DMP linkable icons
| References |
Policy context
G8 adoption of the Open Data Charter in 2013. Available at: http://opendatacharter.net
G20 anti-corruption Open Data Principles in 2015. Available at: www.g20.utoronto.ca/2015/G20-Anti-Corruption-Open-Data-Principles.pdf
Mexico Plenary/Ministerial: EX: Art 10 and 11. Available at: www.earthobservations.org/min_declaration.php
UN Committee of Experts on Global Geospatial Information Management (UN-GGIM). Available at: http://ggim.un.org
Re-use of UK governamental datasets: Data.gov.uk
GEO
GEO (2012). What is GEOSS?: The Global Earth Observation System of Systems. Available at: http://www.earthobservations.org/geoss.php
Science & Technology Committee (2010). The GEO Science and Technology Roadmap. Available at: http://www.earthobservations.org/documents/committees/stc/201104_16thSTC/stc_roadmap_v1_1_11122010.pdf
GEO label
Oficial website: http://www.geolabel.info/home.htm
PhD of Victoria Luch:
Condensed information about the GeoViQua label:
A tool for automatically creating a GEOlabel associated to a dataset:
http://www.geolabel.net/demo.html
GeoViQua project deliverable D6.2 Geo Label description final document. GeoViQua deliverables: http://www.geoviqua.org/Documents.htm
Nust D. and Lush V (2015) A GEO label for the Sensor Web:
https://agile-online.org/Conference_Paper/cds/agile_2015/shortpapers/115/115_Paper_in_PDF.pdf
Lush V., Bastin L., Lumsden J. (2013) Developing a Developing a Developing a Developing a GEO Label:
http://www.geos.ed.ac.uk/~gisteac/proceedingsonline/GISRUK2013/gisruk2013_submission_44.pdf
Plag HP. (2013) Labeling Geo-Referenced Information in Support of Data Sharing and the Facilitating of Societal Benefits of Earth Observations:
http://www.e3s-conferences.org/articles/e3sconf/pdf/2013/01/e3sconf_ichm13_28004.pdf
Data Management Principles
GEOSS Data Management Principles:
https://www.earthobservations.org/documents/dswg/201504_data_management_principles_long_final.pdf
Data Management Principles Implementation Guidelines:
Data Management Principles Implementation Guidelines revision June 2022:
DMP-3
Fulker, D. and Gallagher, J. (2013) Extending OPeNDAP to Offer Remapping Services. Geophysical Research Abstracts. [Online] EGU2013-10236, 2013 EGU General Assembly 2013. 15.
GCOS. (2015) GCOS Essential Climate Variable (ECV) Data Access Matrix. [Online]
GeoJSON. (2015) The GeoJSON Format Specification. [Online]
Hefflin, J. and Hendler, J. (2000) Semantic Interoperability on the Web. Extreme Markup Languages 2000, August 15-18, Montreal, Canada. [Online].
Hugo, W. (2009) Meta-Data Implementation For The Environmental Sciences: Options, Benefits And Issues - Saeon Case Study. African Digital Scholarship and Curation Conference, 12-14 May 2009. [Online].
Hugo, W. (2008) Beyond Spatial Data Infrastructure: Knowledge And Process Extensions. Ecological Circuits. [Online] 2 (2008). p.25.
OGC. (2007) OpenGIS® Geography Markup Language (GML) Encoding Standard. [Online]
OGC. (2007) OGC Validator. [Online]
OGC. (2008) OGC® KML. [Online]
OGC. (2011) OGC® SWE Common Data Model Encoding Standard. [Online]
OGC. (2014) OGC® SensorML: Model and XML Encoding Standard. [Online]
OGC. (2015) OGC Network Common Data Form (netCDF) Standards Suite. [Online]
OGC. (2015) OGC® WaterML. [Online]
OOPC. (2015) Essential Variables. [Online]
TDWG. (2015) TDWG Standards. [Online]
WMO. (2015) WMO Information System. [Online]
DMP-4
ISO 19115:
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a. ISO 19115-1: 2014 Geographic information -- Metadata -- Part 1: Fundamentals
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b. ISO 19115-2: 2009 Geographic information -- Metadata -- Part 2: Extensions for imagery and gridded data
ISO 19139:2007 Geographic information -- Metadata -- XML schema implementation:
ISO 19157:2013 Geographic information -- Data quality
ISO/TS 19139:2007 Geographic information -- Metadata -- XML schema implementation
Directory Interchange Format (DIF) Standard
DMP-5
Isuru Suriarachchi (2015) Survey of Provenance Practices in Data Preservation Repositories. Research Data Alliance: https://rd-alliance.org/filedepot_download/767/632
GeoNetwork4MetaViz – Enabling an open source metadata catalogue to visualize lineage information (2015): http://geoportal-glues.ufz.de/documents/Fact_Sheet_MetaViz.pdf
Demir, I.; Mills, H.; Oh, J.; et. al. (2015), Geoscience Papers of the Future: The Importance of Software Sharing for Science Reproducibility. Presented at EarthCube All Hands Meeting, Washington, DC, 27-29 May 2015: http://earthcube.org/document/2015/geoscience-papers-future.
DMP-6
Callahan S. 2015. Data without Peer: Examples of Data Peer Review in the Earth Sciences. D-Lib Magazine, 21(1/2). http://dx.doi.org/10.1045/january2015-callaghan
Peer L, Green A, Stephenson E. 2014. Committing to Data Quality Review. International Journal of Digital Curation, 9(1), 263-291 http://dx.doi.org/10.2218/ijdc.v9i1.317.
DMP-8
CEOS EO Data Preservation Guidelines.
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- Keeping Research Data Safe (KRDS) Project: http://www.beagrie.com/krds.php
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- Activity Based Costing (ABC) methodology;
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- Angus Whyte and Andrew Wilson. Appraise & Select Research Data for Curation. Digital Curation Centre and Australian National Data Service “working level” guide, 25 October 2010: http://www.dcc.ac.uk/resources/how-guides/appraise-select-data
DMP-9
Plato L. Smith II Exploring Data Curation and Management Programs, Projects, and Services through Metatriangulation (2012).
Brown, A., 2006a. Automatic Format Identification Using PRONOM and DROID, The National Archives].
C.M. Sperberg-McQueen, What Constitutes Successful Format Conversion? Towards a Formalization of `Intellectual Content´, in The International Journal of Digital Curation Issue 1, Volume 6 (2011).
As defined in the Oxford Glossary or Common Definitions.
See M. T. Borzacchiello & M. Craglia, Socio-Economic Benefits from the Use of Earth Observation (Report from the International Workshop held at Joint Research Center, Ispra, 11-13 July 2011), available at: http://ies.jrc.ec.europa.eu/uploads/SDI/publications/EOBenefitWS_JRCTechReport_final.pdf; or, concerning format conversions, -see C.M. Sperberg-McQueen, 2011, What Constitutes Successful Format Conversion?). See also C.M. Sperberg-McQueen, What Constitutes Successful Format Conversion? Towards a Formalization of ‘Intellectual Content, The International Journal of Digital Curation Issue 1, Volume 6 (2011).
Conway, Esther, Sam Pepler, Wendy Garland, David Hooper, Fulvio Marelli, Luca Liberti, Emanuela Piervitali, Katrin Molch, Helen Glaves, and Lucio Badiali. Ensuring the Long Term Impact of Earth Science Data through Data Curation and Preservation. Information Standards Quarterly, Fall 2013, 25(3): 28-36. http://www.niso.org/publications/isq/2013/v25no3/conway/ .
Curation and reprocessing examples
See the process of reanalyzing undertaken by the Analysis Centers (ACs) of the IGS of the full history of GPS data collected by the IGS global network since 1994 in a fully consistent way using the latest models and methodology. [IGS: the International GNSS Service GNSS: Global Navigation Satellite System] http://acc.igs.org/reprocess.html .
On the reprocessing of atmospheric chemistry Ether data website: http://www.poleether.fr/etherTypo/index.php?id=1678&L=1 .
On seismic data reprocessing: http://www.searcherseismic.com/our-services/2d--3d-seismic-datareprocessing.htm .
And, in particular, on the reprocessing of Multi-channel Seismic-Reflection Data Collected in the Beaufort Sea http://pubs.usgs.gov/of/2000/ofr-00-460/ .
Most of NASA satellite mission data are reprocessed multiple times with improvements made each time. This results in multiple versions (variously referred to as Collection, Version or Edition) of data products. For example, see: 1.- http://oceancolor.gsfc.nasa.gov/cms/REPROCESSING; 2.- https://daac.ornl.gov/MODIS/MODIS-menu/reprocessing.html ; 3.- http://disc.sci.gsfc.nasa.gov/Aura/data-holdings/MLS/index.shtml ; 4.- https://earthdata.nasa.gov/modis-terra-collection-6-aerosol-cloud-and-other-atmosphericlevel-2-and-level-3-products-released ;
On sea ice data reprocessing: http://nsidc.org/data/nsidc-0508 https://climatedataguide.ucar.edu/climate-data/sea-ice-concentration-data-reprocessed-ssmr-ssmieumetsat .
On the 2010-2013 ESA reprocessing campaign of all the SMOS (Soil Moisture and Ocean Salinity) data: http://cp34-bec.cmima.csic.es/ocean-reprocessed-dataset/
On the Landsat 8 data held in the USGS archives reprocessing, introducing corrections affecting both the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS): http://landsat.gsfc.nasa.gov/?p=7435 .
On the ESA Landsat 5 Reprocessing, see Alessandra Paciucci et al, Landsat 5 Reprocessing: Case Study Into Reprocessing and Data Configuration 4-11-2013.
On the reprocessing of global vegetation images: http://proba-v.vgt.vito.be/content/reprocessingproba-v-data-finalized.
On NOAA´s project on AVHRR (Advanced Very High Resolution Radiometer) reprocessing in TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long - Term Dynamics In our Natural Environment): see Katrin Molch et al, NOAA AVHRR Data Curation and Reprocessing - TIMELINE (2013), and for Europe and North Africa, C.M. Frey C. et al, (2015) AVHRR re-processing over Europe and North Africa. 36th International Symposium on Remote Sensing of Environment, 11-15 May, Berlin, Deutschland.
DMP-10
Ball, A. & Duke, M. (2012). ‘How to Cite Datasets and Link to Publications’. DCC How-to Guides. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/how-guides .
Joint Declaration of Data Citation Principles https://www.force11.org/group/joint-declaration-datacitation-principles-final .
San Francisco Declaration on Research Assessment (DORA) [http://www.ascb.org/dora/]
Starr J, Castro E, Crosas M, Dumontier M, Downs RR, Duerr R, Haak LL, Haendel M, Herman I, Hodson S, Hourclé J, Kratz JE, Lin J, Nielsen LH, Nurnberger A, Proell S, Rauber A, Sacchi S, Smith A, Taylor M, Clark T. (2015) Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Computer Science 1:e1 https://dx.doi.org/10.7717/peerj-cs.1
Tonkin, E. (2008) ‘Persistent Identifiers: Considering the Options’ Ariadne Issue 56 http://www.ariadne.ac.uk/issue56/tonkin/
Current GEO Recommendations, GEOSS Data Citation Guidelines: Version 2 http://www.gstss.org/library/GEOSS_Data_Citation_Guidelines_V2.0.pdf
DCC Guide, ‘How to Cite Datasets’, provides summary of minimal information for data citations, explanations of DOIs, discusses current issues (including granularity) and implementation issues (including versioning in the context of time series data): http://www.dcc.ac.uk/resources/howguides/cite-datasets
DataCite Metadata Schema v 3.1: https://schema.datacite.org/meta/kernel-3/index.html
Assigning identifiers to different versions of a dataset, particularly for time series data
Dryad DOI Usage: http://wiki.datadryad.org/DOI_Usage
UKDA Approach to Persistent Identifiers and Versioning: http://www.bl.uk/aboutus/stratpolprog/digi/datasets/workshoparchive/LousieCortin_IdentifiersForThe UKDA_May2012.pdf
Assigning identifiers and citing data (subsets) created dynamically by database queries
Recommendations from Research Data Alliance Working Group on Data Citation:
https://rdalliance.org/filedepot/folder/262?fid=667 Re: machine accessibility of cited data by mean of a persistent and unique identifier.
Clark et al. 2015 ‘Achieving human and machine accessibility of cited data in scholarly publications’ https://dx.doi.org/10.7717/peerj-cs.1