What is Data (DataONE Perspective)?

This document describes the concept of “data” within the first iteration of the DataONE system.


Data, in the context of DataONE, is a discrete unit of digital content that is expected to represent information obtained from some experiment or scientific study. The data is accompanied by science metadata, which is a separate unit of digital content that describes properties of the data. Each unit of science data or science metadata is accompanied by a system metadata document which contains attributes that describe the digital object it accompanies (e.g. hash, time stamps, ownership, relationships).

In the initial version of DataONE, science data are treated as opaque sets of bytes and are stored on Member Nodes (MN). A copy of the science metadata is held by the Coordinating Nodes (CN) and is parsed to extract attributes to assist the discovery process (i.e. users searching for content).

The opaqueness of data in DataONE is likely to change in the future to enable processing of the data with operations such as translation (e.g. for format migration), extraction (e.g. for rendering), and merging (e.g. to combine multiple instances of data that are expressed in different formats). Such operations rely upon a stable, accessible framework supporting reliable data access, and so are targeted after the initial requirements of DataONE are met and the core infrastructure is demonstrably robust.

Data Packaging provides a more complete description of data, science metadata, and system metadata and their relationship to one another.

Metadata Types

The following metadata formats are of interest to the DataONE project for the initial version and are representative of the types of content that will need to be stored and parsed.

In all cases the descriptive text was retrieved from the URL provided with the description, and so where there is discrepancy, the referenced location (or the currently authoritative location) takes precedence.

Types of science metadata and their corresponding SystemMetdata.ObjectFormat identifier.


Object Format

Dublin Core


Darwin Core



  • eml://ecoinformatics.org/eml-2.0.0

  • eml://ecoinformatics.org/eml-2.0.1

  • eml://ecoinformatics.org/eml-2.1.0






ISO 19137


Water ML

Genbank internal format

ISO 19115

INCITS 453-2009

Dryad Application Profile


GML Profiles


  • CF-1.0

  • CF-1.1

  • CF-1.2

  • CF-1.3

  • CF-1.4

NetCDF Classic and 64-bit offset formats


NetCDF-4 and netCDF-4 classic model formats








Dryad METS


Dublin Core

The Dublin Core Metadata Element Set is a vocabulary of fifteen properties for use in resource description.

Darwin Core

The Darwin Core is body of standards. It includes a glossary of terms (in other contexts these might be called properties, elements, fields, columns, attributes, or concepts) intended to facilitate the sharing of information about biological diversity by providing reference definitions, examples, and commentaries. The Darwin Core is primarily based on taxa, their occurrence in nature as documented by observations, specimens, and samples, and related information. Included are documents describing how these terms are managed, how the set of terms can be extended for new purposes, and how the terms can be used. The Simple Darwin Core [SIMPLEDWC] is a specification for one particular way to use the terms - to share data about taxa and their occurrences in a simply structured way - and is probably what is meant if someone suggests to “format your data according to the Darwin Core”.


The Ecological Metadata Language (EML) is a metadata specification developed by the ecology discipline and for the ecology discipline. It is based on prior work done by the Ecological Society of America and associated efforts (Michener et al., 1997, Ecological Applications). EML is implemented as a series of XML document types that can by used in a modular and extensible manner to document ecological data. Each EML module is designed to describe one logical part of the total metadata that should be included with any ecological dataset.


The Content Standard for Digital Geospatial Metadata (CSDGM), Vers. 2 (FGDC-STD-001-1998) is the US Federal Metadata standard. The Federal Geographic Data Committee (FGDC) originally adopted the CSDGM in 1994 and revised it in 1998. According to Executive Order 12096 all Federal agencies are ordered to use this standard to document geospatial data created as of January, 1995. The standard is often referred to as the FGDC Metadata Standard and has been implemented beyond the federal level with State and local governments adopting the metadata standard as well.

(word document available for descriptions, Matt has XSD of FGDCbio)
(Excel spreadsheet listing mapping,
 xslt: EML->FGDC (lossy), FGDC->EML)
(mapping available for EML -> DC (Duane))


The DIF does not compete with other metadata standards. It is simply the “container” for the metadata elements that are maintained in the IDN database, where validation for mandatory fields, keywords, personnel, etc. takes place.

The DIF is used to create directory entries which describe a group of data. A DIF consists of a collection of fields which detail specific information about the data. Eight fields are required in the DIF; the others expand upon and clarify the information. Some of the fields are text fields, others require the use of controlled keywords (sometimes known as “valids”).

The DIF allows users of data to understand the contents of a data set and contains those fields which are necessary for users to decide whether a particular data set would be useful for their needs.

ISO 19137


ISO 19137:2007 defines a core profile of the spatial schema specified in ISO 19107 that specifies, in accordance with ISO 19106, a minimal set of geometric elements necessary for the efficient creation of application schemata.

It supports many of the spatial data formats and description languages already developed and in broad use within several nations or liaison organizations.



The NEXUS file format is a commonly used format for phylogenetic data. Unfortunately, over time, the format has become overloaded - which has caused various problems. Meanwhile, new technologies around the XML standard have emerged. These technologies have the potential to greatly simplify, and improve robustness, in the processing of phylogenetic data.

Water ML


The Water Markup Language (WaterML) specification defines an information exchange schema, which has been used in water data services within the Hydrologic Information System (HIS) project supported by the U.S. National Science Foundation, and has been adopted by several federal agencies as a format for serving hydrologic data. The goal of WaterML was to encode the semantics of hydrologic observation discovery and retrieval and implement water data services in a way that is both generic and unambiguous across different data providers, thus creating the least barriers for adoption by the hydrologic research community.

ISO 19115

ISO 19115 “Geographic Information - Metadata” is a standard of the International Organization for Standardization (ISO). It is a component of the series of ISO 191xx standards for Geospatial metadata. ISO 19115 defines how to describe geographical information and associated services, including contents, spatial-temporal purchases, data quality, access and rights to use. The standard defines more than 400 metadata elements and 20 core elements.

  • NA profile

  • bio profile

  • marine community metadata profile

  • WMO profile

Dryad Metadata Profile


The Dryad metadata team has developed a metadata application profile based on the Dublin Core Metadata Initiative Abstract Model (DCAM) following the Dublin Core guidelines for application profiles. The Dryad metadata profile is being developed to conform to the Dublin Core Singapore Framework, a framework aligning with Semantic Web development and deployment.


The purpose of the ADN (ADEPT/DLESE/NASA) metadata framework is to describe resources typically used in learning environments (e.g. classroom activities, lesson plans, modules, visualizations, some datasets) for discovery by the Earth system education community.

GML Profiles

GML profiles are logical restrictions to GML, and may be expressed by a document, an XML schema or both.


The Data Documentation Initiative is an international effort to establish a standard for technical documentation describing social science data. A membership-based Alliance is developing the DDI specification, which is written in XML.


The MicroArray and Gene Expression (MAGE) provides a standard for the representation of microarray expression data that would facilitate the exchange of microarray information between different data systems.


The Earth Science Markup Language (ESML) is a interchange standard that supports the description of both syntactic (structural) and semantic information about Earth science data. Semantic tags provide linking of different domain ontologies to provide a complete machine understandable data description.


The Cruise Summary Report (CSR), previously known as ROSCOP (Report of Observations/Samples Collected by Oceanographic Programmes), is an established international standard designed to gather information about oceanographic data. ROSCOP was conceived in the late 1960s by the IOC to provide a low level inventory for tracking oceanographic data collected on Research Vessels.

The ROSCOP form was extensively revised in 1990, and was re-named CSR (Cruise Summary Report), but the name ROSCOP still persists with many marine scientists. Most marine disciplines are represented in ROSCOP, including physical, chemical, and biological oceanography, fisheries, marine contamination/pollution, and marine meteorology. The ROSCOP database is maintained by ICES


A metadata specification for representing the contextual and environmental information associated with marker gene data sets collected in the environment. The MIENS specification extends the MIGS/MIMS specification.

Additional specifications in use by relevant agencies

ISO 2146

ISO 2146 (Registry Services for Libraries and Related Organisations) is an international standard currently under development by ISO TC46 SC4 WG7 to operate as a framework for building registry services for libraries and related organizations. It takes the form of an information model that identifies the objects and data elements needed for the collaborative construction of registries of all types. It is not bound to any specific protocol or data schema. The aim is to be as abstract as possible, in order to facilitate a shared understanding of the common processes involved, across multiple communities of practice.

Used by the Australian National Data Service (ANDS) for describing data collections in ANDS, which for many Australian data sets corresponds to the concept of a ‘data set’ used here. The term ‘collection’ is loosely defined so that different disciplines can apply it appropriately.

See: http://www.nla.gov.au/wgroups/ISO2146/ Schema: http://www.nla.gov.au/wgroups/ISO2146/n198.xsd

ANZLIC Metadata Profile

A profile of ISO 19115 for Australia. See: http://www.osdm.gov.au/ANZLIC_MetadataProfile_v1-1.pdf?ID=303

Identifying Metadata Types

It is a requirement (#384) of DataONE that users are able to search the holdings, and so a mechanism for indexing the content and therefore a mechanism for specifying how to retrieve attribute values from the different science metadata formats is required. This in turn requires that the system is able to accurately determine the format of the metadata in order to utilize the correct parser for extracting the necessary attribute values for indexing. Potential resources may be found at:


Data and science metadata are immutable for the first version of the DataONE system. As such, resolving the identifiers assigned to the data or the science metadata will always resolve to the same stream of bytes.


Byte stream equivalence of replicated science metadata would require that MNs record an exact copy of the metadata document received during replication operations in addition to the content that would be extracted and stored as part of the normal (existing) operations of a MN. Is this a reasonable requirement for MNs? Since MNs are required to store a copy of data, it seems reasonable to assume a copy of the metadata can be stored as well.

The DataONE CN_crud.update() method will fail if attempting to modify an instance of science data.

Deletion of content is only available to DataONE administrators (perhaps a curator role is required?).


Define the procedures for content deletion - who is responsible, procedures for contacting authors, timeliness of response.

Data Endianness

The data component of a DataONE package is opaque to the DataONE system (though this may change in the future), and so the endianness of the content does not affect operations except that it must be preserved. However, processing modules may utilize content from DataONE and may be sensitive to the byte ordering of content. As such, the endianness of the data content should be recorded in the user supplied metadata (the science metadata), and where not present SHOULD be assumed to be least significant byte first (LSB, or small-endian).


Describe how endianness is specified in various science metadata formats.


An original copy of the data is maintained for a long as practicable (ideally, the original content is never deleted). Derived copies of content, such as might occur when a new copy of a data object is created to migrate to a different binary format (e.g. an Excel 1.0 spreadsheet translated to Open Document Format) always create a new data object that will be noted as an annotation recorded in the system metadata of the data package.

Metadata Character Encoding

All metadata, including the science metadata and DataONE package metadata MUST be encoded in the UTF-8 encoding. The DataONE CN_crud.create() and CN_crud.update() methods always expect UTF-8 encoded information, and so content that contains characters outside of the ASCII character set should be converted to UTF-8 through an appropriate mechanism before adding to DataONE.

Metadata Minimal Content

Experiment metadata MUST contain a minimal set of fields to be accepted by the DataONE system.


List and define the minimal set of fields with examples. A starting point would be the union of the required search properties and the information required for accurate citation.