JSAIS 13-001 Temporal Data Update Methodologies for Data Warehousing


Business organizations have been increasingly using temporal data for making strategic and tactical decisions. The key idea of temporal data management is to make data available at the right time with different time intervals. The temporal data storing enables this by making all the different time slices of data available to whoever needs it. Users with different data latency needs can all be accommodated. Data can be “frozen” via a view on the proper time slice. Data as of a point in time can be obtained across multiple tables or multiple subject areas, resolving consistency and synchronization issues. This article will discuss implementations such as temporal data update methodologies, coexistence of load and query against the same table, performance of load and report queries, and maintenance of views on top of the tables with temporal data.


Temporal Data, Temporal Data Warehouse, Row-Effective Timestamp, Row-Expired Timestamp, Data Update Methodology.



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  1. Mark McMurtrey

    I will admit up front that I did not give the paper a real “close” read. It did seem to flow well and I always love practical applications and examples. The literature review was sufficient, the main body was fine, and conclusions succinct. My only concern is that it needs some newer references; the latest one I could find was from 2008. I also got a 404 error from the one (and only) URL that I tried to visit! LOL

    I think the paper will make a great contribution to JSAIS, it just needs a little re-freshening. 🙂

  2. JY

    Several items in the introduction could be strengthened with relevant citations. Implications and limitations are missing. The conclusion is very short and does not explain the significance of this study. I would be interested in a comparison of most commonly used methods contrasted to the temporal database methods. The tables seem like they have promise of being meaningful, but right now they seem just a bit messy or jumbled.

  3. mcmurrayjsais

    This paper presents a method for maintaining transaction lineage within a data warehouse. The technique proposed is straight forward applying the use of time stamping. Further the paper does a good job of incorporating the use of widely used existing database techniques to enhance the use of temporal data storage, updating and retrieval. The paper has value given the increasing need to find ways to effectively and efficiently improve how we are able to best analyze the data so readily accrued through electronic means.

    However, I have some suggestions that could strengthen the paper. First, while the paper is well-written, it contains a multitude of grammatical errors (missing words, commas, misuse or non-use of articles [‘a’ and ‘the’]. This could be easily addressed by a thorough edit of the paper.

    An explicit definition of what is meant by temporal data in relation to its use in this article should be included. Temporal data often refers to temporal information – that is not the case in this paper. This paper focuses on transaction lineage of changes in rows of data – not the time-sensitive characteristic of the specific data field. Without clarification, the use of ‘temporal data’ could be confusing to the reader.

    The paper could also be strengthened by adding a discussion on the value of maintaining transaction lineage. It certainly is important but sometime time stamping the updating of a row of does not incur meaning unless context is also provided. The paper explores provision for various views based on time-slicing but the paper could be strengthened if ways for maintaining transactional change context were also discussed.

    Finally, the paper notes that temporal database management systems are not commercially available – however, a quick look at the reference list shows the most recent source is dated 2008 – it would be good to incorporated more recent sources in the paper.

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