| H. Gregersen and C. S. Jensen. Temporal EntityRelationship Models - a Survey. IEEE Trans. on Knowledge and Data Engineering, 11(3):464--497, 1999. 1139 |
....and to constrain their temporal properties. If the implicit approach has the attractive of leaving unchanged the original ER model, this approach rules out the possibility of designing non temporal databases or databases where some part of a database is nontemporal and the rest is temporal [ Gregersen and Jensen, 1997 ] The formalism introduced in this paper follows an implicit approach, but extends it by providing the possibility to explicitly express temporal constructs. The formalisms is centred around a basic temporal ER model, which does not have any new syntactical constructs with respect to a ....
....in the corresponding DL knowledge base and logical implication within a ER schema which is mapped to a logical implication problem in the corresponding DL knowledge base. Let us consider the example ER diagram of figure 3; this diagram is the running example considered in the survey paper [ Gregersen and Jensen, 1997 ] We first translate (a fragment of) the ER schema in the description logic knowledge base #ER : WORKS FOR has prj : Project has emp : Employee # #has prj 1 . WORKS FOR We now want to impose additional integrity constraints, which are expressed by means of terminological axioms in a ....
H. Gregersen and C.S. Jensen. Temporal Entity-Relationship models - a survey. Technical Report TR-3, TimeCenter, 1997.
....of the most important reasoning tasks are summarised. The second part is on temporal conceptual modelling in the relational data model. Temporal conceptual modelling constructs for the valid time representation as appeared in the literature on the Entity Relationship data model (see, e.g. [40,26]) are considered. A systematic characterisation (first introduced in [3] of the constructs introduced in the majority of temporal conceptual modelling systems is provided. The third part is about schema evolution in the object oriented data model. A data model supports schema evolution if it ....
....Salary(Integer) vt Project ProjectCode(String) Manager vt TopManager AreaManager Department s InterestGroup OrganisationalUnit s d DEX Works for vt Manages Resp for s (1,n) act emp man (1,1) 1,5] prj (1,1) 1,n) prj org Fig. 1. A temporal ER diagram. cf. [26] for an extensive overview of temporally extended ER models) We refer to ER models because they are the most mature field in temporal conceptual modelling. As far as the notation for temporal constructs is concerned, we use a unifying notation that will capture the commonalities between the ....
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
.... of different classes of information with diverse characteristics, including sensor derived and user supplied information Dependencies between different types of information While modelling approaches exist that are able to capture some of these aspects (such as temporal ER modelling languages [5] and quality modelling approaches [6] we are not aware of any single approach that can capture all of these features in a natural way. In our initial attempt to define a set of modelling concepts appropriate for describing context information, we avoided aligning our work with any of the ....
Gregersen, H., Jensen, C.S.: Temporal entity-relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering 11 (1999)
.... the temporal description logic DLRUS can provide a formal semantic characterisation of the most important temporal conceptual modelling constructs (for the valid time representation) We refer mostly to the temporal extended entity relationship data model, for which a detailed literature exists [25, 24, 41, 44]. We consider the following constructs: snapshot and temporary entities, relationships, attributes (together with the temporal key attribute) temporal cardinalities, dynamic entities, liveliness and safety constraints, and the monotonic form of schema evolution. The extended entity relationship ....
....data model, enriched with IsA links, disjoint and covering constraints, and full cardinality constraints [18] may be viewed as a temporalised EER model which assigns to every construct a temporal interpretation but provides no explicit temporal constructs. Gregersen and Jensen [24] call this approach implicit, because the temporal dimension is hidden in the interpretation structure so that entities and relationships are always time dependent. The non temporal fragment of DLRUS , i.e. DLR, is enough to capture the EER model with implicit time. For the non temporal EER ....
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
....it evolves with the schema by varying its structural properties and it is requested to have an overview of its evolution over time [3, 2] In this case an explicit treatment of time is required in the formal framework. By adopting a temporally extended conceptual data model with implicit time [16], and by assuming that objects in the same database have implicitly always the same timestamp the one labelling the database version, the framework proposed in this paper easily lifts up to cover the case of having multiple pools of data. In fact, the set of pools can be considered as a unique ....
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transaction on Knowledge and Data Engineering, 11(3):464--497, 1999.
.... how the temporal description logic can provide a formal semantic characterisation of the most important temporal conceptual modelling constructs (for the valid time representation) We refer mostly to the temporal extended entity relationship data model, for which a detailed literature exists [18, 22]. The extended entity relationship (EER) model i.e. the standard entity relationship data model, enriched with IsA links, disjoint and covering constraints, and full cardinality constraints may be viewed as a temporalised EER model which assigns to every construct a temporal interpretation ....
....entity relationship data model, enriched with IsA links, disjoint and covering constraints, and full cardinality constraints may be viewed as a temporalised EER model which assigns to every construct a temporal interpretation but provides no explicit temporal constructs. Gregersen and Jensen [18] call this approach implicit, because the temporal dimension is hidden in the interpretation structure so that entities and relationships are always timedependent. i.e. is enough to capture the EER model with implicit time. For the non temporal EER model, such an encoding, introduced by ....
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
....But first we are going to discuss two important applications of RUDs. 3 Applications 3. 1 Conceptual Modeling There have been several proposals to extend the Entity Relationship(ER) model to capture more temporal and spatial semantics [15] A recent survey of temporal extensions of ER models is [9]. In [21] we use temporal functional dependencies (TFDs) to refine the cardinality construct. Tauzovich [18] distinguishes between snapshot cardinality and lifetime cardinality. In [21] we show that TFDs allow to specify cardinality constraints at any granularity level, snapshot and lifetime ....
H. Gregersen and C. S. Jensen. Temporal Entity-Relationshipmodels---A survey. IEEE Trans. on Knowledge and Data Engineering, 11(3):464--497, 1999.
....Tab. 1, the following functions have to be de ned: SV 1 SV 2 , SV 2 SV 3 and SV 3 SV 4 . Additionally, functions for non contiguous structure versions can be de ned or derived to optimize performance. 7 Related Work In contrast to temporal databases, which have been well studied, e.g. [3, 7, 8], few approaches are known in literature for temporal data warehouses, e.g. 4, 13 15] The same applies for schema evolution of databases, e.g. 13, 5] vs. schema evolution of data warehouses, e.g. 2] 4] present which extensions are necessary in order to extend a data warehouse to ....
Gregersen and Jensen. Temporal Entity-Relationship Models - a Survey. TimeCenter, 1997.
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models---a Survey. IEEE Transactions on Knowledge an Data Engineering, 11(3):464--497, May 1999.
No context found.
Gregersen, H., and Jensen, C.S., 1997a. Temporal Entity-Relationship Models-a Survey. Submitted for publication.
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models---a Survey. IEEE Transactions on Knowledge an Data Engineering, 11(3):464--497, 1999.
....4, 2, 21, 20, 15, 26] These temporal ER models are developed in an attempt to provide modeling constructs that more naturally and elegantly permit the database designer to capture general temporal aspects of information, such as valid and transaction time. For a survey of the existing models, see [8] Both the standard and temporally enhanced ER models may be used for different, but related purposes, namely for analysis i.e. for modeling a part of reality and for design i.e. for describing the database schema of a computer system. The typical use seems to be one where the model is ....
....use of the models for design. This papers evaluation focuses exclusively on the modeling of temporal aspects, and in addition considers the use of the models for analysis. Temporally extended ER models have been surveyed and evaluated with respect to a set of evaluation criteria by the author in [8, 9]. The focus of these evaluations are entirely on model properties, and criteria based on real world and relational ontologies are do not considered. In summary, the focus of previous, related evaluations ranges from determining the environments in which methodologies where developed, over the ....
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models---a Survey. IEEE Transactions on Knowledge an Data Engineering, 11(3):464--497, May 1999.
....in Figure 25 provide. 9 Related Work Over the last two decades, many temporal conceptual models have been proposed, e.g. TERM (Temporal Entity Relationship Model) 38, 39] RAKE (Relationships, Attributes, Keys and Entities) 21] TEER (Temporal EER) 17, 18] TERC [89] and TimeER Model [26]. The reader is referred to an excellent survey of extant temporal conceptual models by Gregersen and Jensen [26] In the last couple of years, two major spatio temporal conceptual models have been proposed: MADS (Modeling of Application Data with Spatiotemporal) 52 54] and GeoER [29] which was ....
.... proposed, e.g. TERM (Temporal Entity Relationship Model) 38, 39] RAKE (Relationships, Attributes, Keys and Entities) 21] TEER (Temporal EER) 17, 18] TERC [89] and TimeER Model [26] The reader is referred to an excellent survey of extant temporal conceptual models by Gregersen and Jensen [26]. In the last couple of years, two major spatio temporal conceptual models have been proposed: MADS (Modeling of Application Data with Spatiotemporal) 52 54] and GeoER [29] which was extended to STER (Spatiotemporal Entity Relation) 82] The other spatial models, e.g. GEO Object Oriented ....
H. Gregersen and C. S. Jensen, Temporal Entity-Relationship Models-A Survey,IEEE Transactions on Knowledge and Data Engineering, Vol. 11, No. 3, pp. 464-497, 1999.
No context found.
H. Gregersen and C. S. Jensen. Temporal EntityRelationship Models - a Survey. IEEE Trans. on Knowledge and Data Engineering, 11(3):464--497, 1999. 1139
No context found.
Gregersen, H., Jensen, C.S.: Temporal entity-relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering 11 (1999) 464--497
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transaction on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transaction on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
Heidi Gregersen and Christian S. Jensen. Temporal Entity-Relationship Models - A Survey. Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transaction on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
Heidi Gregersen and Christian S. Jensen. Temporal entity-relationship models - a survey. Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
H. Gregersen and C. S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transaction on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
No context found.
Heidi Gregersen and Christian S. Jensen. Temporal Entity-Relationship Models - A Survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464-497, 1999.
No context found.
H Gregersen and J. S. Jensen. Temporal Entity-Relationship models - a survey. IEEE Transactions on Knowledge and Data Engineering, 11(3):464--497, 1999.
First 50 documents
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC