ON THE SEMANTICS OF TRANSACTION TIME AND VALID TIME IN BITEMPORAL DATABASES

Numerous proposals for extending the relational data model to incorporate the temporal dimension of data have appeared in the past several years. While most of these have been historical databases, incorporating in some fashion a valid time dimension to the data model and the query languages, others have been rollback databases, incorporating a transaction time dimension, or bitemporal databases, incorporating both of these temporal dimensions. In this paper we address an issue that has been lacking in many of these papers, namely, a formal specification of the precise semantics of these temporal dimensions of data. We introduce the notion of reference time - the time that any operation is applied to the database state - and provide a logical analysis of the interrelationships among these three temporal dimensions. We also provide an analysis of the meaning of various variables such as now and â which have been used in many of these models without a complete specification of their semantics.Information Systems Working Papers Serie

History and Point in Time in Enterprise Applications

First part points out the main differences between temporal and non-temporal databases. In the second part, based on identification of the three main categories of time involved in database applications: user-defined time, valid time and transaction time, some relevant solutions for their implementation are discussed, mainly from the point of view of database organization and data access level of enterprise applications. The final part is dedicated to the influences of historical data in the business logic and presentation levels of enterprise applications and in application services, as security, workflow, reporting.temporal databases, non-temporal databases, user-define time, valid time, transaction time, enterprise application architecture, application services

The Events method for temporal integrity constraint handling in bitemporal deductive databases

A bitemporal deductive database is a deductive database that supports valid and transaction time. A temporal integrity constraint deals with only valid time, only transaction time or both times. A set of facts to be einserted and deleted in a bitemporal deductive database can be done in a past, present or future valid time and at current transaction time. The temporal integrity constraint handling in bitemporal deductive databases causes that the maintenance of consistency becomes more complex than another databases. The $events method$is based on applying transition and event rules, which explicitly define the insertions and deletions given by a database update. In the conceptual model, we augment the database with temporal transition and event rules and then standard SLDNF-resolution can be used to verify that a transaction does not violate any temporal integrity constraint. In the representational data model, we use time point-based intervals to store temporal information. In this paper, we adapt the$$$events method$$$ for handling temporal integrity constraints. Finally, we present the interaction between the above-mentioned conceptual and representational data models.Postprint (published version

Inter-organizational collaboration among health and social care: TRT©, a transactional approach

Inter-organizational collaboration (IOC) supported by information and communication technologies (ICTs) faces challenges on many fronts in 21st century England as well as globally. Between the somewhat desirable ideal of 'joined up' systems providing efficient services to customers and clients on one side of the continuum, and the costs and risk factors associated with integrating data or constructing large databases on the other side, a fundamental tension exists. This paper addresses this issue in two parts. Firstly, it argues that there is a way forward for information sharing among heterogeneous organizations which does not involve the integration of systems, interoperability, joined up recordkeeping, database linkage, or construction of yet another large database. Transactions in Real Time© (TRT©), the transaction by transaction information sharing approach, satisfies all the requirements of each collaborating organization for information sharing. Secondly, this paper briefly considers the future of IOC among health and social care and possible pathways forward through this uncertain area. The health and social care information sharing transaction is often unique among the particular transaction situation, and the micro and macro environments

Extending the synthesis of update transaction programs to handle existential rules in deductive databases

We propose a new method for generating consistency-preserving transaction programs for (view) updates in deductive databases. The method augments the deductive database schema with a set of transition and intemal events rules, which explicitly define the database dynamic behaviour in front of a database update. At transaction-design-time, a formal procedure can use these rules to automatically generate parameterised transaction programs for base or view-update transaction requests. This is done in such a way that those transactions will never take the database into an inconsistent state. In this paper we extend a previous version of the method by incorporating existentially defined rules. Within this context, synthesis outputs and processes are provided. Toe method, implemented in Prolog using meta-programming techniques, draws from our previous work in deductive databases, particularly in view updating and integrity constraints checking

An Enhanced Approach for Compress Transaction Databases

Associative rule mining is defined as the task that deals with the extraction of hidden knowledge and frequent patterns from very large databases. Traditional associative mining processes are iterative, time consuming and storage expensive. To solve these processes, a way of representation that reduces this size and at the same time maintains all the important and relevant data needed to extract the desired knowledge from transaction databases is needed. This paper proposes a method that merges the transactions in the transaction database and uses FP-Growth algorithm for mining associative knowledge is presented. The experimental results in terms of compression ratio, both in terms of storage required and number of transactions, prove that the proposed algorithm is an improved version to the existing systems

Rough clustering for web transactions

Grouping web transactions into clusters is important in order to obtain better understanding of user's behavior. Currently, the rough approximation-based clustering technique has been used to group web transactions into clusters. It is based on the similarity of upper approximations of transactions by given threshold. However, the processing time is still an issue due to the high complexity for finding the similarity of upper approximations of a transaction which used to merge between two or more clusters. In this study, an alternative technique for grouping web transactions using rough set theory is proposed. It is based on the two similarity classes which is nonvoid intersection. The technique is implemented in MATLAB ® version 7.6.0.324 (R2008a). The two UCI benchmark datasets taken from: http:/kdd.ics.uci.edu/ databases/msnbc/msnbc.html and http:/kdd.ics.uci.edu/databases/ Microsoft / microsoft.html are opted in the simulation processes. The simulation reveals that the proposed technique significantly requires lower response time up to 62.69 % and 66.82 % as compared to the rough approximation-based clustering, severally. Meanwhile, for cluster purity it performs better until 2.5 % and 14.47%, respectively

The Effect of Bid-Ask Prices on Brazilian Options Implied Volatility: A Case Study of Telemar Call Options

Although not explicitly reported, option traders on the Bovespa exchange pay an implicit bid-ask spread on each trade. Reported transaction prices that comprise the databases previously used to study the Brazilian options markets do not reflect actual option values at the time of the trades, but actual values plus (for purchases) or minus (for sales) the bid-ask spread. We use a chooser American option model to estimate Telemar call options bid-ask spreads, and to create a database of spread-adjusted trade prices. We find that the bid-ask spreads explain several previously reported puzzles regarding asset price volatility.