Temporal data: Difference between revisions
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{{Quotation|Time dependent data is characterized by data elements being a function of time. In general, data takes the form | {{Quotation|Time dependent data is characterized by data elements being a function of time. In general, data takes the form | ||
:''d = f(t)'' | :''d = f(t)'' | ||
''For data defined at discrete time stamps t<sub>i</sub>, this relation can be represented as:'' | ''For data defined at discrete time stamps t<sub>i</sub>, this relation can be represented as:'' | ||
:''D = {(t<sub>1</sub>, d<sub>1</sub>),( t<sub>2</sub>, d<sub>2</sub>), ..., (t<sub>n</sub>, d<sub>n</sub>)}'' | :''D = {(t<sub>1</sub>, d<sub>1</sub>),( t<sub>2</sub>, d<sub>2</sub>), ..., (t<sub>n</sub>, d<sub>n</sub>)}'' |
Revision as of 12:40, 21 June 2005
Temporal data refers to data, where changes over time or temporal aspects play a central role or are of interest.
Definitions
A temporal data denotes the evolution of an object characteristic over a period of time.
[Daassi and Nigay, 2004]
Time dependent data is characterized by data elements being a function of time. In general, data takes the form
- d = f(t)
For data defined at discrete time stamps ti, this relation can be represented as:
- D = {(t1, d1),( t2, d2), ..., (tn, dn)}
- where
- di = f(ti)
[Müller and Schumann, 2003]
Time-series are a part of the broader field of time-oriented data:
Time series data is characterized by data elements being a function of time. In general, this data takes the following form:
- D = {(t1, y1),( t2, y2), ..., (tn, yn)}
- with
- yi = f(ti)
[Weber et al., 2001]
Remarks
Applying exploratory (esp. timelines) as well as confirmatory methods, temporal data can be used to analyze the influence of time on a certain variable.
Synonyms
- temporal data
- time-oriented data
- time-varying data
- time-dependent data
References
- [Daassi et al., 2004] Chaouki Daassi, Laurence Nigay, and Marie-Christine Fauvet. Visualization Process of Temporal Data, Lecture Notes in Computer Science, 3180, Springer-Verlag Heidelberg, 2004.
- [Jensen and Snodgrass, 1999] Christian S. Jensen and Richard T. Snodgrass. Temporal Data Management, IEEE Transactions on Knowledge and Data Engineering, 11:36-44, 1999.
- [Müller and Schumann, 2003] W. Müller and H. S. Schumann. Visualization Methods for Time-dependent Data - an Overview, In Proceedings of Winter Simulation 2003, New Orleans, USA, 2003
- [Weber et al., 2001] Marc Weber, Marc Alexa, and Wolfgang Müller. Visualizing Time-Series on Spirals, In Proceedings of the IEEE Symposium on Information Visualization 2001 (InfoVis 2001), p. 7-14, October 2001.