A comparison of the temporal expressiveness of three database query methods (original) (raw)
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An extended SQL for temporal data management in clinical decision-support systems
Proceedings / the ... Annual Symposium on Computer Application [sic] in Medical Care. Symposium on Computer Applications in Medical Care, 1992
We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.
Temporal Expressiveness in Querying a Time-stamp-- based Clinical Database
Journal of the American Medical Informatics Association, 2000
A b s t r a c t Most health care databases include time-stamped instant data as the only temporal representation of patient information. Many previous efforts have attempted to provide frameworks in which medical databases could be queried in relation to time. These, however, have required either a sophisticated database representation of time, including time intervals, or a time-stamp-based database coupled with a nonstandard temporal query language. In this work, the authors demonstrate how their previously described data retrieval application, DXtractor, can be used as a database querying application with expressive power close to that of temporal databases and temporal query languages, using only standard SQL and existing timestamp-based repositories. DXtractor provides the ability to compose temporal queries through an interface that is understood by nonprogramming medical personnel. Not all temporal constructs are easily implemented using this framework; nonetheless, DXtractor's temporal capabilities provide a significant improvement in the temporal expressivity accessible to clinicians using standard time-stamped clinical databases.
Supporting temporal queries on clinical relational databases: the S-WATCH-QL language
Proceedings : a conference of the American Medical Informatics Association / ... AMIA Annual Fall Symposium. AMIA Fall Symposium, 1996
Due to the ubiquitous and special nature of time, specially in clinical datábases there's the need of particular temporal data and operators. In this paper we describe S-WATCH-QL (Structured Watch Query Language), a temporal extension of SQL, the widespread query language based on the relational model. S-WATCH-QL extends the well-known SQL by the addition of: a) temporal data types that allow the storage of information with different levels of granularity; b) historical relations that can store together both instantaneous valid times and intervals; c) some temporal clauses, functions and predicates allowing to define complex temporal queries.
Querying temporal clinical databases with different time granularities: the GCH-OSQL language
Proceedings / the ... Annual Symposium on Computer Application [sic] in Medical Care. Symposium on Computer Applications in Medical Care, 1995
There is a need for managing temporal clinical information given at different levels of granularity. Different time granularities are also needed in querying clinical databases. In this paper, we describe GCH-OSQL (Granular Clinical History--Object Structured Query Language), an object-oriented temporally-oriented extension of SQL. GCH-OSQL is based on an object-oriented temporal data model. It allows storage of clinical information at different and mixed granularities. GCH-OSQL deals with the valid time of clinical information. GCH-OSQL offers also a graphical user-interface. It guides different end users, from expert to naive, to formulate expressive and correct queries.
Applying temporal joins to clinical databases
Proceedings / AMIA ... Annual Symposium. AMIA Symposium, 1999
Clinical databases typically contain a significant amount of temporal information, information that is often crucial in medical decision-support systems. Most recent clinical information systems use the relational model when working with this information. Although these systems have reasonably well-defined semantics for temporal queries on a single relational table, many do not fully address the complex semantics of operations involving multiple temporal tables. Such operations can arise frequently in queries on clinical databases. This paper describes the issues encountered when joining a set of temporal tables, and outlines how such joins are far more complex than non-temporal ones. We describe the semantics of temporal joins in a query management system called Chronus II, a system we have developed to assist in evaluating patients for clinical trials.
IEEE Transactions on Information Technology in Biomedicine, 1997
The need to manage temporal information given at different levels of granularity or with indeterminacy is common to many application areas. Among them, we focus on clinical data management. Different time granularities and indeterminacy are also needed in querying temporal databases. In this paper, we describe GCH-OSQL (Granular Clinical History-Object Structured Query Language), an object-oriented/temporally-oriented extension of SQL. GCH-OSQL is based on an object-oriented temporal data model, GCH-OODM. GCH-OODM allows storage of clinical information at different and mixed granularities or with temporal indeterminacy. GCH-OSQL deals with the valid time of clinical information. The temporal extension of the SELECT construct includes the addition of the TIME-SLICE and MOVING WINDOW clauses, and the capability to reference the temporal dimension of objects in the WHERE and SELECT clauses. Using object-oriented technologies, a system prototype for GCH-OSQL and GCH-OODM has been implemented and applied to data management of follow-up patients after coronary angioplasty intervention.
The challenges of specifying intervals and absences in temporal queries
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2013
In our burgeoning world of ubiquitous sensors and affordable data storage, records of timestamped events are being produced across nearly every domain of personal and professional computing. The resulting data surge has created an overarching need to search these records for meaningful patterns of events. This paper reports on a two-part user study, as well as a series of early tests and interviews with clinical researchers, that informed the development of two temporal query interfaces: a basic, menu-based interface and an advanced, graphic-based interface. While the scope of temporal query is very broad, this work focuses on two particularly complex and critical facets of temporal event sequences: intervals (events with both a start time and an end time), and the absence of an event. We describe how users encounter a common set of difficulties when specifying such queries, and propose solutions to help overcome them. Finally, we report on two case studies with epidemiologists at the US Army Pharmacovigilance Center, illustrating how both query interfaces were used to study patterns of drug use.
Artificial Intelligence Review, 2006
Storing and retrieving time-related information are important, or even critical, tasks on many areas of Computer Science (CS) and in particular for Artificial Intelligence (AI). The expressive power of temporal databases/query languages has been studied from different perspectives, but the kind of temporal information they are able to store and retrieve is not always conveniently addressed. Here we assess a number of temporal query languages with respect to the modelling of time intervals, interval relationships and states, which can be thought of as the building blocks to represent and reason about a large and important class of historic information. To survey the facilities and issues which are particular to certain temporal query languages not only gives an idea about how useful they can be in particular contexts, but also gives an interesting insight in how these issues are, in many cases, ultimately inherent to the database paradigm.
Representation of temporal indeterminacy in clinical databases
Proceedings / AMIA ... Annual Symposium. AMIA Symposium, 2000
Temporal indeterminancy is common in clinical medicine because the time of many clinical events is frequently not precisely known. Decision support systems that reason with clinical data may need to deal with this indeterminancy. This indeterminacy support must have a sound foundational model so that other system components may take advantage of it. In particular, it should operate in concert with temporal abstraction, a feature that is crucial in several clinical decision support systems that our group has developed. We have implemented a temporal query system called Tzolkin that provides extensive support for the temporal indeterminancies found in clinical medicine, and have integrated this support with our temporal abstraction mechanism. The resulting system provides a simple, yet powerful approach for dealing with temporal indeterminancy and temporal abstraction.