Spoiler alert of the answer: it depends. In this post, I’ll trace it back to how we got to that conclusion and refine it to what it depends on.
There are several conceptual modelling languages with extensions for temporal constraints that then will be used in a database to ensure data integrity with respect to the business rules. For instance, there may be a rule for some information system that states that “all managers in a company must have been employees of that company already” or “all postgraduate students must also be a teaching assistant for some time during their studies”. The question then becomes how to get the modellers to model this sort of information in the best way. The first step in that direction is figuring out the best way to represent temporal constraints. We already know that icons aren’t that unambiguous and easy , which leaves the natural language rendering devised recently , or one of the logic-based notations, such as the temporal Description Logic DLRUS . So, the questions to investigate thus became, more precisely:
- Which representation is preferred for representing temporal information: formal semantics, Description Logics (DL), a coding-style notation, diagrams, or template-based (pseudo-)natural language sentences?
- What would be easier to understand by modellers: a succinct logic-based notation, a graphical notation, or a ‘coding style’ notation?
To answer these questions, my collaborator, Sonia Berman (also at UCT) and I conducted a survey to find out modeller preference(s) and understanding of these representation modes. The outcome of the experiment is about to be presented at the 36th International Conference on Conceptual Modeling (ER’17) that will be held next week in Valencia, Spain, and is described in more detail in the paper “Determining the preferred representation of temporal constraints in conceptual models” .
The survey consisted mainly of questions asking them about which representation they preferred, a few questions on trying to model it, and basic questions, like whether they had English as first language (see the questionnaire for details). Below is one of the questions to illustrate it.
Its option (a) is the semantics notation of the DLRUS Description Logic, its option (b) the short-hand notation in DLRUS, option (c) a coding-style notation we made up, and option (e) is the natural language rendering that came out of prior work . Option (d) was devised for this experiment: it shows the constraint in the Temporal information Representation in Entity-Relationship Diagrams (TREND) language. TREND is an updated and extended version of ERVT , taking into account earlier published extensions for temporal relationships, temporal attributes, and quantitative constraints (e.g., ‘employee receives a bonus after two years’), a new extension for the distinction between optional and mandatory temporal constraints, and the notation preferences emanating from .
Here are some of the main quantitative results:
These are aggregates, though, and they hide some variations in responses. For instance, representing ‘simple’ temporal constraints in the DL notation was still ok (though noting that diagrams were most preferred), but the more complex the constraints got, the more the preference for the natural language rendering. For instance, take “Person married-to Person may be followed by Person divorced-from Person, ending Person married-to Person.” is deemed easier to understand than or . Yet, the temporal relationship was deemed easier to understand than “The objects participating in a fact in Person married to Person do not relate through married-to at some time”. Details of the experiment and more data and analysis are described in the paper . In sum, the evaluation showed the following:
- a clear preference for graphical or verbalised temporal constraints over the other three representations;
- ‘simple’ temporal constraints were preferred graphically and complex temporal constraints preferred in natural language; and
- their English specification of temporal constraints was inadequate.
Overall, this indicates that what is needed is some modeling tool that has a multi-modal interface for temporal conceptual model development, with the ability to switch between graphical and verbalised temporal constraints in particular.
If I hadn’t had teaching obligations (which now got cancelled due to student protests anyway) and no NRF funding cut in the incentive funding (rated researchers got to hear from one day to the next that it’ll be only 10% of what it used to be), I’d have presented the paper myself at ER’17. Instead, my co-author is on her way to all the fun. If you have any questions, suggestions, or comments, you can ask her at the conference, or drop me a line via email or in the comments below. If you’re interested in TREND: we’re working on a full paper with all the details and have conducted further modeling experiments with it, which we hope to finalise writing up by the end of the year (provided student protests won’t escalate and derail research plans any further).
 T. Shunmugam. Adoption of a visual model for temporal database representation. M. IT thesis, Department of Computer Science, University of Cape Town, South Africa, 2016.
 Keet, C.M. Natural language template selection for temporal constraints. CREOL: Contextual Representation of Events and Objects in Language, Joint Ontology Workshops 2017, 21-23 September 2017, Bolzano, Italy. CEUR-WS Vol. (in print).
 A. Artale, E. Franconi, F. Wolter, and M. Zakharyaschev. A temporal description logic for reasoning about conceptual schemas and queries. In S. Flesca, S. Greco, N. Leone, and G. Ianni, editors, Proceedings of the 8th Joint European Conference on Logics in Artificial Intelligence (JELIA-02), volume 2424 of LNAI, pages 98-110. Springer Verlag, 2002.
 Keet, C.M., Berman, S. Determining the preferred representation of temporal constraints in conceptual models. 36th International Conference on Conceptual Modeling (ER’17). Mayr, H.C., Guizzardi, G., Ma, H. Pastor. O. (Eds.). Springer LNCS vol. 10650, 437-450. 6-9 Nov 2017, Valencia, Spain.
 A. Artale, C. Parent, and S. Spaccapietra. Evolving objects in temporal information systems. Annals of Mathematics and Artificial Intelligence, 50(1-2):5-38, 2007.