This collection consists of 5 structure learning datasets from the Bayesian Network Repository (Scutari, 2010). Task: The dataset collection can be used to study causal discovery algorithms. Summary: Size of collection: 5 datasets with 3 - 56 columns of various sizes Task: Causal Discovery Data Type: Discrete Dataset Scope: Collection Ground Truth: Known / Estimated Temporal Structure: No License: TBD Missing Values: No Missingness Statement: There are no missing values. Collection: The alarm dataset contains the following 37 variables: CVP (central venous pressure): a three-level factor with levels LOW, NORMAL and HIGH. PCWP (pulmonary capillary wedge pressure): a three-level factor with levels LOW, NORMAL and HIGH. HIST (history): a two-level factor with levels TRUE and FALSE. TPR (total peripheral resistance): a three-level factor with levels LOW, NORMAL and HIGH. ... (33 more variables, see the corresponding .html file) The binary synthetic asia dataset: D (dyspnoea), a two-level factor with levels yes and no. T (tuberculosis), a two-level factor with levels yes and no. L (lung cancer), a two-level factor with levels yes and no. B (bronchitis), a two-level factor with levels yes and no. A(visit to Asia), a two-level factor with levels yes and no. S (smoking), a two-level factor with levels yes and no. X (chest X-ray), a two-level factor with levels yes and no. E (tuberculosis versus lung cancer/bronchitis), a two-level factor with levels yes and no. The binary coronary dataset: Smoking (smoking): a two-level factor with levels no and yes. M. Work (strenuous mental work): a two-level factor with levels no and yes. P. Work (strenuous physical work): a two-level factor with levels no and yes. Pressure (systolic blood pressure): a two-level factor with levels 140. Proteins (ratio of beta and alpha lipoproteins): a two-level factor with levels 3. Family (family anamnesis of coronary heart disease): a two-level factor with levels neg and pos. The hailfinder dataset contains the following 56 variables: N07muVerMo (10.7mu vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down. SubjVertMo (subjective judgment of vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down. QGVertMotion (quasigeostrophic vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down. CombVerMo (combined vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down. AreaMesoALS (area of meso-alpha): a four-level factor with levels StrongUp, WeakUp, Neutral and Down. SatContMoist (satellite contribution to moisture): a four-level factor with levels VeryWet, Wet, Neutral and Dry. ... (49 more variables are in the correspondent .html file) The lizards dataset contains the following 3 variables: Species (the species of the lizard): a two-level factor with levels Sagrei and Distichus. Height (perch height): a two-level factor with levels high (greater than 4.75 feet) and low (lesser or equal to 4.75 feet). Diameter (perch diameter): a two-level factor with levels narrow (greater than 4 inches) and wide (lesser or equal to 4 inches).