were used extensively.” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 3)
OTHER
“A variety of other sources were consulted for specific cases as well.” ([PRIO] The Natural Resource Conflict Dataset (v. 1.0), codebook, p. 3)
VI/2/ Codebook
| Date | Version |
VII/ Update
VII/1/ Current version
| Date | Version |
VII/2/ Regularly updated ?
| Real-time | Month | Quarter |
| Annually | YES, PERIOD TO BE DETERMINED | TO BE DETERMINED |
Real-time
“ACLED data are available to the public and are released in real-time.” ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), codebook, p. 4)
Month
“Follow the same naming convention (year.0.month) and are available from 18.0.1 to 22.0.5.” ([UCDP] Candidate Events Dataset (GED) (v. 22.0.6), codebook, p. 2)
Quarter
“UCDP Candidate is also released as a global version each Quarter. The first covering the first 3 months, the second the first 6 months, the third the first 9 months and the fourth the full year.” ([UCDP] Candidate Events Dataset (UCDP Candidate) (v. 22.01.22.06), codebook, p. 3)
Annually
“The UCDP Candidate data includes the same variables as the UCDP GED dataset, the main difference being that UCDP Candidate has a monthly release cycle and UCDP GED is released annually.” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 2)
YES, PERIOD TO BE DETERMINED
“That comprehensive list of all types of major armed conflict episodes is a regularly updated version of Appendix C in Monty G. Marshall, Third World War, (Lanham, MD: Rowman & Littlefield, 1999) and further detailed in Monty G. Marshall, AMeasuring the Societal Impact of War,@ in F. O. Hampson and D. M. Malone, eds., From Reaction to Prevention (Boulder: Lynne Rienner, 2002).” ([CSP] Major Episodes of Political Violence (MEPV) and Conflict Regions (v. 2012) (Full Set), codebook, p. 1)
VIII/ Access
VIII/1/ Registration ?
| YES | NO |
YES
“ACLED users are required to register through the Access Portal before gaining access to the data.” ([ACLED] Armed Conflict Location & Event Data Project (v. 2019-08-13-2022-08-23), https://acleddata.com/register/, 22/10/2023)
NO
“The UCDP GED is provided in a variety of formats for use by researchers within different fields and with different needs. All formats are available for download free of charge (no registration required) from the UCDP GED website (http://ucdp.uu.se/ged).” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 25)
VIII/2/ Formats
| .XLS/.XLSX | .CSV | .DTA (STATA) | .RDTA |
Comma Separated Values (CSV), Excel (XLS), R Data Frame (RData), STATA (dta)” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 25)
VIII/3/ API ?
“The UCDP GED versions 5.0, 17.1, 17.2, 18.1, 19.1, 20.1, 21.1 and 22.1 as well as monthly candidate events are also provided as an API service, allowing direct machine-to-machine communication (i.e. you can download the data, as well as filter and subset it on our servers directly from your script, do file, library etc. without downloading it to your own system). Documentation is available here: http://ucdp.uu.se/apidocs/” ([UCDP] Georeferenced Event Dataset (GED) (v. 22.1), codebook, p. 25)