Generation Challenge Programme (GCP): Standards for Crop Data

Abstract. -Darwin Core (DwC) defines a standard set of terms to describe the primary biodiversity data. Primary biodiversity data are data records derived from direct observation of species occurrences in nature or describing specimens in biological collections. The Darwin Core terms can be seen as an extension to the standard Dublin Core metadata terms. The new Darwin Core extension for genebanks declares the additional terms required for describing genebank data sets, and is based on established standards from the plant genetic resources community. The Global Biodiversity Information Facility (GBIF) provides an information infrastructure for biodiversity data including a suite of software tools for data publishing, distributed data access, and the capture of biodiversity data. The Darwin Core extension for genebanks is a key component that provides access for the genebanks and the plant genetic resources community to the GBIF informatics infrastructure including the new toolkits for data exchange. This paper provides one of the first examples and guidelines for how to create extensions to the Darwin Core standard.Keywords. -Darwin Core; Darwin Core extension; GBIF; genebank collections; germplasm; plant genetic resources.There are more than 1750 genebanks distributed all around the world, with more than 130 large and medium-size genebank collections holding more than 10,000 accessions each (FAO, 2010). Each of these genebanks maintains living material of plant genetic resources. New accessions are added to the genebank collections from collecting expeditions and from old cultivars obsolete to the commercial seed trade. The genebank documentation systems are continuously being extended with new accessions and with updated information on existing accessions.The International Treaty on Plant Genetic Resources for Food and Agriculture 1 (ITPGRFA; FAO, 2009, page 29, Article 17.1) calls for building a global information system on plant genetic resources for food and agriculture. Such a system needs to be frequently refreshed with new and updated information from each genebank collection (and other information sources such as inventories of crop wild relatives). With modern information technology, a distributed information system can be designed to allow extracting a snapshot of the decentralized genebank data sets at any time. Moreover, a distributed germplasm information system will make updated germplasm information * Corresponding author; email: dag.endresen@gmail.com. 1 http://www.planttreaty.org/.more easily accessible to plant breeders, crop scientists and other users, thus providing better access also to the plant material. The lack of easy access to germplasm information remains an important bottleneck for utilization of plant genetic resources material . The Global Biodiversity Information Facility (GBIF) 2 has developed a software toolkit for publishing decentralized biodiversity data sets, known as the "Integrated Publishing Toolkit" (GBIF IPT) 3 . It provides a successful example of a software tool ...

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“…The GCP includes a theme for advanced research on crop information systems and bioinformatics (Bruskiewich et al, 2006; …”

Section: Generation Challenge Programme (Gcp)mentioning

confidence: 99%

“…The GCP includes a theme for advanced research on crop information systems and bioinformatics (Bruskiewich et al, 2006; with research data sets published by the project partners using the BioCASE data publishing toolkit.…”

Section: Generation Challenge Programme (Gcp)mentioning

confidence: 99%

The Darwin Core extension for genebanks opens up new opportunities for sharing genebank datasets

Endresen

Knüpffer

2012

Biodiv. Inf.

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“…The CO, along with the GCP domain model (Bruskiewich et al , 2006, 2008) and associated Pantheon software, provides a common semantic and software framework for global integration of data across diverse community protocols. Generation Challenge Programme's semantics are designed to be extensible, and to allow for the addition of new semantics and novel data types as the needs of crop researchers evolve.…”

Section: Conclusion and Forward Lookmentioning

confidence: 99%

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature

et al. 2010

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“…The phenotyping system is based on a modified entity-value database model of the Generation Challenge Program Domain Model (Bruskiewich et al, 2006). The scored object, which can be a single plant or a plot, is identified by the combination of the name of the database table and the primary key of the observation that contains the information on the scored object.…”

Section: Database Modelmentioning

confidence: 99%

A tool for efficient data collection based on controlled vocabulary and the entity-value model

Koehl

2007

J. Verbr. Lebensm.

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Large-scale monitoring projects involving small enterprises and academia require data collection and management systems that are easy to implement and open to alteration within the project. For the Agrikola project, a barcode-scanner-based technique was developed to collect data based on controlled vocabulary and the entity-value model. The database model links a scored object to one or many entities, which likewise are linked to one or many values. As type and number of entities or values are not predefined, the same database model can be used for different scoring programs. Identification of entity and value terms by the primary key of their database table allows editing and multilanguage versions of the term's text. For on-site scoring, primary keys are converted into barcodes arranged on score sheets. In the field, data are collected with portable barcode-scanner-units with tailored data collection workflows. A miniature database in the scanner-unit checks and converts the barcode into clear text. Data exported as CSV-file can be imported into spreadsheets or, using XML-interfaces, database systems. Thus, data are rapidly and reliably available for evaluation and distribution to collaborators.

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Generation Challenge Programme (GCP): Standards for Crop Data

Cited by 17 publications

References 7 publications

The Darwin Core extension for genebanks opens up new opportunities for sharing genebank datasets

The Darwin Core extension for genebanks opens up new opportunities for sharing genebank datasets

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature

A tool for efficient data collection based on controlled vocabulary and the entity-value model

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