Paper Info
Title
Meta-omics data and collection objects (MOD-CO): a conceptual schema and data model for processing sample data in meta-omics research.
Abstract
With the advent of advanced molecular meta-omics techniques and methods, a new era commenced for analysing and characterizing historic collection specimens, as well as recently collected environmental samples. Nucleic acid and protein sequencing-based analyses are increasingly applied to determine the origin, identity and traits of environmental (biological) objects and organisms. In this context, the need for new data structures is evident and former approaches for data processing need to be expanded according to the new meta-omics techniques and operational standards. Existing schemas and community standards in the biodiversity and molecular domain concentrate on terms important for data exchange and publication. Detailed operational aspects of origin and laboratory as well as object and data management issues are frequently neglected. Meta-omics Data and Collection Objects (MOD-CO) has therefore been set up as a new schema for meta-omics research, with a hierarchical organization of the concepts describing collection samples, as well as products and data objects being generated during operational workflows. It is focussed on object trait descriptions as well as on operational aspects and thereby may serve as a backbone for R&D laboratory information management systems with functions of an electronic laboratory notebook. The schema in its current version 1.0 includes 653 concepts and 1810 predefined concept values, being equivalent to descriptors and descriptor states, respectively. It is published in several representations, like a Semantic Media Wiki publication with 2463 interlinked Wiki pages for concepts and concept values, being grouped in 37 concept collections and subcollections. The SQL database application DiversityDescriptions, a generic tool formaintaining descriptive data and schemas, has been applied for setting up and testing MOD-CO and for concept mapping on elements of corresponding schemas.
Year
DOI
Venue
2019
10.1093/database/baz002
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Field
DocType
Volume
Data mining,Mod,Conceptual schema,Information retrieval,Computer science,Omics,Data model
Journal
2019
ISSN
Citations 
PageRank 
1758-0463
0
0.34
References 
Authors
6
8
Name
Order
Citations
PageRank
Gerhard Rambold121.59
Pelin Yilmaz21129.17
Janno Harjes300.34
Sabrina Klaster400.34
Veronica Sanz500.34
Anton Link600.34
Frank Oliver Glöckner726721.70
Dagmar Triebel8173.10