The e[catalog] enables both the build up of a single resource of legacy and current research datasets from a variety of experiments, and permits the federation of relevant disparate data sources. This resource can then be shared and viewed globally by all individuals across different departments of an organisation, from technical staff right through to senior management.
The e[catalog] also allows for seamless collaboration both within the same organisation across various sites and with other external partner organisations.
Being aware of the many different projects and associated experimental datasets resulting from a variety of experimental approaches within an organisation can be of economical benefit, as this can ensure that a repeat of existing experiments on the same samples is prevented. Also researchers within the organisation will be aware of what subjects, samples and raw datasets have already been used in experiments that could potentially be available to be used for a new experiment, thereby saving time.
Datasets within e[catalog] are also readily accessible to undergo various analyses by a Bioinformatician or Statistician who can also reanalyse datasets independently when newer analytical tools and algorithms become available. Having the datasets accessible under a single resource will also permit comparisons and/or combining of similar datasets on which further relevant computational analytics via e[hive] (linked to via the e[catalog] resource) can be performed to provide new biological insights. Hence, addressing the current competency of the numerous computational analysis tools can therefore ensure that the best ones are streamlined and selected for activation within the e[hive] pipeline.
The simple click of the "Analyses" button within each Study of the e[catalog] resource will provide authority to the scientists themselves to seamlessly perform meaningful computational analyses on their own datasets, without the need to rely on other people or external analytical service providers.