| Title |
Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic
|
|---|---|
| Published in |
Software and Systems Modeling, April 2016
|
| DOI | 10.1007/s10270-016-0519-z |
| Pubmed ID | |
| Authors |
Bernd Neumayr, Christoph G. Schuetz, Manfred A. Jeusfeld, Michael Schrefl |
| Abstract |
An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 4% |
| Unknown | 25 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 19% |
| Student > Bachelor | 3 | 12% |
| Researcher | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Lecturer > Senior Lecturer | 2 | 8% |
| Other | 6 | 23% |
| Unknown | 5 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 58% |
| Business, Management and Accounting | 1 | 4% |
| Unspecified | 1 | 4% |
| Agricultural and Biological Sciences | 1 | 4% |
| Engineering | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 7 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 May 2016.
All research outputs
#14,906,966
of 23,849,058 outputs
Outputs from Software and Systems Modeling
#288
of 721 outputs
Outputs of similar age
#164,034
of 303,256 outputs
Outputs of similar age from Software and Systems Modeling
#7
of 15 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 721 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 52% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 303,256 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.