| No. |
Short Citation
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Year
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Special Name
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Descendant of
| Constructs |
Syntactic Rules
| Semantics |
Focus
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Data Definition
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Data Manipulation
| Remarks | Cause |
Alternative Publications
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Binary Vector
| Expressiveness Values | Partially Redundant Constructs |
| Inherent | New | Citation | Content | Structure | Integrity | Behavior | Application | Domain-Specifics |
Total
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Data Model
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Application
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Domain Specifics
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Conjunctive Concepts
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Linked Concepts
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|
Entity Type
|
Relationship Type
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Value Sets / Attributes
| Invented | Borrowed | Expressiveness | Applicability | Correction | Integration | Implementation | Other | [E1] |
[E2] |
[E3] |
[E4] |
[E5] |
[E6] |
[E7] |
[E8] |
[E9] |
[E10] |
[E11] |
[E12] |
[E13] |
[E14] |
[E15] |
[E16] |
[E17] |
[E18] |
[E19] |
[E20] |
[E21] |
[E22] |
[E23] |
[E24] |
[E25] |
[E26] |
[E27] |
[E28] |
[E29] |
[E30] |
[E31] |
[E32] |
[E33] |
| Adapted | Included | Adapted | Included |
| 1 | (Chen 1976) | 1975 | | | sg: weak | sg: existence dependency, sg/l: mapping (1:N,M:N, 1:1) | sg: key, sg/l: role | | | | | (1) Relationship types connect entity types. (2) Entity types are assigned attributes. (3) Relationship types can be assigned attributes. | formalized | g | e | e | | ERM incorporates ... semantic information about the real world (p. 9),... framework from which the three existing data models may be derived (p. 10). | structure | | | X | | | (Chen 1975) | | 1 | | | | | f | | f | 1 | i | | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | W | |
| 2 | (dos Santos et al. 1980) | 1979 | | (Chen 1976) | r: type | r: type | r: type, sg/l: role | | | type constructors: sum, product, correspondence (theory of data types) | | Different types are connected by a type constructor to form a new type. | formalized | g | | e | reference to (Smith/Smith 1977) | ... expressing the semantic contents and the semantic structure of the data base, ... natural expression of the real world (p. 103). | structure | | | | | | | 1 | 1 | i | | i | | | | | m | f | | | i | | | f | f | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 3 | (Schiffner/Scheuermann 1979) | 1979 | | (Chen 1976) | sg: selector | sg: generalization, aggregation, sg/l: mapping | X | | | | | X | informal | g | l | e | reference to (Smith/Smith 1977) | ...support more abstractions (views) (p. 139). | structure | | | | | | | 1 | 1 | i | | 1 | | 1 | | | 1 | | | a | i | | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | |
| 4 | (Scheuermann et al. 1980) | 1979 | | (Scheuermann/Schiffner 1979) | X | sg: generalization, aggregation, total, weak, sg/l: mapping | X | | | | | X | formalized | g | | e | | ... lack of capabilities to express abstractions (p. 122), the original ERM ... [did] not ...[allow to express] any additional constraints (p. 124). | structure, integrity | | | | | | | 1 | 1 | i | | m | | m | | | 1 | i | a | m | i | | | f | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | S, W | |
| 5 | (Tjoa/Wagner 1980) | 1979 | | (Chen 1976) | X | sg: weak | sg/t: attribute values 'undefined', 'unknown' | | | | | X | formalized | g | e | | | -- | | | | | | | | | m | | | | | m | | i | m | f | | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | W | O |
| 6 | (Atzeni et al. 1983) | 1981 | | (Chen 1976) | X | sg: subset, generalization | sg: key | | | | | X | primarily informal | t | e | l | tool, high level language to express transactions | -- | | | | | (X) | | | | m | i | | f | f | 1 | | | 1 | | | | i | | | f | f | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 7 | (Caldiera/Quitadamo 1983) | 1981 | | (Chen 1976) | sg: weak | sg: generalization, existence dependency, optional | X | | | | | X | formal | g | e | | | -- | | | | | | | | | m | i | | | | 1 | | 0 | 1 | i | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | S, W | H |
| 8 | (De et al. 1983) | 1981 | CR: ConCept Relationship Model | (Chen 1976) | r: concept | r: modeling functions, sg/l: horizontal (logical, causal), vertical (logical, mathematical, part-whole, classificatory) | X | | | | | X | formal | g | | | | ... capture information requirements for various levels of the organizational hierarchy (p. 455). | structure, integrity | | | | | | | | m | i | | | | 1 | | | m | i | | | 1 | | | | | | | | | | | 1 | | | | | | | | | 0.21 | 0.33 | 0.11 | 0.00 | | H |
| 9 | (Dogac/Chen 1983) | 1981 | | X | sg: weak | sg: total, weak, aggregation, generalization, sg/l: mapping | X | | | | | X | informal | g | e | e | | ... include the recent extensions (p. 357). | | | | X | | | | 1 | 1 | i | | | | m | | | 1 | i | a | | i | | | f | f | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | W, S | H |
| 10 | (Klopprogge 1983) | 1981 | TERM (Time-extended ERM) | (Chen 1976) | X | X | sg: key, role, history | | | | | X | formal | t | l | l | | ... allows a general and rigorous treatment of time,... express very general patterns of change (p. 474). | time | | | | | | | | 1 | i | | | | 1 | i | 1 | m | i | | | | | | 1 | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | | H |
| 11 | (Tabourier/Nanci 1983) | 1981 | | (Chen 1976) | X | sg: functional dependency, sg/l: min/max | sg/l: role | | | | | restriction: binary relationship types | formal | g | | | alternative graphic representation: Occurrences structure diagram | Some kinds of integrity constraints cannot be represented (p. 73). ... produce an equivalent model with only "1 to n" binary relationships, without lack of integrity information (p. 97). | integrity | | | | | X | | | 1 | | | | | m | | | 1 | 1 | 1 | | | f | f | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | | |
| 12 | (Webre 1983) | 1981 | | (Scheuermann et al. 1980) | X | sg: existence dependency, mapping class, restriction class, completeness class | X | | | | | X | formalized | g | | | | ... to be a need for mutual existence dependencies (p. 173). ...roles of relationship types ... not clearly defined (p. 174). ...semantic information not being modeled (p. 174). | structure, integrity | | X | | | | | | 1 | m | | | | m | | | 1 | 1 | 1 | | m | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | | |
| 13 | (Al-Fedaghi 1983) | 1983 | | (Scheuermann et al. 1980) | X | sg: generalization | sg: calculated, uninherited, sg/l: key | | | | | Relationships connect attributes (equality). | informal | g | | | alternative representation of generalization hierarchy; analogy to multidimensional data analysis | ... represent particular concepts of the analyzed [petroleum engineering] environment (p. 761) | domain (process industry), structure | | | | | | | 1 | m | i | | | | 1 | | | m | | | | i | 1 | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | S | |
| 14 | (Bertino 1983) | 1983 | | (Chen 1976) | sg: fragmentation | sg: fragmentation | sg: key | | | | | X | formal | g | | | vertical fragmentation corresponds to creating new entity/relationship types | ... represent fragmentation schema (p. 189). | structure | | | | | | | | m | | | 1 | 1 | 1 | | | m | 0 | | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | | |
| 15 | (Lenzerini/Santucci 1983) | 1983 | | (Chen 1976) | sg: generalization, subset | sg: generalization, subset, sg/l: min/max | sg/l: identifier | | | | | Relationships connect relationships (generalization). | formalized | g/t | | | language to specify integrity constraints | ... the problem of expressing cardinality constraints is always an open one (p. 529). | integrity, structure | | X | | | i | | i | m | i | 1 | | | 1 | | | 1 | 1 | 1 | 1 | i | f | f | | | | | | | | | | | | | | | | | | 0.36 | 0.67 | 0.00 | 0.00 | S | |
| 16 | (Nakano 1983) | 1983 | Logic-oriented ER | (Chen 1976) | X | sg: classification, aggregation, generalization, | sg: role | | | | | X | formal | t | | | language to specify integrity constraints | ... describe a conceptual structure, a variety of integrity constraints and high-level queries (p. 551). | structure, integrity | | | | | | | 1 | 1 | i | | 1 | | m | | 1 | 1 | | | | i | 1 | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 17 | (Sakai 1983) | 1983 | | (Chen 1976) | X | X | sg: mulitvalued, compound, identifier | | | | behavior description | X | formal | g/t | e | l | Petri Nets represent behavior of entities and relationships, drawn together with ER diagram | A conceptual schema should contain descriptions of both aspects [structure/behavior], (p. 111). | structure, behavior | | | | | | (Sakai 1984) | | m | | | i | i | 1 | 1 | i | m | | | | | | | 1 | 1 | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | | |
| 18 | (Tabourier 1983) | 1983 | EROS (Entity, Relationship, Occurences Structure) | (Tabourier/Nanci 1983) | r: structure | r: structure, sg:min/max | X | | | | | X | formal | t | | e | language to specify integrity constraints | [ER diagrams] may present a lack of precision (p. 565). | | | X | | (X) | | | | 1 | | | | | m | | | 1 | 1 | 1 | | | 1 | 1 | f | f | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | | |
| 19 | (Elmasri et al. 1985) | 1985 | ECR (Entity-Category-Relationship) | (Chen 1976) | r/sg: category, generalization/subset category | sg/l: min/max-participation, sg: total/partial/functional participation (derived) | sg/l: compound, multivalued, role, d: identifier | | | | | X | formalized | g | e | l | | ... [ER model] not sufficient to represent some important data semantics (p. 77). | structure | | | | | | | | 1 | i | f | f | f | 1 | 1 | f | 1 | 1 | 1 | i | i | 1 | | f | f | | | | | | | | | | | | | | | | 0.48 | 0.89 | 0.00 | 0.00 | S, J, T | |
| 20 | (Ferg 1985) | 1985 | | (Chen 1976) | X | X | sg/l: key | | | | | X | informal | g | e | | ID-dependence on time periods | ... representing the time dimension (p. 280). | time | | | | | | | 1 | m | | | | | 1 | i | i | 1 | i | | | | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | Z | H |
| 21 | (Gilberg 1985) | 1985 | | Information Engineering | sg: subentity | sg: recursive, intersection data groups | X | | | | | X | informal | g | | | separate subschema for each primary entity | [large ER diagrams] proved unreadable (p. 320) | | X | | | | | | | 1 | i | | | | 1 | | | m | i | | | i | | | | | | | | | | | | | | | | | | | | 0.18 | 0.33 | 0.00 | 0.00 | S | H |
| 22 | (Hsu 1985) | 1985 | | (Chen 1976) | sg: semantic, d: weak | sg: semantic, operational (plural, functional, mandatory) | sg: key, role | | | | | X | informal | t | e | | | ... integrating the ... top-down analysis and bottom-up synthesis methodologies (p. 56). | | | | | X | | | | 1 | | | | | 1 | | 1 | 1 | i | | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | W | |
| 23 | (Lenzerini 1985) | 1985 | SERM (Semantic ERM) | | r: category | r: category, sg: subset, part-of, cardinality-ratio | r: category, sg: role | | | | | Subset-relationship connects relationships. | formal | t | | l | | ... integration of the original Entity-Relationship Model and many proposed extensions (p. 271). . ... give a sound foundation to possible implementations of a high-level programming language (p. 272). | | | | X | X | | | i | 1 | i | | | | | | | 1 | 1 | 1 | | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 24 | (Qian/Wiederhold 1985) | 1985 | | | sg: primary, secondary | sg: subtype, association | sg: key, single-/multi-valued, constrained, derived | | | | | X | informal | t | e | | | ... provide syntactic embodiment of semantic data model and a uniform linguistic tool for data definition, query, manipulation (p. 46). | | | | | X | | | 1 | 1 | i | | | | 1 | 1 | 1 | 1 | | | i | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 25 | (Velez 1985) | 1985 | TIGRE | | X | sg: min/max | sg: role, type | | | constructor (programming languages) | | The application of a constructor results in a typ. | informal | t | | l | | The aim ... is to handle multi-media data in an office automation context (p. 82). | domain (multi-media) | | | | X | | | | 1 | i | | | | | | 1 | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | | | | 0.18 | 0.33 | 0.00 | 0.00 | | |
| 26 | (Bruno/Elia 1987) | 1986 | | (Chen 1976) | X | sg: static/dynamic specialization, sg/l: cardinality | X | | | | state, transition | X | informal | g/t | | | | ...[ERM] does not give any information on the behavior of entities (p. 169). .... integrating requirements specification and simulation (p. 169). | behavior | | | | X | | | | m | i | | 1 | | m | i | i | 1 | | | | i | | | 1 | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S, Z | |
| 27 | (Dittrich et al. 1987) | 1986 | CERM (Complex-Entity/Relationship Model) | (Chen 1976) | r: objects, sg: complex objects, c: versions | sg/l: min/max | sg/l: predefined domains | | | | | X | primarily informal | g | e | e | | ... [the ERM] lacks a notion of... [composite] objects and a set of operators capable of dealing with these aspects (p. 422). | structure, time | | | | | | | 1 | 1 | i | | | | m | | f | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 28 | (Eder et al. 1987) | 1986 | BIER (Behavior Integrated E-R) | (Chen 1976) | sg: weak, subentity | sg: generalization | sg/l: surrogate | | | states, activities (Petri nets) | | (1) States are connected to entities.,(2) Activities connect states. | informal | g | | e | Petri Nets represent behavior of entities | .. introduce a general framework ... which includes both static and dynamic aspects ... (p. 147). | behavior, time | | | | | | | | m | i | | | | 1 | i | | m | i | | | i | | | 1 | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | |
| 29 | (Junet 1987) | 1986 | | (Chen 1976) | sg: weak | sg: sub-relation, generic-relation, sg/l: cardinality | sg/l: key, sg: multivalued-role, mandatory/not-mandatory roles | | | | | X | formal | g/t | l | | | ...., the meaning of a role in the original E-R model is not powerful enough to capture some enhanced semantic of the real world (p. 305). | structure | | X | | (X) | | | 1 | 1 | i | | | | 1 | i | f | 1 | i | | | i | | 1 | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | W, S | |
| 30 | (Lipeck/Neumann 1987) | 1986 | | (Chen 1976) | r: objects; sg: complex, generalization, partition; sd: geoobjects, map objects | sg/l: functional | sg/l: identifier | | | | | X | formal | g/t | l | l | | ...[extended ERM] is adapted to geoscientific needs ... (p. 68). | domain (geographic IS) | | | | | | | 1 | m | i | | | | 1 | | 1 | 1 | i | | i | i | | | | | | | | | | | | | | 1 | | | | | | 0.30 | 0.50 | 0.00 | 0.17 | J, T | H |
| 31 | (Teorey et al. 1986) | 1986 | | | sg: weak, subset, generalization | sg: connectivity, membership class | sg/l: identifier, descriptor | | | | | X | informal | g | e | | | ... inadequacy of the initial [ER] modeling constructs (p. 201). | | | X | | | | | | 1 | i | | | | 1 | | | 1 | i | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | W, S | |
| 32 | (Downs 1992) | 1987 | SSADM | | X | sg: optional, exclusive | sg/l: key | | | | | restriction: binary relationship types | informal | g | e | | ERM as a step of SSADM (Structured Systems Analysis and Design Method) | -- | | | | | | | | | 1 | | | | | 1 | | | 1 | i | 1 | 1 | | | | | | | | | | | | | | | | | | | | | 0.18 | 0.33 | 0.00 | 0.00 | | H |
| 33 | (Flory/Giard 1988) | 1987 | | (Chen 1976) | sd: spacio-temporal | sgL: cardinality | sg/l: composite, identifier, role | | | | | X | informal | g | e | | spacio-temporal entity types are generally hidden in ER diagrams | ... [application in manufacturing]... leads to new requirements which are not always matched by conventional systems (p. 249). | domain (manufacturing) | | | | | | | | 1 | | | | | 1 | | f | 1 | i | | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | | H |
| 34 | (Hohenstein et al. 1987) | 1987 | | (Chen 1976) | r: objects, sg/l: complex objects, versions | sg/l: min/max, sg: derived | sg/l: key, role, multivalued, sg/l: optional, derived | integrity boxes, type construction | | | | (1) Integrity boxes are connected to entity types (relationship types, attributes). (2) Different input entity types are connected by type constructors to form separate output entity types [requirements]. | formal | g | l | | | ... [extended ERM] to be suited for the design of standard and non-standard applications ... (p. 59). ... integrate all important semantic concepts of recent semantic data models (p. 64). ... shall form the basis for several database and information systems design tools (p. 59). | structure | | | X | X | | | | 1 | 1 | 1 | | | 1 | 1 | i | 1 | 1 | 1 | i | i | 1 | 1 | f | f | | | | | | | | | | | | | | | | 0.45 | 0.83 | 0.00 | 0.00 | J, T | O |
| 35 | (ISO 1987) | 1987 | ISO | | X | sg/l: min/max, functional dependent | sg/l: identifier | | | | | X | informal | g | l | | | ... providing a framework for the design of conceptual schema languages (p. 2). | | | | X | | | | | 0 | | | | | 1 | | f | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | | |
| 36 | (Lazimy 1988) | 1987 | ERA (Entity-Relationship-Attribute) | (Chen 1976) | X | X | sg: action, sg/l: probabilistic | constraint set, transformation set | | | | Constraint sets and transformation sets connect attributes. | formalized | g | l | | | [new ERM] .. sufficiently rich for representing both transactional and conceptual information (p. 133). | structure, uncertainty | | | | | | | 1 | m | 1 | | | | m | | i | m | | | | | | | | | | | | | | | | | | | | | | | | 0.18 | 0.33 | 0.00 | 0.00 | | F |
| 37 | (Kappel/Schrefl 1989) | 1988 | | BIER | rf: BIER | rf: BIER | rf: BIER | complex activities | | | | Complex activities connect states. | informal | g | e | | | ... [new ERM] considers the structural as well as the behavioral aspects (p. 311). | structure, behavior | | | | | | | | m | | | | | m | m | | m | m | | | i | | | 1 | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | S | |
| 38 | (Navathe/Pillalamarri 1989) | 1988 | OOER (Object-Oriented ERM) | (Chen 1976) | sg: weak, generalization, specialization, classification | sg: association | sg: key | | | operation (object-orientation) | | Operations are connected to entity types. | informal | g | e | e | | ... enhance ER model to improve its abstraction capability (p. 186). | structure | | | | | | | 1 | m | i | | 1 | | 1 | | f | 1 | i | | a | i | | | f | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | W, S | |
| 39 | (Put 1989) | 1988 | | (Scheuermann et al. 1980) | X | sg: total, weak, aggregation, generalization, sg/l: mapping | X | | action | | | X | formalized | g/t | | l | actions are the leaf nodes of sequence diagrams, which are used in addition to ER diagrams, verification of conceptual design | A conceptual schema should include all relevant aspects of the real world, both static and dynamic (p. 423). | behavior | | | | | | | 1 | 1 | i | | | | | | | 1 | i | a | | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 40 | (Sinz 1988) | 1988 | SER (Structured ER) | (Chen 1976) | sg: ER-Typ | sg: complexity, subtype-hierarchy, is-a-hierarchy | sg/l: key | | | | | X | informal | g | e | | | ... Verbesserung der semantischen Aussagefähigkeit von ER-Diagrammen (S. 191). ... fünf verbesserungsfähige Schwachstellen des ERM (S. 193). | structure | | X | | | | | | 1 | i | | | | 1 | | | 1 | 1 | 1 | i | i | | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S, J, T | |
| 41 | (Carlson et al. 1990) | 1989 | NER (Nested ER) | (Chen 1976) | sg: complex | sg: complex | sg: complex, key | | | | | X | formalized | g | e | | | [improve] comprehensibility, retrievability, updatability (p. 44). | | X | | | | | | 1 | m | i | 1 | | | 1 | | i | m | | | | i | | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | C |
| 42 | (Davis/Bonnell 1990) | 1989 | EARL | (Chen 1976) | X | sg: IS-A, PART-OF, AGGR-OF, INST-OF, MEMBER-OF, ROLE-OF,sg/l: min/max | sg: identifier | constraint-links | | | | Constraint links connect relationship types. | informal | g | | | | ... capture abstraction relations (p. 95). ... express certain types of cardinality constraints (p. 96). coupling concept abstraction with constraint specification (p. 95). | structure, integrity | | | | (X) | | | 1 | 1 | i | | | | 1 | | | 1 | 1 | 1 | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | | |
| 43 | (Elmasri/Navathe 2000) | 1989 | EER (Enhanced ER) | (Chen 1976) | sg: weak, subclass, superclass, category | sg/l: cardinality, sg: total participation, identifying, disjoint/overlapping total/partial specialization, aggregation | sg: composite, multivalued, derived, key, sg/l: role | | | | | X | formalized | g | e | e | | ... To represent these requirements [of newer applications] as accuratly and clearly as possible.... ... the ER model can be enhanced to include these concepts [of semantic data models] .. (p. 73) | structure | X | | X | | | | 1 | 1 | 1 | | | | 1 | 1 | f | 1 | i | a | i | i | | | | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | W, S, J,T | H |
| 44 | (Embley/Ling 1990) | 1989 | E2R (E-squared-R) | (Chen 1976) | sg: lexical, non-lexical | sg: functionally dependent, participation, union/partition generalization/specialization, sg/l: min/max | sg: composite, sg/l: role | | | | | X | informal | g | e | | normalized EER models | ... capture a wider range of design-dependent real-world semantics (p. 111). ... improved, synergistic database design methodology (p. 111). ... design work cannot be completed in the ER model alone (p. 112). | | | | | X | | | | 1 | i | | | | 1 | 1 | i | 1 | 1 | 1 | i | i | | | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S, J, T | |
| 45 | (Lazimy 1990) | 1989 | E2R (E-squared-R) | (Chen 1976) | X | sg: association, aggregation, class-subclass, membership | sg: derived, objective/goal | functions | | | | (1) Relationships connect attributes. (2) Functions connect attributes. | formalized | t | l | | knowledge-based design | .. a need ... [to] represent semantically-rich knowledge as well as a variety of activities (p. 130). | knowledge | | | | | | | 1 | 1 | 1 | | | | m | | 1 | m | | | a | i | | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | |
| 46 | (Kerschberg et al. 1990) | 1989 | KER (Knowledge-based ER) | (Teorey et al. 1986) | rf (Teorey et al. 1986) | sg: cardinality, min/max | rf (Teorey et al. 1986), sg: cardinality | formulas | | inference rules (knowledge-based systems) | | Formulas and inference rules connect attributes. | informal | t | | l | | There was a ... need to specify rule-based knowledge as well as object-oriented data specifications (p. 256). | knowledge | | | | | | | | m | 1 | | | | 1 | 1 | 1 | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 47 | (Parent/Spaccapietra 1992) | 1989 | ERC+ | | sg: complex objects | sg: optional, min/max, generalization | sg: surrogate key, complex, sg/l: role | | | | | X | formal | g/t | | l | | A richer semantic model [for integration of heterogeneous schemas] was needed (p. 69). ... besides .. expressive power, friendliness was assigned as additional requirement... (p. 69). | structure | X | | | | | | | 1 | i | | | | 1 | | i | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | O, C |
| 48 | (Teorey et al. 1989) | 1989 | | (Teorey et al. 1986) | rf (Teorey et al. 1986) | rf (Teorey et al. 1986), sg: grouping, exclusive | rf (Teorey et al. 1986) | | | | | X | informal | g | e | | | In an ER diagram with 1000 entities [...] the overall structure will probably not be very clear | | X | | | | | | 1 | m | i | | | | m | | | 1 | i | 1 | 1 | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 49 | (Barker 1990) | 1990 | | (Chen 1976) | sg: subtype | sg: cardinality, optional, exclusive, non-transferable | sg: identifier | | | | | restriction: binary relationship types | informal | g | e | | | -- | | | | | | | | | 1 | i | | | | 1 | | f | 1 | i | 1 | 1 | i | | i | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S | H, X |
| 50 | (Brunet et al. 1991) | 1990 | | ERC+ | rf ERc+ | rf ERc+ | rf ERc+ | | | action, event (object orientation) | | (1) Actions are connected to entity types. (2) Events connect actions. | informal | g | e | | | ... for the description of behavioral aspects (p. 211). | behavior | | | | | | | | m | i | | | | 1 | | 1 | m | m | 1 | | i | | | 1 | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 51 | (Elmasri et al. 1991) | 1990 | TEER | (Elmasri/Navathe 2000) | rf (Elmasri/Navathe 2000) | rf (Elmasri/Navathe 2000) | rf (Elmasri/Navathe 2000) | role type | | | | (1) Each role type is associated with a single entity type. (2) Role types can be connected by relationship types. | formal | g | e | l | | .. conventional DBMS lack the power to describe and query information related to time aspects (p.239). | time | | | | | | | m | 1 | 1 | | f | f | 1 | 1 | f | 1 | m | m | m | i | | | | | | | | | | | | | | | | | | | | 0.39 | 0.72 | 0.00 | 0.00 | S | |
| 52 | (Hsu/Rattner 1990) | 1990 | TSER (Two-Stage ER) | (Chen 1976) | X | sg: mandatory, functional | sg: key | | context, subject | | | X | informal | t | e | | focus on system implementation, separate SER and OER diagrams | ... consolidating data structures across the manufacturing facility (p. 758). | | | | | | X | | | 1 | | | | | 1 | | | 1 | | a | | | | | | | | | | | | | | | | | | | | | | 0.12 | 0.22 | 0.00 | 0.00 | | |
| 53 | (Martin 1990) | 1990 | Information Engineering | | sg: subtypes | sg: min/max, exclusive | sg/l: role | | | | | restriction: binary relationship types | informal | g | | | exclusive relationships | | | | | | | | | | 1 | i | | | | | | | 1 | 1 | 1 | 1 | i | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | S | |
| 54 | (Schrefl 1991) | 1990 | | BIER | rf BIER | rf BIER | rf BIER | abstract activities, abstract states | | | | rf BIER | informal | g | | | | [BIER] ... lacks refinement primitives for states and activities (p. 119). | behavior | | X | | | | | | m | | | | | 1 | i | | 1 | i | m | | m | | | 1 | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | | H |
| 55 | (Rochfeld et al. 1991) | 1990 | | (Chen 1976) | X | sg/l: min/max | sg: key | (inclusive/exclusive) functional integrity constraint | | | | Relationships connect relationship types. | primarily informal | g | | | | [remove] ... a modelling constraint (p. 149). | | X | | | | | | 1 | m | | | | | 1 | | | 1 | 1 | 1 | 1 | | | 1 | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | | |
| 56 | (Zhu et al. 1991) | 1990 | HAMMER (Hierarchical Abstraction Mechanism on Models in ER) | | sg: hyperentity | sg: min/max-participation, association, aggregation, hierarchy | sg: roles | model, hypermodel | | | | (1) Entity types and relationship types are connected to models. (2) Hypermodels are connected to models. | formalized | t | e | | | [HAMMER] grew out of the concerns with the complexities associated with large conceptual models (p. 75) | | X | | | | | | 1 | 1 | i | 1 | | | | | 1 | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 57 | (Ferg 1991) | 1991 | | | X | sg: participation cardinality, look across cardinality, generalized cardinality | X | | | | | X | formalized | g | e | | | [certain ER notations] are found not to be capable.. of expressing [...] cardinality constraints (p. 1) | integrity | | | | | | | | 1 | | | | | f | | | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | | |
| 58 | (Gogolla/Hohenstein 1991) | 1991 | EER | different EER | X | sg: min/max,derived, functional | sg: multivalued, optional, derived, components, role, key | type construction | | | | Different input entity types are connected by type constructors to form separate output entity types [requirements]. | formal | t | l | l | | ... concentrating nearly all concepts of ... semantic data-models...., ... provide our extended ER model with a formal mathematical semantics (p. 369) | | | X | X | | | (Engels et al. 1992/93) | i | 1 | 1 | 1 | 1 | 1 | 1 | 1 | i | 1 | 1 | 1 | a | i | 1 | 1 | | | | | | | | | | | | | | | | | | 0.48 | 0.89 | 0.00 | 0.00 | S | O |
| 59 | (Heuser/Peres 1991) | 1991 | ER-T | (Chen 1976), Petri nets | sg: control places | X | X | | | external agents, transaction sets (Petri nets) | | Transaction sets are connected to external agents, control places, entity/relationship types. | informal | g | | | | ... integrated modeling of static and dynamic properties... (p. 247). | behavior | | | | | | | | m | i | | | | m | | f | 1 | | a | | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 60 | (Kouramajian/Elmasri 1991) | 1991 | | TEER (Temporal Extended ER) | sg: weak | sg: superclass/subclass | sg: temporal, multivalued, composite, surrogate key | temporal element | | | | each entity/relationship type is associated with a temporal element | formal | t | l | | | [current DBMS] ... lack the power to describe and query information related to time aspects... ; handle both valid and transaction time (p. 671). | time | | | | | | | m | 1 | i | | m | m | 1 | 1 | i | 1 | i | | | i | | | | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | W, S | c |
| 61 | (Loucopoulos et al. 1991) | 1991 | ERT (ER-Time) | | r: class, sg: time period class, complex object, derived | sg: generalization/specialization, derived, sg/l: cardinality | sg/l: complex, role | | | | | X | formalized | g/t | l | l | | ... capturing and representation of business rules (p. 323). ... the need for expressiveness power of conceptual modelling formalisms... (p. 324). | integrity | | | | | | (Theodoulidis et al. 1991), (Theodoulidis et al. 1992) | 1 | 1 | i | 1 | | | | | i | 1 | 1 | 1 | i | i | f | f | | | | | | | | | | | | | | | | | | 0.36 | 0.67 | 0.00 | 0.00 | S, J, T | D |
| 62 | (Moyne et al. 1991) | 1991 | | (Teorey et al. 1989) | rf (Teorey et al. 1989) | rf (Teorey et al. 1989) | rf (Teorey et al. 1989) | sequential ordered function | | | | Sequential ordered functions connect relationship types. | formalized | g | | e | | ... represent ordering and time sequencing of process recipe information (p. 421). | domain (process industry) | | | | | | | | m | m | | | | m | | | 1 | i | 1 | m | m | | i | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | | H, OR |
| 63 | (Tanaka et al. 1991) | 1991 | ER-R | | X | sg: total participation, sg/l: cardinality | sg/l: key | rule objects | | | | Rule objects are connected to entity types, relationship types or attributes. | informal | g/t | e | l | | ... introduction of active aspects of information systems in the conceptual schema (p. 60). | behavior | | | | | | | | 1 | | | i | i | 1 | | f | 1 | i | a | | | | | 1 | 1 | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | | H |
| 64 | (Tauzovich 1991) | 1991 | TER | | X | sg/l: min/max, optional, snapshot cardinality, lifetime cardinality | X | | | | | X | informal | g | e | | | [current ER approaches] ... ignore time (p. 163) | time | | | | | | | | 1 | | | | | 1 | | | 1 | 1 | 1 | | | | | | | | | | | | | | 1 | | | | | | | | 0.18 | 0.28 | 0.11 | 0.00 | | |
| 65 | (Thalheim 2000) | 1991 | HERM+ | | sg: cluster, weak | sg: min/max | sg: nested, key | integrity constraints, operations, type construction | | | | (1) Relationships connect relationships. (2) Integrity constraints/operations are connected to entity or relationship types. | formal | t | l | l | | [HERM] ... has a strong theoretical basis (p. 9). The modeling is more natural and can be applied in a simple manner (p. 9). The theory is applicable to practical needs (p. 10). The results of the design are much simpler than with other approaches (p. 10). The model is easy to understand, simple and comprehensible (p. 11). The model is capable to support sophisticated database design techniques (p. 11). | | X | X | X | X | | (Thalheim 1999) | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | i | i | 1 | 1 | 1 | 1 | | | | | | | | 1 | | | | | | | | 0.58 | 1.00 | 0.11 | 0.00 | S | |
| 66 | (Wei/Teorey 1991) | 1991 | ORAC | (Teorey et al. 1989) | r: abstract objects | sg: generalization, categorization, aggregation, min/max | r: literal objects, sg: complex, multivalued, surrogate keys, sg/l: role | constraint primitives | | | | Constraint primitives connected to relationship types. | formal | g | | | | ... answer these criticisms [concerning the ER model]... (p. 32). ... humanly intuitive, semantically expressive, and can be mapped into simple mathematical concepts (p. 32). | | X | X | | (X) | | | 1 | 1 | i | | | | 1 | 1 | 1 | 1 | 1 | 1 | 1 | i | | | | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | S | |
| 67 | (Batini et al. 1992) | 1992 | | (Chen 1976) | sg: generalization (sg/l: total/partial, disjoint/overlapping), subset | sg: rings, sg/l: min/max | sg: identifier (external/mixed), composite, sg/l: multi-valued, optional, mandatory | | | | | | formalized | g | l | e | | ... present basic elements and advanced features of the ER model ... (p. 31). | | | | X | | | | | 1 | i | | | | 1 | 1 | f | 1 | 1 | 1 | i | i | | | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S | |
| 68 | (Garcia/Sheng 1992) | 1992 | SEER (Synthesized Extended ER) | (Teorey et al. 1986) | rf (Teorey et al. 1986) | rf (Teorey et al. 1986) | rf (Teorey et al. 1986) | | | | focal objects, transaction access, statistics, procedures (transaction-modeling, frames) | X | informal | g | | | separate diagram | ... formalize the descriptions of distributed transaction information (p. 181). ...., facilitating relational distribution design (p. 181). | behavior | | | | X | | | 1 | 1 | i | | | | 1 | | | 1 | i | 1 | | i | | | 1 | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 69 | (Hainaut 1992) | 1992 | | (Chen 1976) | sd: space | sg/l: min/max, specialization | sg/l: compound, role, optional/mandatory, multivalued, identifier | group | | | | Group connects attributes or roles. | formalized | g | | | | .. extension of the [ER] model to describe main statistical aspects of data (p. 79). | domain (IS planning) | | | | | | | | 1 | i | | | | 1 | 1 | 1 | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | |
| 70 | (Han/Li 1992) | 1992 | | (Chen 1976) | sg: subentity, virtual | sg: generalization, virtual, cardinality | sg: complex, virtual, multivalued, key | | | | | X | informal | t | e | e | | ... design of deductive databases (p. 192). | knowledge | | | | | | | | m | 1 | 1 | | | 1 | 1 | 1 | 1 | | | | i | 1 | 1 | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S | |
| 71 | (Behm/Teorey 1994) | 1993 | | (Chen 1976) | sg: aggregate | sg: subset, sg/l: mapping | s/l: structured, derived | relationship operators, constraints | | | | (1) Relationship operators connect relationship types. (2) Domain-based constraints connect attributes. | informal | g/t | e | | | ... extend the ER model to support these additional business rules and constraints (p. 46) | integrity | | | | | | | | m | 1 | | | | m | | 1 | 1 | 1 | 1 | 1 | i | 1 | 1 | | | | | | | | | | | | | | | | | | 0.33 | 0.61 | 0.00 | 0.00 | S | |
| 72 | (Dijkstra 1994) | 1993 | O2XER (Object Oriented eXtensions to the ERM) | ERC+ | r: objects, sg: complex objects, c: versionable | sg: generalization | sg: complex, multivalued, optional, role | | | | | X | informal | g/t | | | | ... [EER models] lack the support for complex objects, versioning, and slightly explore the aggregation concept (p. 13). | structure, time | | | | | | | 1 | 1 | i | | | | m | 1 | 1 | 1 | m | m | | i | | | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S | |
| 73 | (Garzotto et al. 1994) | 1993 | HDM (Hypertext Design Model) | different EER | sg: derived | r: application web type, sg: derived application web, cardinality, optional | r: unit, sg: component | index, guided tour | | | | Application web types/indexes/guided tours connect entity types, components or application web types. | formalized | t | | | | Goal of HDM is ... the specification of structural and navigational aspects of hypermedia (p. 179). | domain (hypermedia) | | | | | | | | 1 | i | 1 | | | | | 1 | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | | D |
| 74 | (Heuser et al. 1993) | 1993 | | (Batini et al. 1992) | r: entity place | r: relationship place, dead links | r: attribute place | | | live links (Petri nets) | | Live links connect places, transitions, entity types, relationship types. | formal | g | | | ER diagrams are translated into Petri nets. | ... the need also to include dynamic properties (p. 275). ... the semantic of an E-R diagram ... can be expressed in terms of a high-level Petri net (p. 276). | behavior | | | | | | | | m | i | | | | | 1 | 0 | 1 | i | 1 | | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 75 | (NIST 1993) | 1993 | IDEF1X | | sg: identifier-dependent | sg: identifying, non-identifying, optional, mandatory, categorization, cardinality | sg: typed, key, sg/l: role | | | | | X | informal | g | | | | .. support integration (p. i). ...meet the following requirements: .... consistent, extensible, transformable; .. easy for users to grasp, yet powerful and robust; ... teachability; ...be automatable (p. ii). | structure | X | | X | X | X | | | 1 | | | | | 1 | | 1 | 1 | i | 1 | i | | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | | H |
| 76 | (Norrie 1994) | 1993 | | | | sg/l: min/max, sg: is_a | sg: complex | | | | | X | formal | g/t | e | e | | How can [ER and object-oriented modeling] be combined to support the development of database application systems (p. 391)? | | | | | X | | | | m | i | | | | | | 1 | 1 | 1 | 1 | | i | 1 | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | |
| 77 | (Pernul et al. 1994) | 1993 | | extended ER | sd: security object | r: security object, sg/l: cardinality | sg: identifier | security constraints | | | | Security constraints connect attributes. | formal | g/t | e | l | | ... capture security semantics (p. 166). | domain (security) | | | | | | | | m | i | | | | 1 | | f | 1 | i | | | i | 1 | 1 | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 78 | (Winter 1994) | 1993 | | | sd: derived | sg: existential dependency, aggregation, generalization, cardinality | sg: key | | | | | X | informal | t | | | | ... allow an utilization of database trigger mechanisms (p. 60). | | | | | X | | | 1 | m | i | | | | 1 | | | 1 | i | | | i | | | 1 | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | H, D |
| 79 | (Gandhi et al. 1994) | 1994 | LER (Leveled ER) | (Chen 1976) | sg: complex, c: aspect | sg: is_part_of | sg/l: identifier, sg: multi-valed aspect | | | | | X | formal | g | | | | ... the current proposal overcomes ... [limitations of existing ER models] (p. 421). | | X | X | | | | | i | m | i | | | | 1 | 1 | 1 | 1 | i | | | i | | | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | S | H |
| 80 | (Ling/Teo 1994) | 1994 | OOER (Object-Oriented ER) | (Chen 1976) | sg: weak, complex | sg: m-n, recursive, existence dependent, identifier dependent, ISA, UNION, INTERSEcTION | sg: multi-valued, composite, derived, methods | | | | | X | formalized | t | l | | | ... inability to judge the quality of an OO schema design, the presence of inheritence conflicts ..., the lack of ... support for different relationship types ... and views (p. 241). | structure | | X | | | X | | 1 | 1 | 1 | | | | m | 1 | 1 | 1 | i | | i | i | | | | | | | | | | | | | | | | | | | | 0.30 | 0.56 | 0.00 | 0.00 | S | H |
| 81 | (Liu et al. 1994) | 1994 | EVER (Evolutionary ER) | (Teorey et al. 1986) | sg: visible, defunct | sg: visible, defunct | sg: domain-changed, renamed, resumed, derived, dependent, independent, key | version derivation | | | | Version derivation connects defunct and visible entity types. | formalized | g | l | | | ... provide for the specification of the derivation of relationships between schema versions (p. 133). | time | | | | | | | | m | 1 | | | | 1 | | 1 | m | m | m | | m | | | | | | | | | | | | | 1 | | | | | | | 0.27 | 0.44 | 0.11 | 0.00 | | |
| 82 | (Oh/Navathe 1995) | 1995 | SEER (Security Enhanced ER) | (Chen 1976) | sd: user group | sd: security | X | | | | | Security relationship connects user, entity or relationship types. | informal | t | | | | ... address the conceptual modeling of security features and authorization histories... (p. 170). | domain (security) | | | | | | | | m | | | 1 | | m | | | m | | | | | | | | | | | | | | | | | | | | | | | | 0.12 | 0.22 | 0.00 | 0.00 | | |
| 83 | (Green/Benyon 1996) | 1996 | ERMIA (ER for Information Artifacts) | | sd: pile, chain, sorted list, unsearchable, hashed, conceptual | sg: optionality, sg/l: cardinality | sd: perceptually coded | | | | | X | informal | g | | e | | ... analyse structures with respect to human abilities rather than computer ones (p. 803). | domain (cognitive science) | | | | | | | | m | | | | | | | | 1 | 0 | 1 | | | | | | | | | | | | | | | | | 1 | 1 | | | 1 | 0.18 | 0.17 | 0.00 | 0.50 | | |
| 84 | (Lee et al. 1996) | 1996 | | TEER | X | sg/l: cardinality | sg: composite, multivalued, time series | | | | | X | informal | g | | l | | The concept of time series, ..., does not fit well within these [temporal data] models (p. 341). | time | | | | | | | | m | m | | m | m | m | 1 | 1 | 1 | m | m | m | m | | | f | f | | | | | | | | | | | | | | | | 0.42 | 0.78 | 0.00 | 0.00 | | |
| 85 | (Steeg 1996) | 1996 | ERBM (ER and Behavior Model) | HERM | rf HERM | rf HERM | rf HERM | | behavior properties, behavior specification | | | X | formal | t | l | l | | ... derive an efficient database application to avoid logical/physical tuning (p. 106). [by applying the proposed approach]... logical/physical tuning measures ... can be ... avoided (p. 105). | | | | | X | | | 1 | 1 | | | m | m | 1 | i | 1 | 1 | 1 | 1 | m | m | m | m | 1 | 1 | | | | | | | | | | | | | | | | 0.48 | 0.89 | 0.00 | 0.00 | | |
| 86 | (Chu/Zhang 1997) | 1997 | | general EER | X | r: association, sg: ISA, sg/l: min/max | X | | | role classes (object-oriented) | | Role classes are connected to entity types or role classes. | informal | g | e | | | ... support object evolution and extension for long lived objects (p. 257). | structure | | | | | | | | 1 | | i | | | m | | | 1 | 1 | 1 | | i | | | | | | | | | | | | | | | | | | | | 0.21 | 0.39 | 0.00 | 0.00 | S | |
| 87 | (Moody 1997) | 1997 | | Information Engineering | X | sg: cardinality, optionality | X | subject areas | | | | Each entity type is assigned to one subject area. | informal | | | | | On of the ... limitations of the Entity Relationship Model is its inability to cope with the size and complexity of data models encountered in real world situations (p. 184). | | X | | | | | | | m | i | | | | m | | | 1 | 0 | 1 | m | i | 1 | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | S | |
| 88 | (Bergamaschi/Sartori 1998) | 1998 | CHRONO | IDEFI1X | sg/l: temporal | sg: aggregation, generalization, cardinality, optionality | X | temporal element | | | | Each entity type is associated with a temporal element. | formalized | g | e | | | ... necessity of representing time varying information (p. 35). | time | | | | | | | 1 | m | i | | | | 1 | i | i | 1 | 1 | 1 | m | i | | m | f | | | | | | | | | | | | | | | | | 0.39 | 0.72 | 0.00 | 0.00 | S, Z | |
| 89 | (Lee/Elmasri 1998) | 1998 | ITDM (Integrated Temporal Data Model) | EER (enhanced) | X | sg: generalization, sg/l:min/max | sg: time-varying, time-series, surrogate,sg/l: role | | | | | X | formal | t | e | l | | ... we ... formalize a conceptual model that supports time-series objects as well as traditional version-based objects (p. 21). | time | | | | | | | m | 1 | i | | 1 | | 1 | 1 | i | 1 | 1 | 1 | m | i | | | | | | | | | | | | | | | | | | | | 0.36 | 0.67 | 0.00 | 0.00 | S, Z | |
| 90 | (Sapia et al. 1999) | 1998 | ME/R (Multidimensional ER) | (ISO 1987) | sg: dimension level | sg: fact, classification | | | | | | X | formalized | g | | | | In order to allow the natural representation of the multidimensional semantics ... (p. 109) | multidimensionality | X | | | | | | | | | | | | 1 | | | 1 | 1 | m | | | | | | | 1 | 1 | 1 | | | | | | | | | | | | | 0.21 | 0.22 | 0.33 | 0.00 | | |
| 91 | (Balaban/Shoval 1999b) | 1999 | EER (Enhanced ER) | general EER | X | sg: cardinality, specialization | sg: composite, multivalued, key, role | | | primitive methods (abstract data types) | | Primitive methods are associated with entity and relationship types. | formal | t | | | | The integrity methods ... are automatically created for a given EER diagram (p. 14). | | | | | X | | (Balaban/Shoval 2002) | | 1 | i | | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | i | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.42 | 0.78 | 0.00 | 0.00 | S, J, T | |
| 92 | (Badia 2000) | 2000 | | (Chen 1976) | | sg: cardinality, total, partial | sg: complex, multi-valued, role | constraint | | | generalized quantifier (logics) | X | formal | t | | | | ... limitations on what can be expressed in the [ER] model (p. 323). | integrity | | | | | | | | 1 | i | 1 | | 1 | m | 1 | 1 | 1 | i | 1 | i | i | 1 | 1 | | | | | | | | | | | | | | | | | | 0.42 | 0.78 | 0.00 | 0.00 | S,T | H |
| 93 | (Castellani et al. 2000) | 2000 | MCX | (Tardieu et al. 1974) | X | sg/l: min/max-cardinality, target class | X | | | | | X | informal | g | | | | .. one must be able to mention multiple cardinality couples (p. 34). ... the cardinalities of n-ary (n>=3) relationships defined with the chen model are ambiguous (p. 32). | integrity | | X | | | | | | m | | | | | m | | | 1 | 1 | 1 | | | | | | | | | | | | | | | | | | | | | | 0.15 | 0.28 | 0.00 | 0.00 | | |
| 94 | (Karlapalem et al. 2001) | 2001 | EREC (ER for e-ContraCts) | ER-R | rf ER-R | rf ER-R, sg/l: min/max | rf ER-R | sd: exception, contract event | | | | Rule objects are connected to entity types, relationship types or attributes. | informal | g/t | | | exceptions are represented as rules | ... conceptually modelling e-contracts ... (p. 193). | domain (electronic commerce) | | | | | | | 1 | 1 | i | | m | m | m | | | 1 | 1 | 1 | a | i | | | 1 | 1 | | | | | | | | | | | | | | | | 0.39 | 0.72 | 0.00 | 0.00 | S | |
| 95 | (Ma et al. 2001) | 2001 | FEER (Fuzzy Extended ER) | EER | sg: weak | sg: specialization, category, aggregation | sg: key, multivalued, composite, fuzzy | grade of membership | | | | grades of membership are associated with entity types, relationship types, attributes | formalized | g/t | e | | | .. to cope with imperfect as well as complex objects ... (p. 697). | uncertainty | | | | | | | 1 | 1 | i | | | | 1 | 1 | 1 | m | i | m | i | i | | | | | | | | 1 | 1 | 1 | | | | | | | | | | 0.42 | 0.61 | 0.33 | 0.00 | W, S, J, T | |
| 96 | (Wagner 2001) | 2001 | AOR (Agent-Object-Relationship) | (Barker 1990) | sd: event, action, claim, commitment, agent, object | sg: specialization, composition, sd: sends, receives, does, perceives | rf: Barker (1990) | | | | | X | informal | g | e | | | ER modelling does not account for the dynamic aspects of information and knowledge processing systems (p. 114). | domain (institutional agents) | | | | | | (Wagner 2002) | | m | i | | | | m | | m | 1 | i | 1 | m | i | | m | | | | | | | | | | | | | | | 1 | 1 | | 0.36 | 0.56 | 0.00 | 0.33 | S | H |
| 97 | (Bowers et al. 2002) | 2002 | | (Chen 1976) | r: schematic, sd: authoritative | r: schematic, sg/l: min/max | sg: complex, identifier, sd: mark values, sd/l: role, optional, | anchor | | | | Entity types and relationship types may be associated with at most one anchor. | formal | g/t | | | | ... providing structured access to unstructured information sources (p. 90)... | domain (hypermedia) | | | | | | | | 1 | | | 1 | | 1 | | 1 | 1 | 1 | 1 | | | i | | | | | | | | | | | | | | | | | | | 0.24 | 0.44 | 0.00 | 0.00 | | R |
| 98 | (Vert et al. 2002) | 2002 | | | X | sg: subset, cardinality, optionality, sd/l: fuzzy spatial | X | | | | | X | formalized | g/t | | | uncertainty is extensively treated | ... express ... different degrees of relevance to a GIS user's specific needs (p. 165). | domain (geographic IS) | | | | | | | | 1 | i | | | | 1 | | | 1 | i | 1 | | i | | | | | | | | 1 | 1 | 1 | | | | | | | | | | 0.30 | 0.39 | 0.33 | 0.00 | S | H |
| 99 | (Psaila 2003) | 2003 | ERX (ER for XML) | (Batini et al. 1992) | X | sg: alternative, sd: containment, sg/l: min/max | sg: implied | | | | | X | informal | g/t | | | | [ERX] allows to deal with concepts coming from XML documents at the conceptual level (p. 378). | domain (XML) | | | | | | | | m | 1 | | | | 0 | | i | 1 | 1 | 1 | 1 | m | | i | | | | | | | | | | | | | | | | | | 0.27 | 0.50 | 0.00 | 0.00 | | OR |
| 100 | (Shimazu 2003) | 2003 | RER (Refined ER) | (Chen 1976) | X | sg: generalization | sg: identifier, derived, role | | | | | X | formal | t | | | derived attributes are indicated, but stored | The purpose of an RER model is to apply ILP [Inductive Logic Programming] (p. 390). | knowledge | | | | | | | | 1 | 1 | | | | 1 | | f | m | | | | i | | | | | | | | | | | | | | | | | | | | 0.18 | 0.33 | 0.00 | 0.00 | S | |
Copyright(a) Susanne Patig, 2005