A new conceptual data model that addresses the geometric dimensioning and tolerancing concepts of datum systems, datums, datum features, datum targets, and the relationships among these concepts, is presented. Additionally, a portion of a related data model, Part 47 of STEP (ISO 10303-47), is reviewed and a comparison is made between it and the new conceptual data model. NOTE—Though the scope of the DSCDM is limited to the concepts mentioned above, the aim is to provide a foundation upon which more comprehensive GD&T data models may be based.Datum is an entity name and datum refers to the object). Attribute names are printed in italic type . Additionally, permissible values from enumerated data types are printed in all uppercase letters .NOTE—The following conventions are employed throughout the course of this paper. To distinguish between EXPRESS entities and the objects they represent, entity names are printed in bold type and the objects they represent are printed in non-bold type. Furthermore, entity names start with a leading uppercase letter  requirements have been exchanged with technical drawings. However, with the advent of computer-aided design, manufacturing, and inspection equipment, the ability to exchange these requirements in a computer-sensible manner has become increasingly more desirable. As “a data model is an effective technique to define the shareable semantics that are essential to the success of data communication in an integrated environment” , a conceElectronic assembly, interconnect and packaging design [“The first step in data modeling is to define the data requirements” . In regag design . With thMost of the following definitions are from existing drawing-based GD&T standards and associated reference books. These definitions are important, because they explain some of the concepts that are at the foundation of these GD&T standards, and consequently form the basis for the requirements of the DSCDM.Datum: “A theoretically exact point, axis, or plane derived from the true geometric counterpart of a specified datum feature. A datum is the origin from which the location or geometric characteristics of features of a part are established” .Datum Feature: “An actual feature of a part that is used to establish a datum” .Datum Feature Symbol: “The symbolic means of indicating a datum feature consists of a capital letter enclosed in a square frame and a leader line extending from the frame to the concerned feature, terminating with a triangle” .Datum System: “A group of two or more separate datums used as a combined reference for a toleranced feature” .Datum Reference Frame: A framework that consists of three mutually perpendicular datum planes, three datum axes (located at the intersection of each pair of datum planes), and a datum point (that is located at the intersection of the three datum planes).Datum Target: “A specified point, line, or area on a part used to establish a datum” .Datum Target Frame: “The datum targets are indicated by a circular frame divided in two compartments by a horizontal line. The lower compartment is reserved for a letter and a digit. The letter represents the datum feature and the digit the datum target number. The upper compartment is reserved for additional information, such as dimensions of the target area. If there is not sufficient space within the compartment, the information may be placed outside and connected to the appropriate compartment by a leader line” .Feature: “The general term applied to a physical portion of a part, such as a surface, pin, tab, hole, or slot” . [Feature Control Frame: “The feature control frame is a rectangular box containing the geometric characteristic symbol and the form, orientation, profile, runout, or location tolerance. If necessary, datum references and modifiers applicable to the feature or the datums are also contained in the box, e.g.”  .Feature of Size: “One cylindrical or spherical surface, or a set of two opposed elements or opposed parallel surfaces, associated with a size dimension” .Least Material Condition (LMC): “The condition in which a feature of size contains the least amount of material within the stated limits of size—for example, maximum hole diameter, minimum shaft diameter” .least material requirement permits an increase in the stated geometrical tolerance when the concerned feature departs from its least material condition (LMC)” [Least Material Requirement: “The n (LMC)” .Maximum Material Condition (MMC): “The condition in which a feature of size contains the maximum amount of material within the stated limits of size—for example, minimum hole diameter, maximum shaft diameter” .maximum material principle is a tolerancing principle which requires that the virtual condition for the toleranced feature(s) and, if indicated, the maximum material condition of perfect form for datum feature(s), shall not be violated” [Maximum Material Principle: “The iolated” .Regardless of Feature Size (RFS): “The term used to indicate that a geometric tolerance or datum reference applies at any increment of size of the feature within its size tolerance” .Shape_aspect, Shape_aspect_relationship, Property_definition, and Property_definition_relationship. A review of these entities is presented in STEP integrated generic resources are a series of STEP parts that define resource constructs that are context-independent. The underlying structure of the DSCDM is based on four entities from the STEP integrated generic resources. These entities are Shape_aspect entity of STEP Part 41 [Shape_aspect based entities are the entities based on the Shape_aspect_relationship entity of STEP Part 41. At the bottom of the page are the entities based on the Property_definition entity of STEP Part 41. Note that the DSCDM does not actually contain entities based on the Property_definition_relationship entity of STEP Part 45 [Property_definition based entities are related with attributes that have been included in the Property_definition based entities. For example, instead of specifying a Property_definition_relationship based entity in the DSCDM to relate the Datum_system_definition entity with the Datum_precedence_assignment entity, the relationship between these two entities is established by the assigned_datum_precedences attribute of the Datum_system_definition entity.Property_definition_relationship based entities exist in the DSCDM, they exist in spirit wherever two Property_definition based entities are related.NOTE—While no The DSCDM is presented in the EXPRESS-G diagram shown in  Part 41  are at t Part 45 . InsteadShape_aspect based entities are first, followed by the Shape_aspect_relationship based entities, and finally, the Property_definition based entities.The definitions of the entities presented in Datum_system corresponds to a datum system (see Sec. 3 of this paper) that is comprised of one to three datums.Datum_system entity is based on the Shape_aspect entity of STEP Part 41 [NOTE—The  Part 41 .NOTE—The definition of datum system as defined in ISO 5459-1981 is given in Sec. 3 of this paper. However, for the purpose of this model, the definition of datum system has been extended so that a datum system may be comprised of a single datum.A datum_usages: The datum_usages attribute specifies a set of one to three Datum_usage_in_datum_systems. Each of the Datum_usage_in_datum_systems in this set corresponds to the usage of a datum in the datum system.defining_definition: The defining_definition attribute specifies the Datum_system_definition that specifies the characteristics of the corresponding datum system .NOTE—On technical drawings, the characteristics of a datum system are typically specified in a feature control frame.EXAMPLE—Both Datum_features specified as the used_datum_feature by the Datum_feature_usage_in_datums that are specified as the datum_feature_usages by the Datums that are specified as the used_datum by the Datum_usage_in_datum_systems that are specified as the datum_usages of the Datum_system, no Datum_feature may be specified more than once.NOTE—WR1 corresponds to the assertion that each datum feature shall not be used more than once in establishing any one datum system.WR1: Of the Datum_targets specified as the used_datum_target by the Datum_target_usage_in_datum_target_sets specified as the datum_target_usages by the Datum_target_sets specified as the used_datum_feature by the Datum_feature_usage_in_datums that are specified as the datum_feature_usages by the Datums that are specified as the used_datum by the Datum_usage_in_datum_systems that are specified as the datum_usages of the Datum_system, no Datum_target may be specified more than once.NOTE—WR2 corresponds to the assertion that each datum target shall not be used more than once in establishing any one datum system.WR2: Of the Datum corresponds to a datum (see Sec. 3 of this paper). A Datum may be either a Simple_datum or a Common_datum.Datum entity is based on the Shape_aspect entity of STEP Part 41 [NOTE—The  Part 41 .A datum_feature_usages: The datum_feature_usages attribute specifies a set of zero or more Datum_feature_usage_in_datums. Each of the Datum_feature_usage_in_datums in this set corresponds to the usage of a datum feature in establishing the datum.Simple_datum is a type of Datum that corresponds to a datum that is established from exactly one datum feature.A Simple_datum shall be specified as the used_datum by at least one Datum_usage_in_datum_system.NOTE—WR1 corresponds to the assertion that each simple datum shall be used in at least one datum system.WR1: Each Simple_datum shall specify exactly one Datum_feature_usage_in_simple_datum as its datum_feature_usages.NOTE—WR2 corresponds to the assertion that each simple datum shall be established from exactly one datum feature.WR2: Each Common_datum is a type of Datum that corresponds to a datum that is established from more than one datum feature.NOTE—On technical drawings, a datum that is established from multiple datum features is indicated by placing the identifying letters of the datum features, separated by a dash, within a single compartment in a feature control frame. There is no significance to the order of the datum feature identifying letters within a compartment of the feature control frame.EXAMPLE—The technical drawing presented in A Common_datum shall be specified as the used_datum by at least one Datum_usage_in_datum_system.NOTE—WR1 corresponds to the assertion that each common datum shall be used in at least one datum system.WR1: Each Common_datum shall specify more than one Datum_feature_usage_in_common_datum as its datum_feature_usages.NOTE—WR2 corresponds to the assertion that each common datum shall be established from more than one datum feature.WR2: Each Datum_feature corresponds to a datum feature (see Sec. 3 of this paper). A Datum_feature may be a Datum_target_set.Datum_feature entity is based on the Shape_aspect entity of STEP Part 41 [NOTE—The  Part 41 ..NOTE—On technical drawings, a feature is typically identified as a datum feature by means of a datum feature symbol, e.g., NOTE—The concept of datum feature in the DSCDM applies to features that are used to establish one or more datums. Features that may be used as datum features include “partial” features and datum target sets, as well as “complete” and composite features. The concept of datum feature in the DSCDM does not pertain to features in which only a portion of the feature  is used to establish one or more datums. “Partial” and composite features are discussed in Sec. 10.2 of this paper.A identification: The identification attribute specifies the string value by which the corresponding datum feature is referred.).NOTE—On technical drawings, each datum feature is referred to by an identifying letter, .WR1: There shall be at most one Datum_target_set is a type of Datum_feature that corresponds to a set of one or more datum targets (see Sec. 3 of this paper).) indicate in which datum target sets the associated datum targets are used.EXAMPLE—There are three datum target sets shown in the technical drawing presented in A datum_target_usages: The datum_target_usages attribute specifies a set of one or more Datum_target_usage_in_datum_target_sets. Each of the Datum_target_usage_in_datum_target_sets in this set corresponds to the usage of a datum target in the datum target set.Datum_target corresponds to a datum target (see Sec. 3 of this paper).Datum_target entity is based on the Shape_aspect entity of STEP Part 41 [NOTE—The  Part 41 .NOTE—Datum targets are typically used in situations where it is inappropriate to specify an entire surface as a datum feature.EXAMPLE—There are six datum targets shown in A datum_target_usages: The datum_target_usages attribute specifies a set of one or more Datum_target_usage_in_datum_target_sets. Each of the Datum_target_usage_in_datum_target_sets in this set corresponds to the usage of the datum target in a datum target set.Datum_usage_in_datum_system corresponds to the usage of a datum in a datum system.Datum_usage_in_datum_system entity is based on the Shape_aspect_relationship entity of STEP Part 41 [NOTE—The  Part 41 .A comprised_datum_system: The comprised_datum_system attribute specifies the Datum_system that corresponds to the datum system that is either partially or wholly comprised of the corresponding datum.used_datum: The used_datum attribute specifies the Datum that corresponds to the datum that is used in the corresponding datum system.precedence_assignment: The precedence_assignment attribute specifies the Datum_precedence_assignment that corresponds to the specification of the order in which the datum is established within the datum system.comprised_datum_system and used_datum shall be unique within a population of Datum_usage_in_datum_system.NOTE—UR1 corresponds to the assertion that each datum shall not be used more than once in any one datum system.UR1: The combination of Datum specified as the used_datum shall either be a Common_datum or Simple_datum.NOTE–WR1 corresponds to the assertion that each datum that is used in a datum system shall be established from one or more datum features.WR1: The Datum_feature_usage_in_datum_system corresponds to the usage of a datum feature in establishing a datum system.Datum_feature_usage_in_datum_system entity is based on the Shape_aspect_relationship entity of STEP Part 41 [NOTE—The  Part 41 .Datum_feature and a Datum_system is indirectly established with a Datum_feature_usage_in_datum, a Datum, and a Datum_usage_in_datum_system. Therefore, a Datum_feature_usage_in_datum_system should not be used unless it is necessary to indicate the application of either the least material requirement or the maximum material principle (see Sec. 3 of this paper) to a datum feature within the context of a datum system. In essence, a Datum_feature_usage_in_datum_system corresponds to a datum feature in the context of a datum system.NOTE—The relationship between a A established_datum_system: The established_datum_system attribute specifies the Datum_system that corresponds to the datum system that is established from the corresponding datum feature.used_datum_feature: The used_datum_feature attribute specifies the Datum_feature that corresponds to the datum feature that is used to establish the corresponding datum system.applied_material_condition_property: The applied_material_condition_property attribute specifies the Datum_feature_material_condition_property that corresponds to the specification of a material condition property  that is applied to the datum feature in the context of the datum system.Datum_feature specified as the used_datum_feature shall be specified as the used_datum_feature by a Datum_feature_usage_in_datum that specifies a Datum as the established_datum, and that Datum shall be specified as the used_datum by a Datum_usage_in_datum_system that specifies the same Datum_system as the comprised_datum_system, as is specified as the established_datum_system by the Datum_feature_usage_in_datum_system.NOTE—WR1 corresponds to the assertion that the datum feature shall be used to establish a datum that is used in the datum system.WR1: The Datum_feature_usage_in_datum corresponds to the usage of a datum feature in establishing a datum. A Datum_feature_usage_in_datum is either a Datum_feature_usage_in_simple_datum or a Datum_feature_usage_in_common_datum.Datum_feature_usage_in_datum entity is based on the Shape_aspect_relationship entity of STEP Part 41 [NOTE—The  Part 41 .A established_datum: The established_datum attribute specifies the Datum that corresponds to the datum that is established from the corresponding datum feature.used_datum_feature: The used_datum_feature attribute specifies the Datum_feature that corresponds to the datum feature that is used to establish the corresponding datum.Datum_feature_usage_in_simple_datum is a type of Datum_feature_usage_in_datum that corresponds to the usage of a datum feature in establishing a datum that is established from exactly one datum feature.A established_datum: The established_datum attribute specifies the Simple_datum that corresponds to the datum that is established from the corresponding datum feature.Datum_feature specified by the inherited used_datum_feature attribute.NOTE—“The corresponding datum feature” refers to the datum feature that corresponds to the Datum_feature_usage_in_common_datum is a type of Datum_feature_usage_in_datum that corresponds to the usage of a datum feature in establishing a datum that is established from more than one datum feature.A established_datum: The established_datum attribute specifies the Common_datum that corresponds to the datum that is established, in part, from the corresponding datum feature.Datum_feature specified by the inherited used_datum_feature attribute.NOTE—“The corresponding datum feature” refers to the datum feature that corresponds to the Datum_target_usage_in_datum_target_set corresponds to the usage of a datum target in a set of datum targets.Datum_target_usage_in_datum_target_set entity is based on the Shape_aspect_relationship entity of STEP Part 41 [NOTE—The  Part 41 . symbol in NOTE—On technical drawings, the usage of a datum target in a datum target set is indicated with a datum target frame, e.g., the  datum target frame in EXAMPLE—The A comprised_datum_target_set: The comprised_datum_target_set attribute specifies the Datum_target_set that corresponds to the datum target set that is either partially or wholly comprised of the corresponding datum target.datum_target_number: The datum_target_number attribute specifies the integer value by which the corresponding datum target is identified within the corresponding datum target set.NOTE—Datum target numbers are described in 7.1.1 of ISO 5459 . datum target frame of EXAMPLE—The datum target number “1” in the used_datum_target: The used_datum_target attribute specifies the Datum_target that corresponds to a datum target that is used in the corresponding datum target set.used_datum_target and defined_datum_target_set shall be unique within a population of Datum_target_usage_in_datum_target_set.NOTE—UR1 corresponds to the assertion that each datum target shall not be used in any one datum target set more than once.UR1: The combination of datum_target_number and defined_datum_target_set shall be unique within a population of Datum_target_usage_in_datum_target_set.NOTE—UR2 corresponds to the assertion that within a datum target set each datum target shall be identified by a unique datum target number.UR2: The combination of Datum_system_definition corresponds to the specification of the characteristics of a datum system. These characteristics include the order in which the datums are established within the datum system and any material condition properties  that are explicitly applied to datum features within the context of the datum system. A Datum_system_definition shall either be a Datum_system_definition_with_material_conditions or a Datum_system_definition_without_material_conditions.Datum_system_definition entity is based on the Property_definition entity of STEP Part 41 [NOTE—The  Part 41 .NOTE—On technical drawings, the characteristics of a datum system are typically specified in a feature control frame.A defined_datum_system: The defined_datum_system attribute specifies the Datum_system that corresponds to the datum system the characteristics of which are specified.assigned_datum_precedences: The assigned_datum_precedences attribute specifies a set of one to three Datum_precedence_assignments. Each of the Datum_precedence_assignments in this set corresponds to the specification of the order in which a datum is established within the datum system.Datum_precedence_assignment within the set of Datum_precedence_assignments specified as the assigned_datum_precedences shall specify as its assigned_to a Datum_usage_in_datum_system that specifies as its comprised_datum_system the same Datum_system as specified as the defined_datum_system.NOTE—WR1 corresponds to the assertion that each datum system specification shall only specify the precedence of datums used in the datum system that the specification characterizes.WR1: Each Datum_precedence_assignment that has a name of TERTIARY shall not exist within the set of Datum_precedence_assignments specified as the assigned_datum_precedences unless a Datum_precedence_assignment exists within that set that has a name of SECONDARY.NOTE—WR2 corresponds to the assertion that each datum system specification that specifies a tertiary datum shall also specify a secondary datum.WR2: A Datum_precedence_assignment that has a name of SECONDARY shall not exist within the set of Datum_precedence_assignments specified as the assigned_datum_precedences unless a Datum_precedence_assignment exists within that set that has a name of PRIMARY.NOTE—WR3 corresponds to the assertion that each datum system specification that specifies a secondary datum shall also specify a primary datum.WR3: A Datum_system_definition shall be specified as the referenced_datum_system_definition by at least one Geometric_tolerance_with_specified_datum_systrem or Dimension_with_specified_datum_system.NOTE—WR4 corresponds to the assertion that each datum system specification shall be referenced by at least one geometric tolerance or dimension.WR4: Each Datum_system_definition_with_material_conditions is a type of Datum_system_definition that corresponds to a specification of a datum system that specifies the application of material condition properties  to one or more datum features within the context of the datum system.Datum_system_definition_with_material_conditions is specified in a feature control frame that contains either at least one least material requirement symbol  that is preceded immediately by a datum feature letter or at least one maximum material principle symbol  that is preceded immediately by a datum feature letter, e.g.,  .NOTE—On technical drawings, a datum system specification that corresponds to a A applied_material_condition_properties: The applied_material_condition_properties attribute specifies a set of one or more Datum_feature_material_condition_propertys. Each of the Datum_feature_material_condition_propertys in this set corresponds to the specification of a material condition property that is explicitly applied to a datum feature within the context of the datum system.Datum_feature_material_condition_property within the set of Datum_feature_material_condition_propertys specified as the applied_material_condition_properties shall specify as its applied_to a Datum_feature_usage_in_datum_system that specifies as its established_datum_system the same Datum_system as specified as the defined_datum_system.NOTE—WR1 corresponds to the assertion that each datum system specification shall only specify material condition properties for datum features used to establish the datum system that the specification characterizes.defined_datum_system attribute referred to in WR1 is inherited from the Datum_system_definition entity of which this entity is a subtype.NOTE—The WR1: Each Datum_system_definition_without_material_conditions is a type of Datum_system_definition that corresponds to a specification of a datum system in which no material condition properties  are specified.Datum_system_definition_without_material_conditions is typically specified in a feature control frame that contains neither a least material requirement symbol  that is immediately preceded by a datum feature letter nor a maximum material principle symbol  that is immediately preceded by a datum feature letter, e.g., .NOTE—In technical drawings, a datum system specification that corresponds to a Datum_system_definition_without_material_conditions could also be specified in a dimension related note; see NOTE—On technical drawings, a datum system specification that corresponds to a A Datum_precedence_assignment corresponds to the specification of the order in which a datum is established within a datum system.Datum_precedence_assignment entity is based on the Property_definition entity of STEP Part 41 [NOTE—The  Part 41 .NOTE—On technical drawings, the precedence of a datum within a datum system is typically specified in a feature control frame. The location of the compartment containing the letter(s) corresponding to the datum feature(s) from which the datum is established indicates the assigned precedence. The compartment for the primary datum (if it exists) is immediately to the right of the compartment containing the tolerance value. The compartment for the secondary datum (if it exists) is immediately to the right of the compartment for the primary datum. Lastly, the compartment for the tertiary datum (if it exists) is immediately to the right of the compartment for the secondary datum.EXAMPLE—A assigned_to: The assigned_to attribute specifies a Datum_usage_in_datum_system. In essence, the Datum_usage_in_datum_system corresponds to the datum within the context of the datum system to which the datum precedence is assigned.NOTE—A datum within the context of one datum system may be assigned one precedence, e.g., primary, and the same datum within the context of another datum system may be assigned another precedence, e.g., secondary.EXAMPLE—In name: The name attribute specifies the value of the assigned datum precedence. Valid values for the name are PRIMARY, SECONDARY, and TERTIARY.associate_datum_system_definition: The associate_datum_system_definition attribute specifies the Datum_system_definition that corresponds to the datum system specification to which the datum precedence is associated.name and associate_datum_system_definition shall be unique within a population of Datum_precedence_assignments.NOTE—UR1 corresponds to the assertion that no two datums of a datum system shall have the same precedence.UR1: The combination of Datum_feature_material_condition_property corresponds to the specification of a material condition property  that is explicitly applied to a datum feature within the context of a datum system.Datum_feature_material_condition_property entity is based on the Property_definition entity of STEP Part 41 [NOTE—The  Part 41 .A applied_to: The applied_to attribute specifies a Datum_feature_usage_in_datum_system. In essence, the Datum_feature_usage_in_datum_system corresponds to the datum feature within the context of the datum system to which the material condition property is applied.least material requirement, and the same datum feature within the context of another datum system may have another material condition property applied, e.g., maximum material principle.NOTE—A datum feature within the context of one datum system may have one material condition property applied, e.g., name: The name attribute specifies the value by which the material condition property is known. Valid values for the name are LEAST_MATERIAL_REQUIREMENT and MAXIMUM_MATERIAL_PRINCIPLE (see Sec. 3 of this paper).Datum_feature_material_condition_property that has a name of LEAST_MATERIAL_REQUIREMENT corresponds to a datum feature letter followed by the  symbol in a feature control frame of a technical drawing, e.g.,  .NOTE—A Datum_feature_material_condition_property that has a name of MAXIMUM_MATERIAL_PRINCIPLE corresponds to a datum feature letter followed by the  symbol in a feature control frame of a technical drawing, e.g.,  .NOTE—A regardless of feature size principle (see Sec. 3 of this paper) shall be in effect in cases where the datum feature is a feature of size (see Sec. 3 of this paper) and a Datum_feature_material_condition_property is not specified.NOTE—It shall be understood that the associate_datum_system_definition: The associate_datum_system_definition attribute specifies the Datum_system_definition_with_material_conditions that corresponds to the datum system specification to which the material condition property is associated.Geometric_tolerance_with_specified_datum_system entity is not completely defined here, as it is not within the scope of this paper. However, the referenced_datum_system_definition attribute of this entity is defined to illustrate how the DSCDM could be tied into a larger GD&T data model.Geometric_tolerance_with_specified_datum_system entity is based on the Property_definition entity of STEP Part 41 [NOTE—The  Part 41 .The referenced_datum_system_definition: The referenced_datum_system_definition attribute specifies the Datum_system_definition that corresponds to the datum system specification that is referenced by the geometric tolerance.Dimension_with_specified_datum_system entity is not completely defined here, as it is not within the scope of this paper. However, the referenced_datum_system_definition attribute of this entity is defined to illustrate how the DSCDM could be tied into a larger GD&T data model.Dimension_with_specified_datum_system entity is based on the Property_definition entity of STEP Part 41 [NOTE—The  Part 41 .Datum_system_definition entity is associated almost exclusively with geometric tolerances, clause 4.4 of ASME Y 14.5M [Dimension_with_specified_datum_system entity is shown in NOTE—While the data modeled with the EXAMPLE—The three linear dimensions presented in The referenced_datum_system_definition: The referenced_datum_system_definition attribute specifies the Datum_system_definition_without_material_conditions that corresponds to the datum system specification that is referenced by the dimension.Datum_target, Datum_feature, and Datum entities . Additionally, the EXPRESS-G diagram does not show that the Datum_target, Datum_feature, and Datum entities are subtypes of the Shape_aspect entity of STEP Part 41 [A pseudo EXPRESS-G diagram of the datum system related portion of the Part 47 model is presented in  Part 41 .NOTE—The actual EXPRESS declarations of these entities have not been included in the definitions given in Tables 1NOTE—The clause and figure numbers specified within Tables 1Geometric_tolerance entity of which the Geometric_tolerance_with_datum_reference entity is a subtype is not shown here, as it is not within the scope of this paper.NOTE—The definition of the The definitions of the entities shown in Tables 1NOTE—The STEP architecture is such that STEP application protocols may specialize entities from the STEP integrated generic resources. However, deficiencies in entities of the type mentioned above will only be passed on to the STEP application protocols that incorporate them.Datum_feature entity from STEP Part 47 will not be able to support multiple use datum features (see Sec. 6.3).EXAMPLE—A STEP application protocol that incorporates the This section discusses the differences between the DSCDM and portions of the model presented in STEP Part 47  that areDatum_system and Datum_system_definition entities of the DSCDM. Two independent comments were submitted against the STEP Part 47 DIS [Datum_reference only made sense in the context of a datum system. Concurring with those comments, the Datum_system and Datum_system_definition entities were incorporated within the DSCDM.One of the main differences between the Part 47 model and the DSCDM is that the Part 47 model has no entities that are equivalent to the t 47 DIS  documentidentification attribute is on the Datum_feature entity; in contrast, in the Part 47 model the identification attribute is on the Datum entity. In practice, it is the datum feature to which an identifier is assigned. ASME Y14.5M [identification attribute may seem moot, because if the identification attribute is placed on the Datum entity, the name of the associated datum feature could easily be derived. However, in cases in which a datum is established from more than one datum feature, the Part 47 model produces ambiguous results because it is impossible to determine the name of the datum features from the value of the identification attribute on a Datum. The DSCDM does not have this ambiguity, as the identification attribute is on the Datum_feature entity. feature control frame of the position tolerance in identification attribute of the Datum entity would have a value of “A–B”. However, it would be unclear as to which datum feature is identified as A and which datum feature is identified as B.EXAMPLE—The Datum and Datum_feature entities in the Part 47 model are subtypes of the Shape_aspect entity of STEP Part 41 [name attribute. However, as a Datum_feature corresponds to an actual feature of a part it is likely that the name attribute will not be available for the datum feature identifying letter because it will likely be used for another purpose . Furthermore, as datums are identified solely for GD&T purposes it is likely that the inherited name attribute on the Datum entity would be available, thereby making the identification attribute on the Datum entity not only misplaced but redundant.NOTE—As the  Part 41 , they boIn the DSCDM the feature_basis_relationship attribute and WR1 on the Datum_feature entity specify that a Datum_feature shall be related to exactly one Datum. On the other hand, in the DSCDM the inverse datum_feature_usages attribute on the Datum_feature entity constrains the number of Datums that shall be established from a Datum_feature to one or more.). Also, , and ). Furthermore, both datum features A and B are used once again to establish the primary datum (yet another center axis) of the datum system specified by the position tolerance . As the Part 47 model limits the number of datums that may be established from a datum feature to one, this situation cannot be represented with the Part 47 model.EXAMPLE—The technical drawing presented in The Part 47 model fails to account for the fact that a datum feature may be used to establish multiple datums, whereas the DSCDM does account for this fact. In the Part 47 model, the target_basis_relationship attribute and WR1 on the Datum_target entity specify that a Datum_target shall be related to exactly one Datum. On the other hand, the DSCDM does not specify a direct relationship between a Datum_target and a Datum. Instead, in the DSCDM the relationship between a Datum_target and a Datum is specified indirectly via the Datum_target_set entity and the two relationship entities Datum_target_usage_in_datum_target_set and Datum_feature_usage_in_datum. In the DSCDM the constraints on Datum_target and Datum_feature correspond to the assertion that a datum target shall be used in at least one datum target set and because a datum target set is a type of datum feature, the datum target set shall be used to establish at least one datum. The technical drawing presented in  and  datum target frames is associated with two datum target sets, F and G, each of which is used to establish a separate datum. As the Part 47 model limits the number of datums that may be established from a datum target to one, this situation cannot be represented with the Part 47 model.EXAMPLE—The datum target point in The Part 47 model fails to account for the fact that a datum target may be used to establish multiple datums, whereas the DSCDM does account for this fact. In the Part 47 model the Datum_target_set is a type of Datum_feature. The Part 47 model has no entity that is equivalent to the Datum_target_set entity. Furthermore, the Part 47 model prevents the Datum_feature entity or a specialization  of it to serve as a set of datum targets. That is, in the Part 47 model the attributes target_basis_relationship and feature_basis_relationship on the Datum_target and Datum_feature entities, respectively, in association with WR1 on each of these entities, prevent a Datum_target from being related to a Datum_feature via a Shape_aspect_relationship.NOTE—On technical drawings, datum target frames are used to group datum targets into datum target sets.,  and  datum target frames make up datum target set A. Additionally, the two datum target areas (hatched regions are used to indicate datum target areas) that are connected to the  and  datum target frames constitute datum target set B. Also, the datum target point that is connected to the  datum target frame makes up datum target set C.EXAMPLE—In the technical drawing presented in In the DSCDM, a target_id attribute on the Datum_target entity indicates that the use of this attribute is to associate a datum target number with a datum target. However, the placement of this attribute on the Datum_target entity only allows a single datum target number to be associated with a datum target, which is not surprising as the Part 47 model only allows a datum target to be associated with a single datum. On the other hand, in the DSCDM the placement of the datum_target_number attribute on the Datum_target_usage_in_datum_target_set entity permits a different datum target number to be assigned to each usage of a datum target in a datum target set.NOTE—On technical drawings, datum target frames are used to group datum targets into datum target sets. Additionally, datum target frames specify datum target numbers by which the datum targets are identified within the datum target sets.The technical drawing presented in  and  datum target frames is associated with two datum targets sets, C and G. This datum target is identified by a datum target number of “1” when it is associated with datum target set C and is identified by a datum target number of “2” when it is associated with datum target set G.EXAMPLE—The datum target point in The Part 47 model fails to account for the fact that multiple datum target numbers may be associated with a datum target, whereas the DSCDM does account for this fact. In the Part 47 model, the definition for the A composite datum feature is a datum feature that is composed of other features. Neither the Part 47 model nor the DSCDM have an explicit entity that corresponds to a composite datum feature. However, it is of interest to examine how composite datum features may be represented using these two models.Composite_shape_aspect entity, the intent of which is to group Shape_aspects for a purpose. At first glance this seems like a perfect match—a Shape_aspect that is a Datum_feature as well as a Composite_shape_aspect could represent a composite datum feature. This usage of Composite_shape_aspect is even mentioned in a note in clause 4.4.1 of STEP Part 47 [feature_basis_relationship inverse attribute on the Datum_feature entity requires that a Datum_feature be specified as the relating_shape_aspect by exactly one Shape_aspect_relationship. Conversely, the component_relationships inverse attribute on the Composite_shape_aspect entity requires that a Composite_shape_aspect be specified as the relating_shape_aspect by two or more Shape_aspect_relationships (these Shape_aspect_relationships relate the Composite_shape_aspect with the Shape_aspects from which it is composed). This conflict between the two inverse attributes prohibits a Shape_aspect from being both a Datum_feature and a Composite_shape_aspect. The model presented in STEP Part 47 has a  Part 47   submitted against the STEP Part 47 DIS  documentThe second difference is that in the Part 47 model the Referenced_modified_datum entity is used to associate modifiers with datums, not datum features. On the other hand, in the DSCDM the Datum_feature_material_condition_property entity is used to associate modifiers with datum features. datum reference letter is somewhat of a misnomer, as a datum reference letter actually refers to a datum feature.NOTE—The term  symbol following the letter “A” in the feature control frame associates the maximum material principle with datum feature A. Likewise, the  symbol following the letter “B” in the feature control frame associates the maximum material principle with datum feature B.EXAMPLE—In The Part 47 model is inconsistent with ASME Y14.5M [NOTE—While the DSCDM supports the application of different modifiers to the datum features of a common datum, as is permitted in ASME Y14.5M, the author of this paper has been unable to find examples of this situation in standards or reference books. Therefore, it is believed that occurrences of this case are probably extremely limited.One may argue that if modifiers are directly associated with datums, as in the Part 47 model, they are indirectly associated with the datum features that establish those datums. However, this contrivance fails in cases in which the requirements are such that all the datum features from which a common datum is established are not to be associated with the same modifier.Dimension_with_specified_datum_system corresponds to a type of dimension that references a datum system specification. The Part 47 model has no entity that is equivalent to the Dimension_with_specified_datum_system entity.Dimension_with_specified_datum_system entity is not completely defined in this paper, as a discussion of dimensions is outside its scope.NOTE—The NOTE—Clause 4.4 of ASME Y14.5M [EXAMPLE—The technical drawing presented in In the DSCDM the Datum, Datum_feature, and Datum_target entities assert that each datum shall be established from one or more datum features or datum targets, that each datum feature shall be used to establish a single datum, and that each datum target shall be used to establish a single datum. In contrast, the DSCDM only requires that the relationship between the datum feature(s) from which a datum is established be specified for those datums that are used to establish a datum system. That is, for a datum not used to establish a datum system (some datums may just be the origin of one or more dimensions), the DSCDM does not require the corresponding Datum to be related to a Datum_feature via the Datum_feature_usage_in_datum entity.Datum, Datum_feature, and Datum_target entities in the Part 47 model). However, as the DSCDM does not require a Datum to be related to either a Datum_feature or a Datum_system, this situation can be represented using the DSCDM.EXAMPLE—In NOTE—Although the datum planes that are labeled “Second datum plane” and “Third datum plane” in The Part 47 model cannot be used to represent datums that are not directly established from datum features or datum targets. This is because the attributes and rules on the This paper has presented a data model (the DSCDM) that covers the concepts of datum systems, datums, datum features, and datum targets. Furthermore, for comparison purposes, this paper has presented the datum related portions of the data model given in STEP Part 47 . In pres


Anopheles mosquitoes were first recognised as the transmitters of human malaria in the late 19th Century and have been subject to a huge amount of research ever since. Yet there is still much that is unknown regarding the ecology, behaviour (collectively ‘bionomics’) and sometimes even the identity of many of the world’s most prominent disease vectors, much less the within-species variation in their bionomics. Whilst malaria elimination remains an ambitious goal, it is becoming increasingly clear that knowledge of vector behaviour is needed to effectively target control measures. A database of bionomics data for the dominant vector species of malaria worldwide has been compiled from published peer-reviewed literature. The data identification and collation processes are described, together with the geo-positioning and quality control methods. This is the only such dataset in existence and provides a valuable resource to researchers and policy makers in this field. Biting location, biting time and host preference will influence how effectively a mosquito can transmit malaria. In addition, understanding the behaviour of the vector guides how best it can be controlled and the likelihood that a particular intervention measure will be successful2. For example, a night feeding, anthropophilic, endophagic and endophilic mosquito  is likely to be a highly effective transmitter of malaria . These same characteristics make this vector an ideal candidate for indoor insecticide-based control such as indoor residual spraying (IRS), which targets mosquitoes that preferentially rest indoors, or long-lasting insecticide-treated nets (LLINs), which target those species attracted to humans indoors at night. On the other hand, a species that is zoophilic, exophagic and exophilic  would not be impacted by these control methods , but may be vulnerable to outdoor space spraying or insecticidal zooprophylaxis.The behaviour and life history characteristics of a mosquito vector contribute to the relative importance of the species in terms of human malaria transmission4. It is becoming more widely accepted that simply scaling up existing insecticide based intervention methods is insufficient to tackle increasingly resistant vector populations or to impact existing, control avoiding species5–7. Spatially explicit, species-specific behavioural data are needed to populate the emerging transmission models that aim to identify the pathways to achieve elimination4.Increasingly malaria researchers are turning to transmission models to predict the impact of control measures on malaria transmission, to focus limited resources toward the most efficient measures of control and to address residual transmission1, and a brief literature survey of vector bionomics was conducted to accompany a series of papers that mapped the ranges of these species9. The survey did not show the proportion of a species showing a particular trait, but instead the proportion of studies reporting the trait for each species. This highlighted two major points. Firstly, a lack of published spatial datasets describing the ecology or behaviour of even the most dominant malaria vectors, and secondly, how much variation in behaviour exists within individual species. A comprehensive search for spatial bionomics data, incorporating behaviour, parasite infection and transmission potential plus other pertinent parameters was therefore conducted (The dominant vector species (DVS) of Africa, the Americas and the Asia-Pacific region have previously been identifiedonducted .The focus of this publication is to present the results of this work; a global, species-specific, temporally and spatially categorised database of the bionomics of the DVS of human malaria.Bionomics data were abstracted from the published literature detailing research studies that included data on:Vector biology; for example parity and longevity;Vector infection and transmission; for example sporozoite rate and entomological inoculation rate;Human biting rate;Vector host preference (quantifiable measures of anthropo- and zoophily);Human biting preference (quantifiable measures of endo- or exophagy);Human biting activity (preferred time of biting);Resting preference (quantifiable measures of endo- or exophily).Regional datasets were created for Africa, the Americas and the Asia-Pacific region within which all data were attributed to species and location. There is no single standard method for measuring each of the above parameters so full details including mosquito collection date, season and sampling method were recorded, where given.8 (date range of field data: 1985–2010). To ensure an up-to-date dataset, additional searches using the DVS specific names as search terms were conducted in PubMed10 and Web of Science11 covering literature published from 2010 to May 2013 for the African DVS and August 2014 for the American and Asia-Pacific DVS. Language restrictions were not placed on these searches. Full text digital copies of all publications were obtained. All articles written in English, French, Portuguese and Spanish were read, and those publications with no useful bionomics data were removed. The decision to only include data collected since 1985 was made to ensure that the dataset reflected the current distribution of the DVS and included specimens identified using more up-to-date identification methods and taxonomy1.Publications detailing occurrence data for the DVS were identified from the MAP DVS databaseAn. gambiae but only relying on morphological identification and with no clear indication whether the specimens were considered An. gambiae species or An. gambiae complex).Each article was searched for relevant bionomics data related to both a given location and to one of the vector species in question. Data were extracted as reported in the source document, with no assumptions made, and only tabulated data or values reported in the text were accepted . When possible, bionomics data for individual sibling species were extracted. However, where there was some ambiguity in the species being reported, they were recorded as the species complex . Where given, we captured full species details, however these use the old molecular form classification. Therefore, consider all mentions of An. gambiae to include An. coluzzii and An. gambiae unless specifically stated otherwise. Our dataset also records the previous classification of chromosomal form, where given. On occasion, despite conducting additional identifications to determine sibling species, authors presented their bionomics data for the species complex, this was also recorded as given.In 2013 the Where possible all data reported in the source for a specific location, time and species are combined on a single data line. For example, this means there may be information relating to a vector population’s host preference, sporozoite infection rate and peak biting time all combined on a single row. However, as not all bionomics parameters were reported by every study this also means that there are blank cells on each row. Blanks cells always represent ‘no data’.Where given, season was recorded. Due to the high influence of season on mosquito behaviour and abundance, when it was not provided it was calculated from the dates given, either in the source or by searching for information detailing when the rainy and dry seasons normally occurred in the specific location. When season has been calculated this is recorded in a separate column, so that users of the dataset are aware that this was not included in the original data source.For the African dataset a search of the accumulated bionomics library was conducted to identify those authors who were most prolific in publishing pertinent bionomics data. These authors were contacted to ask if they had any further, unpublished data they would be able to contribute. Any unpublished data was added into the dataset as above. Authors were also contacted to clarify details that were unclear or to disaggregate data where the source suggested more detail may have been collected in the study, but had not been presented within the published source. Due to time constraints this step was not carried out for the American and Asia-Pacific datasets.9. All additional sites were georeferenced following the same protocol, fully detailed in Hay et al1. In brief, site location was determined by searching for the site name in online gazetteers  or other geolocational resources . Site related contextual information provided in the original reference  was used to confirm that the correct site had been identified. Data locations were attributed to area types, including point locations (within 10 km2), wide areas (10–25 km2), small polygons (25–100 km2) or large polygons (>100 km2). Single sampling points were identified as point locations. However, data were often reported for several sampling sites combined. In this case, sampling locations were determined as a wide areas, small polygons or large polygons depending on the extent of the sampling area. A single set of coordinates for the most central sampling site of the study are used to define the location of the sampling area, with the area type used to give an indication of the geographic spread of the sampling locations.The majority of sites sampled had previously been geolocated in an earlier study mapping the ranges of the DVSWe define a data record as a data point for a unique site-date-species combination. 13 and the VecNet digital library14. Each survey included in the vector bionomics database has been disaggregated to individual sites , individual dates (if the same site was sampled repeatedly) and individual Anopheles DVS. Values were extracted to a database with the following fields:The three regional databases are publicly available online as comma delimited files (Data Citation 1). The data are also available via the Malaria Atlas Project (MAP) websiteSource_ID. Unique source identifier.Country. Country where the study was conducted.Site. Site name.Lat. Latitude in decimal degrees.Long. Longitude in decimal degrees.Area_type. Point (within 10 km2), wide area (10–25 km2), small polygon (25–100 km2) or large polygon (>100 km2).Insecticide_control. Indicates whether insecticide based control methods are in place (previously implemented or implemented as part of the referenced study) at the specified location and time period.T: TRUE.F: FALSE.blank if unknown.Control_type. If ‘TRUE’ above, details the insecticide control method.ITN: insecticide treated nets.IRS: indoor residual spraying.IT curtains: insecticide treated curtains.Coil: coil.Combination: more than one control method used.?: not stated.Month_start. Survey start month.Month_end. Survey end month.Year_start. Survey start year.Year_end. Survey end year.Season_given. Rainy or dry season at the time of the survey, as indicated in the source.Season_calc. Rainy or dry season at the time of the survey, as derived from information on the general seasonal timings provided from the source or elsewhere.Species. The Anopheles species, species complex or subgroup. Also includes molecular form or chromosomal form if reported.ASSI. Additional species-specific information given in the source and provided as a free text field.Id_1. The method used to identify species.Chromosome banding: banding patterns on chromosomes.Cyto: cytological=cell/chromosomal characteristics.DNA: other DNA probing methods without PCR.M: morphological.Palpal ratio: palpal ratio.PCR: Polymerase Chain Reaction amplification techniques.Polytene chromosome: banding patterns on polytene chromosomes.PCR/DNA: PCR combined with DNA probe.Blank: unknown or unreported identification method.Id_2. The second method used to identify species, using same options as above.Biology_sampling_1. The sampling methods used to collect the specimens detailed in the VECTOR BIOLOGY section. Three methods can be listed. If more than three methods have been used, this is indicated as ‘t’ in the final column.MBI: Human biting indoorsMBO: Human biting outdoorsMB: Human biting (location not specified)ABI: Animal biting indoorsABO: Animal biting outdoorsAB: Animal biting (location not specified)HRI: House resting indoorsILT: Indoor light trapOLT: Outdoor light trapRO: Resting outdoors RO (pit): Resting outdoors in pitsRO (shelter): Resting outdoors in a shelterRO (ani-shelter): Resting outdoors in an animal shelterWinExit: Window exit trapsHBN: Human baited netABN: Animal baited netOdour-trap: Odour trapTent trap: Tent trapCol. Curtains: Colombian curtains?: Sampling method not specifiedBiology_sampling_2. As ‘Biology_sampling_1’.Biology_sampling_3. As ‘Biology_sampling_1’.Biology_sampling_n. ‘t’ indicates that there are more than three sampling methods.Parity_n. The number of parous females detected from the total number examined.Parity_total. The total number of females examined for parity.Parity_percent. The percentage of parous females in the sample: number of parous females/total number examined*100.Daily_survival_rate_percent. The estimated proportion of female mosquitoes alive on day d that are still alive on day d+1.Fecundity. The number of eggs laid per batch.Gonotrophic_cycle_days. The number of days for a female mosquito to go through the reproduce-feeding cycle.Infection_sampling_1. The sampling methods used to collect the specimens detailed in the VECTOR INFECTION RATE section. Three methods can be listed. If more than three methods have been used, this is indicated as ‘t’ in the final column. As ‘Biology_sampling_1’.Infection_sampling_2. As ‘Infection_sampling_1’.Infection_sampling_3. As ‘Infection_sampling_1’.Infection_sampling_n. ‘t’ indicates that there are more than three sampling methods.SR_dissection_n. The number of sporozoite infected females detected by dissection from the total number examined.SR_dissection _total. The total number of females dissected for sporozoites.SR_dissection_percent. The percentage of sporozoite infected females detected by dissection in the sample: number of infected females/total number examined*100.SR_CSP_n. The number of sporozoite infected females detected by circumsporozoite protein (CSP) analysis from the total number examined.SR_CSP_Pf_n. The number of P. falciparum specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_n. The number of P. vivax (variant not stated or combined) specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_210_n. The number of P. vivax variant 210 specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_247_n. The number of P. vivax variant 247 specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pm_n. The number of P. malariae specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Po_n. The number of P. ovale specific sporozoite infected females detected by CSP analysis from the total number examined. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_total. The total number of females analysed for CSP.SR_CSP_percent. The percentage of sporozoite infected females detected by CSP analysis in the sample: number of infected females/total number analysed*100.SR_CSP_Pf_percent. The percentage of P. falciparum specific sporozoite infected females detected by CSP analysis in the sample: number of P. falciparum specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_percent. The percentage of P. vivax (variant not stated or combined) specific sporozoite infected females detected by CSP analysis in the sample: number of P. vivax specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_210_percent.The percentage of P. vivax variant 210 specific sporozoite infected females detected by CSP analysis in the sample: number of P. vivax variant 210 specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pv_247_percent.The percentage of P. vivax variant 247 specific sporozoite infected females detected by CSP analysis in the sample: number of P. vivax variant 247 specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Pm_percent. The percentage of P. malariae specific sporozoite infected females detected by CSP analysis in the sample: number of P. malariae specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.SR_CSP_Po_percent. The percentage of P. ovale specific sporozoite infected females detected by CSP analysis in the sample: number of P. ovale specific infected females/total number analysed*100. This field is only included for the Americas and the Asia-Pacific region.Oocyst_n. The number of oocyst infected females detected from the total number examined.Oocyst_total. The total number of females examined for oocysts.Oocyst_percent. The percentage of oocyst infected females detected in the sample: number of infected females/total number examined*100.EIR. The entomological inoculation rate. This is the number of infective bites per person per unit time.EIR_period. The unit of time relating to the EIR.Ext_incubation_period_days. The extrinsic incubation period of the malaria parasite in days.Indoor_HBR_sampling. The sampling method used to collect the mosquitoes from which indoor human biting rate is evaluated. As ‘Biology_sampling_1’.Indoor HBR. The indoor human biting rate; the number of bites per person per unit time.Outdoor_HBR_sampling. The sampling method used to collect the mosquitoes from which outdoor human biting rate is evaluated. As ‘Biology_sampling_1’.Outdoor HBR. The outdoor human biting rate; the number of bites per person per unit time.Combined_HBR_sampling_1. The sampling methods used to collect the mosquitoes from which human biting rate is evaluated where data are amalgamated from more than one method . Three methods can be listed. If more than three methods have been used, this is indicated as ‘t’ in the final column. As ‘Biology_sampling_1’.Combined_HBR_sampling_2. As ‘Combined_HBR_sampling_1’.Combined_HBR_sampling_3. As ‘Combined_HBR_sampling_1’.Combined_HBR_sampling_n. ‘t’ indicates that there are more than three sampling methods.Combined_HBR. The human biting rate evaluated from the data from amalgamated sampling methods.HBR_unit. The unit time for the HBR data.Indoor_host_sampling. The indoor sampling method used to collect the mosquitoes from which indoor host preference is evaluated. As ‘Biology_sampling_1’.Indoor_host_n. The number of mosquitoes positively indicating a measure of host preference from the total number collected indoors.Indoor_host_total. The total number of mosquitoes sampled indoors examined for measures of host preference.Indoor host. The measure of host preference from indoor sampled mosquitoes.Outdoor_host_sampling. The outdoor sampling method used to collect the mosquitoes from which outdoor host preference is evaluated. As ‘Biology_sampling_1’.Outdoor_host_n. The number of mosquitoes positively indicating a measure of host preference from the total number collected outdoors.Outdoor_host_total. The total number of mosquitoes sampled outdoors examined for measures of host preference.Outdoor host. The measure of host preference from outdoor sampled mosquitoes.Combined_host_sampling_1. The sampling methods used to collect the mosquitoes from which host preference is evaluated where data are amalgamated from more than one method, or where the method used is unclear. Three methods can be listed. If more than three methods have been used, this is indicated as ‘t’ in the final column. As ‘Biology_sampling_1’.Combined_host_sampling_2. As ‘Combined_host_sampling_1’.Combined_host_sampling_3. As ‘Combined_host_sampling_1’.Combined_host_sampling_n. ‘t’ indicates that there are more than three sampling methods.Combined_host_n. The number of mosquitoes positively indicating a measure of host preference collected by a combination of sampling methods.Combined_host_total. The total number of mosquitoes sampled by a combination of sampling methods, examined for measures of host preference.Combined_host. The measure of host preference from mosquitoes sampled by a combination of methods.Host_unit. Indicates the measure used to identify host preference.HBI (%): Human Blood Index as a percentage.ABI (%): Animal Blood Index as a percentage.HBI : Human Blood Index as a percentage calculated from data given in source.ABI : Animal Blood Index as a percentage calculated from data given in source.AI: ‘Anthropophilic Index’, a measure of attraction to humans not included above, for example % individuals attracted to human baited trap over total collected in both human and cattle baited trap, calculated from count data.NB. the unit ‘HBI ’ and ‘ABI ’ is where the source provides the raw data needed to calculated HBI or ABI but does not actually present these data. The unit indicates that the calculation has been done here.Other_host_sampling_1. The sampling methods used to collect the mosquitoes from which host preference is evaluated where additional data are presented examining host preference. Three methods can be listed. If more than three methods have been used, this is indicated as ‘t’ in the final column. As ‘Biology_sampling_1’.Other_host_sampling_2. As ‘Other_host_sampling_1’.Other_host_sampling_3. As ‘Other_host_sampling_1’.Other_host_sampling_n. ‘t’ indicates that there are more than three sampling methods.Other_host_n. The number of mosquitoes positively indicating a measure of host preference.Other_host_total. The total number of mosquitoes examined for measures of host preference.Other_host. The measure of host preferenceOther_host_unit. As ‘Host_unit’.Indoor_number_sampling_nights_biting. The sampling effort, in number of ‘man nights’, to collect the indoor biting data.Indoor_biting_sampling. The sampling method used to collect the indoor mosquitoes from which biting location preference is determined. As ‘Biology_sampling_1’.Indoor_biting_n. The number of mosquitoes found biting indoors.Indoor_biting_total. The total number of indoor and outdoor biting mosquitoes.Indoor_biting. The percentage or ratio of mosquitoes found biting indoors.Outdoor_number_sampling_nights_biting. The sampling effort, in number of ‘man nights’, to collect the outdoor biting data.Outdoor_biting_sampling. The sampling method used to collect the outdoor mosquitoes from which biting location preference is determined. As ‘Biology_sampling_1’.Outdoor_biting_n. The number of mosquitoes found biting outdoors.Outdoor_biting_total. The total number of indoor and outdoor biting mosquitoes.Outdoor_biting. The percentage or ratio of mosquitoes found biting outdoors.Indoor_outdoor_biting_units. Indicates the data unit for the indoor and outdoor biting data.I:O: Indoor to outdoor ratio.%: % biting indoors (or outdoors) given in source.%calc: % biting indoors (or outdoors) calculated from data given in source.NB. the unit ‘%calc’ is where the source provides the raw data for indoor and outdoor biting densities but does not calculate the percentage indoors/outdoors. The unit indicates that the calculation has been done here.Indoor_number_sampling_nights_biting_activity. The sampling effort, in number of ‘man nights’, relevant to indoor biting activity data.Indoor_1830_2130. ‘t’ given here if indoor biting activity peaks in the first quarter of the night, includes dusk biting.Indoor_2130_0030. ‘t’ given here if indoor biting activity peaks in the second quarter of the night.Indoor_0030_0330. ‘t’ given here if indoor biting activity peaks in the third quarter of the night.Indoor_0330_0630. ‘t’ given here if indoor biting activity peaks in the fourth quarter of the night, includes dawn biting.Outdoor_number_sampling_nights_biting_activity. The sampling effort, in number of ‘man nights’, relevant to outdoor biting activity data.Outdoor_1830_2130. ‘t’ given here if outdoor biting activity peaks in the first quarter of the night, includes dusk biting.Outdoor_2130_0030. ‘t’ given here if outdoor biting activity peaks in the second quarter of the night.Outdoor_0030_0330. ‘t’ given here if outdoor biting activity peaks in the third quarter of the night.Outdoor_0330_0630. ‘t’ given here if outdoor biting activity peaks in the fourth quarter of the night, includes dawn biting.Combined_number_sampling_nights_biting_activity. The sampling effort, in number of ‘man nights’, relevant to biting activity data where data are presented for both indoor and outdoor biting combined.Combined_1830_2130. ‘t’ given here if combined biting activity peaks in the first quarter of the night, includes dusk biting.Combined_2130_0030. ‘t’ given here if combined biting activity peaks in the second quarter of the night.Combined_0030_0330. ‘t’ given here if combined biting activity peaks in the third quarter of the night.Combined_0330_0630. ‘t’ given here if combined biting activity peaks in the fourth quarter of the night, includes dawn biting.Indoor_resting_sampling. Indoor sampling method used to collect the mosquitoes to assess indoor resting behaviour. As ‘Biology_sampling_1’.Indoor_unfed. Total number of unfed mosquitoes in the sample collected indoors.Indoor_fed. Total number of fed mosquitoes in the sample collected indoors.Indoor_gravid. Total number of gravid mosquitoes in the sample collected indoors.Indoor_total. Total number of mosquitoes in the sample collected indoors, including unfed, fed and gravid females.Outdoor_resting_sampling. Outdoor sampling method used to collect the mosquitoes to assess outdoor resting behaviour. As ‘Biology_sampling_1’.Outdoor_unfed. Total number of unfed mosquitoes in the sample collected outdoors.Outdoor_fed. Total number of fed mosquitoes in the sample collected outdoors.Outdoor_gravid. Total number of gravid mosquitoes in the sample collected outdoors.Outdoor_total. Total number of mosquitoes in the sample collected outdoors, including unfed, fed and gravid females.Other_resting_sampling. Sampling methods relevant to ‘other’ data. These columns are used when additional sampling is reported, for example if indoor and outdoor resting mosquitoes are listed in the previous sections, but the source also reports data from a third sampling method such as mosquitoes resting in animal sheds. As ‘Biology_sampling_1’.Other_unfed. Total number of unfed mosquitoes in the sample collected by additional/‘other’ methods.Other_fed. Total number of fed mosquitoes in the sample collected by additional/‘other’ methods.Other_gravid. Total number of gravid mosquitoes in the sample collected by additional/‘other’ methods.Other_total. Total number of mosquitoes in the sample collected by additional/‘other’ methods, including unfed, fed and gravid females.Resting_unit. The unit relating to the indoor, outdoor or other resting data.Count: raw count data.%: percentage.Per man hour: total number collected divided by time spent collecting in hours.Fed:gravid: fed to gravid ratio, total number of fed specimens divided by total number of gravid specimens.Citation. The data source.PubMed_ID. PubMed ID, when available.Bionomics data have been recorded by a large number of researchers, often using different sampling methods and reporting the data using different metrics. Due to the complicated and non-standard nature of the data, all data were reviewed and checked by a second data abstractor. The data were also checked to ensure that recorded values were within the possible ranges (for example between 0 and 100 for parameters recorded as percentages) and that all values had associated units.16 and vector occurrence9 the geolocation coordinates for these sites had already been confirmed. Coordinates were also plotted to ensure that they fall on land and in the correct country.To ensure all locations were accurately geo-located these were again confirmed by a second data abstractor. As many of the data sources identified in this project had previously been included in mapping projects on parasite rateThis is the first time that a comprehensive global database has been compiled of published bionomics data for the DVS of human malaria. The dataset described here will be of value to researchers when assessing the likely impact of vector control measures on malaria transmission and to policy makers when deciding how malaria control resources are allocated. Searching the dataset for data related to a specific DVS, geographic location or bionomic parameter will allow the user to quickly identify the available data, and to link this back to the original data source. In addition, this dataset can be used to identify the current knowledge gaps in the behaviour and life history characteristics of the DVS across their geographic ranges.The published studies did not use consistent units for each of the parameters of interest, and no attempt has been made to standardise the units as part of this work. It is vitally important that the values for each parameter are not treated as single dataset that used a common methodology and unit. Users are strongly advised to examine the sampling methods and units fields provided for each parameter when making use of the data.We will be using these data to test specific hypotheses relating to the DVS of Africa, including the presence of an east-west behavioural cline; whether insecticide control has caused a continent-wide non species-specific shift to exophagy amongst previously endophagic species; whether insecticide control has caused a continent-wide non species-specific shift in biting times amongst night biting species; and whether the DVS are really behaviourally flexible, or if the observed plasticity actually relates to different sub-species or sibling species within a complex.How to cite this article: Massey, N.C. et al. A global bionomic database for the dominant vectors of human malaria. Sci. Data 3:160014 doi: 10.1038/sdata.2016.14 (2016).


Damastes. Molecular data include the nuclear genes histone H3 (H3) and 28S ribosomal RNA (28S rRNA), mitochondrial genes cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (16S rRNA) were sequenced via Sanger sequencing by J.A. Gorneau. Life history data were collected in the field and in the lab by L.S. Rayor and include data on age at sexual maturity, lifespan, social classification, egg sac shape, how the egg sac is attached or carried, retreat location, retreat modification, retreat size relative to adult female body size, approximate mean body mass, and mean cephalothorax width. Morphological data on Deleninae and one Damastes sp. were scored by C.A. Rheims and includes information on the following characters: prosoma , anterior median eye (AME) diameter, AME-AME and PME-PME interdistances), male palp (embolic sclerite (PS), conductor sclerotized base (SB), tegular apophysis (TA), flange (f)) and female epigyne and vulva , spermathecal sacs (SS)). These data were used to clarify relationships among the Australian endemic Deleninae, as well as global patterns in sparassid evolution. The data demonstrate phylogenetic patterns in life history, social evolution, and natural history among the sparassids. These data contribute to future comparative research on sparassid systematics, evolution, and behavior. This data article complements a research article published in Molecular Phylogenetics and Evolution This article on biodiversity and life history data in huntsman spiders (Araneae: Sparassidae) includes the following: molecular data deposited on GenBank for 72 individuals representing 27 species in seven subfamilies, life history and behavioral data on 40 huntsman species from over two decades of observations, and morphological data for 26 species in the subfamily Deleninae as well as an undescribed representative of the genus  Specifications Table•While focused molecular investigations and life history  datasets are not uncommon, providing an integrated dataset with both molecular and life history data allows for examination of trends in the context of evolution.•These data will be of particular use to arachnologists, evolutionary biologists, systematists, behavioral ecologists, and biogeographers looking to explore trends in comparative social evolution and life history, morphology, and more generally, the evolution of the Sparassidae and Australian endemism.•Molecular data deposited in GenBank will be available for future studies of molecular evolution and phylogenetic analyses, as well as for species-based identification using the barcode gene cytochrome c oxidase subunit I (COI).•Voucher exemplar specimens for molecular, morphological, and behavioral data are deposited in museums for replicability and additional analysis, including sequencing of additional loci in the future.•Morphological and behavioral data will inform individuals designing their own character matrices for members of the Sparassidae, as well as provide a basis from which to designate and define certain life history characteristics.•Long-term datasets presenting total evidence character traits are a rich source for researchers to design their own character matrices for comparative study.1These data present a detailed compilation of molecular, morphological, life history, and behavioral character states for representatives of 37 of the 89 genera of Sparassidae, the eleventh-most speciose spider family, and focus on taxa endemic to Australia. We provide tables including accession numbers for sequences contributed to GenBank, morphological and life history character matrices, and input files and code for each analysis. We also include R code in R Markdown (.Rmd) format for the phylogenetic comparative methods used in Gorneau et al. 22.1Primers_and_PCR_protocols.xlsx — Excel file with information on primers used in this study. C1-N-2776 was used for samples for which the HCO/LCO combination of primers did not amplify adequate DNA. Second sheet of file includes information on PCR protocols used.Voucher_information.xlsx — Excel file with information on vouchers representing exemplars for the molecular data  contributed in this study. Specimens deposited in the National Museum of Natural History  arachnology collections.New_data_generated_GenBank.xlsx — Excel file that corresponds to GenBank_sequences.xlsx — Excel file with accession numbers for sequences downloaded from GenBank.2.2IQTREE_Sparassidae_10_Nov_2021.phy — Input file for IQ-TREE inference containing concatenated alignment for all four gene sequences of taxa used in this analysis.IQTREE_partition.nex — Input NEXUS file for IQ-TREE inference containing details on partitioning of four genes in concatenated dataset IQTREE_Sparassidae_10_Nov_2021.phy.IQTREE_10_Nov_2021.log — Output .log file for IQ-TREE inference containing details of run progress and models of molecular evolution selected.IQTREE_10_Nov_2021.contree — Output IQ-TREE phylogeny with results of 10,000 ultrafast bootstrap replicates as nodal support values.2.3RAxML_Sparassidae_10_November.phy.raxml.startTree — Starting tree as inferred by IQ-TREE. The same tree file as IQTREE_10_Nov_2021.contree.RAxML_22_Nov_2021_partition.txt — inference containing details on partitioning of four genes in concatenated dataset.RAxML_Sparassidae_10_Nov_2021.phy — Input file for RAxML inference containing concatenated alignment for all four gene sequences of taxa used in this analysis.RAxML_Sparassidae_10_Nov_2021.raxml.log — Output .log file for RAxML inference containing details of run progress and models of molecular evolution selected.RAxML_Sparassidae_10_Nov_2021.raxml.bestTree — Best maximum likelihood tree as inferred by RAxML with bootstrap values as nodal support values.2.4MrBayes_21_Dec_2021.nex — Input NEXUS file for MrBayes inference with concatenated dataset of four genes, MrBayes block with information about sequence partitions and models used, as well as IQ-TREE phylogeny used as starting tree.MrBayes_21_Dec_2021_stout.txt — Output file with information on MrBayes run including average standard deviation of split frequencies for duration of run.MrBayes_21_Dec_2021.tre — Bayesian inference phylogeny output of MrBayes with posterior probability values as nodal support values.2.5Tree_convergence_huntsman.Rmd — R Markdown file with code to analyze convergence between IQ-TREE inferences and MrBayes and RAxML inferences. Employs the use of the phytools R package.2.6BEAST_28_Jan_2022_mono.xml — Input file for BEAST 2.6.0 containing information about priors for divergence dating including models of molecular evolution and fossil outgroup calibrations. This file was run independently three times through BEAST to generate three independent .log and files that were then combined into BEAST_28_Jan_2022_combined_runs_123.log in the program LogCombiner.BEAST_28_Jan_2022_combined_runs_123.log — The combined .log files for the three independent runs of BEAST. Contains information about effective sample sizes to determine the quality of the run in BEAST 2.6.0. Examined using Tracer v.1.7.1BEAST_28_Jan_combined_123_TA_25.tre — Maximum clade credibility tree from three independent BEAST runs identified by TreeAnnotator, with input merged .trees files from three runs and burn-in percentage 25%. Node heights set at keep target heights.2.7Life_history_data.xlsx — Excel file containing two spreadsheets: one named Character_States with information about character states for nine life history characters, and one named Character_Matrix with character matrix of life history attributes.lh_matrix.csv — .csv file with same character matrix from Life_history_data.xlsx Excel file, for use in stochastic character mapping and D-test code in Stochastic_character_mapping_and_D-test_huntsman.Rmd.lifeHistorysubName.csv — .csv file with substitutions of names from IQ-TREE phylogeny tip labels to names for stochastic character mapping; essentially removes specific identifiers for ease of visualization in Stochastic_character_mapping_and_D-test_huntsman.Rmd code.Stochastic_character_mapping_and_D-test_huntsman.Rmd — R Markdown file containing code for stochastic character mapping of life history and D-test correlation analysis. Requires the use of the following R packages: corHMM, phylotools, and phytools. Also available on GitHub.Stochastic_character_mapping_model_selection.csv — .csv file with output of model selection including Akaike information criterion (AIC) values from Stochastic_character_mapping_and_D-test_huntsman.Rmd code among the following models: equal rates (ER), symmetric (SYM), and all rates different (ARD) for all life history characters.D_test_p_values.xlsx — Excel file with output partitioned by individual sheet showing the p-values of the D-test analysis in a pairwise matrix. The numeric codes for character states correspond to the following file: Life_history_data.xlsx.Stochastic_character_mapping_posterior_probabilities.xlsx — Posterior probabilities of stochastic character mapping analyses organized by character and then by individual node. Node numbers correspond to Stochastic_character_mapping_w_node_numbers.Stochastic_character_mapping_w_node_numbers.pdf — PDF file with results of stochastic character mapping analyses with node numbers so Stochastic_character_mapping_posterior_probabilities.xlsx can be consulted to examine specific posterior probabilities for specific life history characters by node.2.8Morphology_data.xlsx — Excel file with four sheets: Character_States describing the characters and character states in the Character_Matrix sheet; the Character_Matrix sheet, which is the basis for the input file morpho_matrix.csv; Morphological_Vouchers sheet with information on specimens directly examined for morphological character scoring; and Morpohology_From_Literature for species scored with the use of literature, either instead of direct examination or in tandem with direct observation.morpho_matrix.csv — .csv file of character matrix from Morphology_data.xlsx slightly altered such that the questionable characters were marked as the characters they are likely to be for ease of plotting using the code in Morphology_huntsman.Rmd. The uncertainty was then readded in Adobe Illustrator.morphosubName.csv — .csv file with substitutions of names from IQ-TREE phylogeny tip labels to names for mapping of morphological data matrix from morpho_matrix.csv; essentially removes the specific identifiers for ease of visualization in Stochastic_character_mapping_and_D-test_huntsman.Rmd code.Morphology_huntsman.Rmd — R Markdown file containing code for mapping data matrix of morphological data Deleninae + Damastes. Input files: morpho_matrix.csv, morphosubName.csv, IQTREE_10_Nov_2021.contree. Employs the use of the following packages: corHMM, phylotools, phytools, and RColorBrewer. Also available on GitHub.Male_genitalia.tif – Male, left palp, ventral view. A: Beregama cordata . B: Delena cancerides Walckenaer, 1837. C: Holconia flindersi Hirst, 1991. D: Isopeda villosa L. Koch, 1875. E: Isopedella leai . F: Neosparassus salacius . G: Pediana regina . H: Typostola barbata . I: Zachria flavicoma L. Koch, 1875. Scale lines: 1 mm. F = tegular flange; PS = palpal embolic sclerite; SB = conductor sclerotized base; TA = Deleninae tegular apophysisFemale_genitalia.tif – Female, genitalia. A–B: Delena cancerides Walckenaer, 1837 . C–D: Holconia flindersi Hirst, 1991 . E–F: Isopeda villosa L. Koch, 1875 . G–H: Isopedella conspersa  . I–J: Isopedella leai  . K–L: Pediana regina  . M–N: Typostola barbata  . O–P: Zachria flavicoma L. Koch, 1875 . Scale lines: 1 mm. ES = epigynal sclerite; SS = spermathecal sac.33.1Gryllodes sigillatus and Acheta domesticus), houseflies (Musca domestica), calliphorid flies , and fruit flies (Drosophila spp.). A table with specimen information and voucher information for exemplars of molecular work is included in the Zenodo dataset (Voucher_information.xlsx). Legs  from individuals were stored in ethanol and placed in a -20°C freezer prior to DNA extraction.Behavior and life history traits for each species were observed in the field and/or laboratory. Spiders were fed a diet of crickets (3.2Primers_and_PCR_protocols.xlsx). PCR products were visualized using gel electrophoresis on a 1% agarose gel with 2 ml of DNA and 2 ml GelRed dye under a BioRad UV transilluminator and imaged using the ImageLab™ software . PCR products were purified using ExoSAP-IT  to remove remaining primers and dNTPs. Purified PCR samples were quantified using a Qubit 4 fluorometer  and Biotium High Sensitivity AccuGreen dye  to determine the quantity of DNA after purification and immediately prior to sequencing. Samples were cycle-sequenced in the forward and reverse directions and diluted based on the DNA concentration for full-service (post-PCR purification) sequencing at the Cornell Genomics Facility .A total of 54 samples were extracted in fall 2019 by JAG using the QIAGEN DNeasy PowerSoil Kit . A single adult leg or whole bodies of immatures were used for DNA extraction. An additional 30 samples were extracted by Dr. Ingi Agnarsson's lab group at the University of Vermont using the QIAGEN DNeasy Tissue Kit . DNA from these extractions was then amplified using polymerase chain reaction (PCR) on a BioRad 96-well C1000 Touch Thermal Cycler  for two mitochondrial genes (cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (16S rRNA) and two nuclear genes (histone H3 (H3) and 28S ribosomal RNA (28S rRNA). In short, PCR reactions involved 6.5 mL water, 12.5 mL EconoTaq® PLUS Master Mix , 2.5 mL each of forward and reverse primer (10 mM), and 1 mL of DNA for each 25 mL reaction. The primers used for each gene in this study, and PCR conditions for each gene can be found in the Zenodo dataset (3.3GenBank_sequences.xlsx).In addition, sequences for a total of 201 samples were downloaded from GenBank , Uloborus diversus Marx 1898 ), Oecobius Blackwall 1862 (Oecobiidae), Uroctea durandi ((Latreille 1809); Oecobiidae), Peucetia viridans ((Hentz 1832); Oxyopidae), Dolomedes tenebrosus Hentz 1844 (Pisauridae), Salticus scenicus , Selenops muehlmannorum Jäger & Praxaysombath 2011 (Selenopidae), and Tibellus chamberlini Gertsch 1933 (Thomisidae). The IQ-TREE inference was used as a starting tree for inferences in RAxML and MrBayes with the concatenated sequences partititioned by gene to see if the tree topologies were comparable Aligned sequences were partitioned and exported from Mesquite in .phy format for analysis in IQ-TREE version 1.6.12 3.6Zamilia aculeopectens Wunderlich 2015 (Oecobiidae) for the node representing Oecobiidae, Oxyopes succini Petrunkevitch 1958 (Oxyopidae) for Oxyopidae + Pisauridae, Almolinus ligula Wunderlich 2004  for the node containing the outgroups Salticidae + Thomisidae, and ‘Selenops’ sp. indet. Wunderlich 1988 (Selenopidae) for the node with outgroups Selenopidae sister to Salticidae + Thomisidae Zamilia aculeopectens, an exponential distribution was set with an offset of 98.17 and a mean of 0.32. For Oxyopes succini and Almolinus ligula, an exponential distribution was set with an offset of 43.0 my, and a mean of 1.3. For ‘Selenops’ sp. indet., an exponential distribution was set with an offset of 53.0 my, and a mean of 0.8. As such, these analyses were conducted in accordance with the latest work on fossil calibration of phylogenies by Magalhães et al. An estimation of divergence time was conducted in BEAST using fossil calibrations recommended for use by Magalhães et al. 3.7Life_history_data.xlsx).From 2002 – 2021, LSR collected life history and behavioral data from 40 sparassid species, with emphasis on the endemic Australian Deleninae. Data was collected in the field  and in her laboratory at Cornell University (USA). Life history variables included: mother-offspring dynamics and sociality, egg sac structure, how the egg sac was attached to the retreat or carried, retreat type, modifications to the retreat, adult female body mass and cephalothorax width, age at sexual maturity, and lifespan. These character states are outlined in the Zenodo dataset , ‘subsocial’ species dispersed between four – five weeks (third or fourth instar), ‘prolonged subsocial’ species remained in mother-offspring groups for five to twelve months  prior to dispersing.Three types of egg sacs were observed in the species studied: ‘plastered’ with a ground sheet silked onto the substrate and the rest of the sac built onto that attached sheet, a ‘lenticular’ (a relatively flat round disc), and a ‘spherical’  shape. Egg sacs varied in support structure among the sparassids studied: egg sacs were either ‘completely adhered’ to the substrate and immobile, ‘tethered’ by guy-lines of silk and relatively immobile, or actively ‘carried’ by the adult female under her venter. Adhered egg sacs were only accessible on one side, while tethered and carried egg sacs were relatively accessible on both sides. The spiders in this analysis used retreats under tree ‘bark’ or in small hollows in trees, ‘rocks’, in ‘dead foliage’, in ‘living foliage’, or in the open without a retreat (‘in the open’). Modifications included either ‘silk bonds’ whch are repeated short silken swaths that bind the bark/rock/leaves together, effectively limiting access to the retreat, or a small ‘silken cage’ that completely surrounds the female and her egg sac forming a retreat, or ‘none’ in which there was no silk modification of the retreat.Additionally, parameters of body size , age of female at sexual maturity, and average life span in captivity were collected.3.8To investigate the evolution of life history in the context of phylogeny, the inferred IQ-TREE phylogeny tips were trimmed using the keep.tip function in the R package phytools to the 40 species for which life history data as collected by LSR existed 3.9Damastes were tabulated in a matrix. Character scoring was based on direct examination of available specimens , and when unavailable, from literature Male_genitalia.tif). Female epigynes were dissected and illustrated in ventral and dorsal views. In dorsal view illustrations, the hyaline part of the copulatory ducts was omitted .Relevant morphological data for the endemic Australian Deleninae and This work is consistent with the ethical requirements and standards for publication. This study did not include any human subjects, data collected from social media platforms, or animal experiments requiring approval. The authors have no conflict of interest to disclose.Jacob A. Gorneau: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. Linda S. Rayor: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing. Cristina A. Rheims: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – review & editing. Corrie S. Moreau: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.