Concept

Single source of truth

In information science and information technology, single source of truth (SSOT) architecture, or single point of truth (SPOT) architecture, for information systems is the practice of structuring information models and associated data schemas such that every data element is mastered (or edited) in only one place, providing data normalization to a canonical form (for example, in database normalization or content transclusion). There are several scenarios with respect to copies and updates: The master data is never copied and instead only references to it are stored; this means that all reads and updates go directly to the SSOT The master data is copied but the copies are only read and only the master data is updated; if requests to read data are only made on copies, this is an instance of CQRS The master data is copied and the copies are updated; this needs a reconciliation mechanism when there are concurrent updates Updates on copies can be thrown out whenever a concurrent update is made on the master, so they are not considered fully committed until propagated to the master (many blockchains work that way) Concurrent updates are merged (if an automatic merge fails, it could fall back on another strategy, which could be the previous strategy or something else like manual intervention, which most source version control systems do) The advantages of SSOT architectures include easier prevention of mistaken inconsistencies (such as a duplicate value/copy somewhere being forgotten), and greatly simplified version control. Without a SSOT, dealing with inconsistencies Deployment of an SSOT architecture is becoming increasingly important in enterprise settings where incorrectly linked duplicate or de-normalized data elements (a direct consequence of intentional or unintentional denormalization of any explicit data model) pose a risk for retrieval of outdated, and therefore incorrect, information. Common examples (i.e.

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Related publications (7)

A Method for Record Linkage with Sparse Historical Data

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Massive digitization of archival material, coupled with automatic document processing techniques and data visualisation tools offers great opportunities for reconstructing and exploring the past. Unprecedented wealth of historical data (e.g. names of perso ...
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Data Reconciliation in Reaction Systems using the Concept of Extents

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Abstract of the conference paper Concentrations measured during the course of a chemical reaction are corrupted with noise, which reduces the quality of information. Since these measurements are used for identifying kinetic models, the noise imp ...
Elsevier2015

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Related concepts (1)
Master data management
Master data management (MDM) is a technology-enabled discipline in which business and information technology work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets. Organisations, or groups of organisations, may establish the need for master data management when they hold more than one copy of data about a business entity. Holding more than one copy of this master data inherently means that there is an inefficiency in maintaining a "single version of the truth" across all copies.

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