Editing BioMicro:NextSEEK (section)

== NExtSEEK ==

While SEEK met a lot of our needs, there were still some features we wanted to implement. Therefore, we created NExtSEEK, an implementation of SEEK that supports many of the original data storage and sharing resources. Similar to SEEK, NExtSEEK stores samples in tables and protocols in documents. The main difference is that experimental assays act as a connector between data samples. For example, in the diagram below, the mouse sample type is connected to the DNA library sample type with the ear punch assay, as the library was extracted from the mice via an ear punch. The overall sample types in NExtSEEK are connected by assays, while the individual samples are connected to the samples directly upstream and downstream using the “parent” metadata attribute. In the situation above, all of the DNA libraries would be connected to the specific mouse that they were extracted from. All of these connections result in a diagram that outline the workflow of the entire experiment, including the different data types that were generated and the protocols used to do so. 

[[File:DMAC2.png|left|350px]]

[[File:DMAC3.png|500px]]




The generalizability of NExtSEEK data storage makes it simple to transfer the data to our public repository, FAIRDOMHub, or another external repository. Additionally, the flexibility of the system makes it easy to add more sample types if we do not already provide support for storing it.


[[File:Nextseekarchitecture.png|left|400px]]

[[File:DMAC1.png|500px]]



Storing rich metadata in NExtSEEK can also allow for new findings, as it theorized that combining multiple datasets can lead to new discoveries. For example, by working with the IMPAcTB consortium, we can collect all of the different types of experimental data, with the hopes that these single omics datasets could potentially be combined into a multi-omic approach across multiple different datasets, to discover something that would not have been possible if not. This is phrased as “meta-analysis” across multiple scientific studies, often times performed by different researchers. This would not be possible if we did not have a well curated database with rich metadata describing the samples that span the different studies. Additionally, NExtSEEK allows users to query based on metadata values, allowing scientists to focus on specific groups of data.


For those interested in learning more about the technical aspects of NExtSEEK and the architecture of the data storage, [https://jbt.pubpub.org/pub/nextseek-interopaerable-data-management/release/1 this paper] outlines the details behind the system.