Bioinformatics researches, when is data integration needed and necessary?

Question

[d]

In which cases is data integration necessary and needed in bioinformatics? is there a specific research step in which data integration is necessary?

And most importantly, how to approach data integration, which type of omic data is more important to integrate between database repositories?

Thank you

[Pierre Lindenbaum]

what do you mean with "data integration" ? We all use public databases (ucsc, ncbi, ensembl...). Is it data integration ?

[d]

I mean if the data from those public databases would need to be integrated into one single repository for easier access, and how to approach this if it is a necessary task.

Answer 1

[Jean-Karim Heriche]

Data integration broadly defined as making use of data from multiple sources is not a single thing. The "making use of" part determines the kind of integration. One example of data integration in when you map various pieces of information to a common reference genome, another example is statistical data integration to combine data for analysis. The approach you take is determined by the context and the question you try to answer. Nevertheless, a common first step is to define the data sources to use. Should you include data from study A but not from study B? When using curated resources, you may need to be aware that they contain redundant information or biases that may affect your conclusions.
Regarding the more specific question of integrating public databases into a single repository, the question would be: for what purpose and in which form? Consider that we already have plenty of such integrated databases such as Ensembl or all the model organisms databases (e.g. wormbase, flybase...) each adapted to serve a specific purpose or community.

[d]

Very detailed and perfectly answered my question. Thank you!