When you integrate two vectors you put them side by side and they can be clearly differentiated (you can say that they are orthogonal). In fusion you can do vector addition, multiplication or compound operation that merges the two values into a single value which then is "fused" together. I this instance the identity of the individual contributions are lost.

Data fusion by definition is the process of "fusing" or combining data from multiple data sources for the purpose of better inference.

For example, multiple radar sources allow fusing of data captured from its built-in sensor in order to effectively detecting an object such ship or flight.

On the other hand, Data integration by definition is a process in which heterogeneous data is retrieved and combined as an incorporated form and structure. Data integration allows different data types (such as data sets, documents and tables) to be merged by users, organizations and applications, for use as personal or business processes and/or functions. For instance, various navigation systems such as gyro, DVL, compass are integrated for better navigation solution.

In fusion, you combine two or more resource with together to achieve a one data that it have properties of all input resources. In this field, resources merged into together and they not separate from each other.In integration you also combine two or more resources, but the output combination can be separate to all of inputs. In other wise, fusion is like to salt soluble in water and integration is like to combination of sandwich materials.

Dear Mahdis Dezfouli,

01. Data Fusion :

Data fusion is the process of getting data from multiple sources in order to build more sophisticated models and understand more about a project. It often means getting combined data on a single subject and combining it for central analysis.

or

Data fusion frequently involves “fusing” data at different abstraction levels and differing levels of uncertainty to support a more narrow set of application workloads.

or

Data fusion is the process of integrating multiple data sources to produce more consistent, accurate, and useful information than that provided by any individual data source.

Various types of data fusion work in different ways:

Low, intermediate and high-level data fusion – and likewise distinguish geospatial types of data fusion from other types of data fusion. Another specific type of data fusion is called “sensor fusion” where data from diverse sensors are combined into one data-rich image or analysis.

Data fusion is broadly applied to technologies, for instance, in a research project, scientists might use data fusion to combine physical tracking data with environmental data, or in a customer dashboard, marketers might combine client identifier data with purchase history and other data collected at brick-and-mortar store locations to build a better profile.

Data fusion involves a level of concrete definition from something called the Joint Directors of Laboratories Data Fusion Group which produces six levels for a data fusion information group model:

02. Data integration :

Data integration is a process in which heterogeneous data is retrieved and combined as an incorporated form and structure. Data integration allows different data types (such as data sets, documents and tables) to be merged by users, organizations and applications, for use as personal or business processes and/or functions.

or

Data integration is the combination of technical and business processes used to combine data from disparate sources into meaningful and valuable information. A complete data integration solution delivers trusted data from various sources.

or

Data integration involves combining data from several disparate sources, which are stored using various technologies and provide a unified view of the data. Data integration becomes increasingly important in cases of merging systems of two companies or consolidating applications within one company to provide a unified view of the company's data assets. The later initiative is often called a data warehouse.

or

Data integration in the purest sense is about carefully and methodically blending data from different sources, making it more useful and valuable than it was before. IBM provides a strong definition, stating “Data integration is the combination of technical and business processes used to combine data from disparate sources into meaningful and valuable information.”

An example of data integration in a smaller paradigm is spreadsheet integration in a Microsoft Word document.

Data integration is a term covering several distinct sub-areas such as:

I hope I have answered your question.

With Best Wishes,

Samir G. Pandya.

Samir G Pandya, so in summary it seems that the main difference between the two is that data fusion works with homogeneous data while data integration works with heterogeneous data. In programming terms:

Data fusion: all the same data type

Data integration: different data types

Daniel said the main difference

The homogeneous data in data fusion does require having the source devices of the data be identical or homogeneous. However, the homogeneity of the data is their description/transformation of the data coming from the different domain into a common domain of description that allows (melting) adding, subtract, or multiply different vectors of the data described in the same domain, for the purpose to facilitate effective inference. While the data integration does not demand/require such transformation of data into the same domain of description as the data coming from different sources stay in their domain of description.

Data integration involves combining data residing in different sources and providing users with a unified view of them.

Data fusion is collecting data from different sources, but it is not involved in to produce more consistent, accurate, and useful information than that provided by any individual data source. Data fusion processes are often categorized as low, intermediate, or high, depending on the processing stage at which fusion takes place.