Séance 02, Le paysage de la publication des données en 2015, dans la formation GB22 pour points nodaux du GBIF
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Cette présentation décrit le scénario changeant de la publication des données sur la biodiversité, tel qu'il est en 2015. Elle était présenté pour la première fois dans la formation GB22 pour des points nodaux du GBIF. Diapos produites et présentés par L. Russell (Vertnet), traduites en Français par M. Raymond (Secrétariat GBIF).
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Similaire à Séance 02, Le paysage de la publication des données en 2015, dans la formation GB22 pour points nodaux du GBIF
Similaire à Séance 02, Le paysage de la publication des données en 2015, dans la formation GB22 pour points nodaux du GBIF (20)
Plus de Alberto González-Talaván
Plus de Alberto González-Talaván (20)
Séance 02, Le paysage de la publication des données en 2015, dans la formation GB22 pour points nodaux du GBIF
- 1. GB22 TRAINING EVENT FOR NODES – 4 OCTOBER 2015 Séance 02: Le paysage de la publication de données en 2015 Laura Russell
- 2. INDEX Le « paysage » de la publication des données La publication des données sur la biodiversité Les types de données Les normes de données La normalisation des données et la qualité des données Les méthodes de publication des données La -promotion de la publication de données Les cas d'utilisation
- 3. LE PAYSAGE DE LA PUBLICATION DES DONNÉES DiGIR / TAPIR très utilisé pour publier des données sur la biodiversité Idée de publier à base de fichier texte simple et comprimé présenté à TDWG Le GBIF lance l’ IPT 1,0 Le GBIF réaménage l’ IPT Le GBIF lance l’ IPT 2.0 La publication des données est enseigné à la formation des nœuds Le points nodaux et les agrégateurs commencent à installer et à utiliser l’ IPT Les jeux de données de type occurrence et checklist ainsi que le nombre d’installations de l’IPT montrent une croissance continue 2008 2008 2009 2010 2011 2011 2012 2011
- 4. LE PAYSAGE DE LA PUBLICATION DES DONNÉES - STATISTIQUES http://www.gbif.org/ipt/stats No. d’installations de l’IPT enregistrées avec le GBIF
- 5. LE PAYSAGE DE LA PUBLICATION DES DONNÉES - STATISTIQUES No. de jeux de données publiées avec l’IPT
- 6. LE PAYSAGE DE LA PUBLICATION DES DONNÉES EN 2015 L'engagement continue du GBIF à améliorer l'accès aux données de la biodiversité Le raffinement et l'expansion des normes et des logiciels de publication L'évolution des normes sociales La plupart des données sont encore publiées avec le « core » simple pour occurrences Les portails n’ont pas encore les fonctionnalités pour soutenir les données plus riches De nombreuses institutions ont encore besoin d’ être convaincues de publier des données sur la biodiversité http://www.gbif.org/page/82104
- 7. INDEX Le « paysage » de la publication des données La publication des données sur la biodiversité Les types de données Les normes de données La normalisation des données et la qualité des données Les méthodes de publication des données La -promotion de la publication de données Les cas d'utilisation
- 8. QU'EST-CE QUE DES DONNÉES DE BIODIVERSITÉ? Texte numérique ou donnée multimédia détaillant les faits sur l'instance d’occurrence d'un organisme, à savoir sur le quoi, où, quand, comment et par qui de l’occurrence et de l'enregistrement.
- 9. QU'EST CE LA PUBLICATION DE DONNÉES? La « publication » consiste à rendre des jeux de données de la biodiversité accessibles au public et découvrable, sous une forme standardisée, via un point d'accès, généralement une adresse Web (URL). IPT ∞
- 10. LES TYPES DE DONNÉES SUR LA BIODIVERSITÉ http://www.gbif.org/publishing-data/summary#datatypes Checklistes Occurrences Metadonnées
- 11. LES TYPES DE DONNÉES SUR LA BIODIVERSITÉ – DONNÉES D’ ÉCHANTILLONNAGE http://www.gbif.org/newsroom/news/sample-based-data Échantillonnage
- 12. LES NORMES OU “STANDARDS” http://www.tdwg.org/standards/ ABCD Access to Biological Collection Data (2005) DwC Darwin Core (2009) AC Audubon Core Multimedia Resources Metadata Schema (2013) NCD Natural Collection Descriptions (Draft)
- 13. DARWIN CORE http://rs.tdwg.org/dwc recordedBy: Une liste (concaténée et séparée) de noms de personnes, groupes ou organisations responsables de l'enregistrement de l'occurrence originale. Le collecteur ou observateur primaire, en particulier celui qui applique un identifiant personnel (RecordNumber), doit être cité en premier. Exemples: « José E. Crespo », « Oliver P. Pearson | Anita K. Pearson »
- 14. DARWIN CORE SIMPLE SIMPLEDWC est une spécification pour une façon particulière d'utiliser les termes Darwin Core - de partager des données sur les taxons et leurs occurrences avec une structure simple - et probablement ce que veux dire quelqu'un qui suggère de "formater vos données conformément à la Darwin Core". http://rs.tdwg.org/dwc/terms/simple/index.htm
- 15. LES ARCHIVES DARWIN CORE Une Archive Darwin Core (DwCA) est la représentation en texte des données formatées à Darwin Core. Une DwCA est un fichier compressé contenant un minimum de trois fichiers. http://rs.tdwg.org/dwc/terms/guides/text/index.htm
- 16. “STAR SCHEMA” OU SCHÉMA ÉTOILE Ext 2 Core Ext 1 Ext 3 meta.xml EML.xml + DwC Archive Ext 4 Ext 5
- 17. “MAPPING CORES” OU FICHIERS CENTRALES Taxon Core La catégorie d'informations relatives aux noms taxonomiques, le nom du taxon, les usages ou les concepts de taxons. Sortie en Avril 2015, cette version supprime dcterms:source and dcterms:rights, et ajoute dcterms: licence. 43 termes. Occurrence Core La catégorie d'informations relatives aux preuves d’une occurrence dans la nature, dans une collection ou dans un jeu de données (de spécimens, d’observations etc.) Sortie en July 2015, cette version supprime les terms dcterms:source, dcterms:rights, dwc:individualID, dwc:occurrenceDetails,et ajoute dcterms:license, dwc:organismQuantity, dwc:organismQuantityType, dwc:organismID, dwc:organismName, dwc:organismScope, dwc:associatedOrganisms, dwc:organismRemarks, dwc:parentEventID, dwc:sampleSizeValue, dwc:sampleSizeUnit. 169 termes. Event La catégorie des informations relatives à un événement d'échantillonnage. Sortie le 29 May 2015. 95 termes
- 18. EXTENSIONS Darwin Core ne fournit pas de termes pour chaque type de données possible. • 22 inscrits • 25 en cours de développement Exemples • Audubon Media Description (ou “Audubon Core”) • Darwin Core Identification History (historique de l’identification) • Darwin Core Measurement or Facts (measures ou faits) http://tools.gbif.org/dwca-validator/extensions.do
- 19. EXEMPLE SCHÉMA ÉTOILE - OCCURRENCE Media Occurrence Core Geographica l Determination meta.xml EML.xml + DwC Archive Occurrence Germoplas m
- 20. EXEMPLE SCHÉMA ÉTOILE - CHECKLISTES Literature Taxon Core Description Occurrences meta.xml EML.xml + DwC Archive Checklist Vernacular Distribution Types
- 21. EXEMPLE SCHÉMA ÉTOILE - ÉCHANTILLONNAGE Event Core Occurrences Measurement/Fact meta.xml EML.xml + DwC Archive SamplesRelevé
- 22. NORMALISATION DES DONNÉES Quelle est la normalisation des données? Raisons pour normaliser une base de données Formes normales http://www.essentialsql.com/get-ready-to-learn-sql-database-normalization-explained-in-simple-english/, http://databases.about.com/od/specificproducts/a/normalization.htm, http://www.dotnet-tricks.com/Tutorial/sqlserver/756N210512-Database-Normalization-Basics.html
- 23. LA QUALITÉ DES DONNÉES Encodages Outils Pourquoi travailler sur l'amélioration des données? Importance de la rétroaction http://community.gbif.org/pg/pages/view/48546/precourse-activities
- 24. MÉTHODES DE PUBLICATION DE DONNÉES la capacité technique Capacité de gestion de données Créer vos propres DwCa Publier avec des tableurs centre d'hébergement de données
- 25. MÉTHODES DE PUBLICATION DE DONNÉES
- 26. MÉTHODES DE PUBLICATION DE DONNÉES – PREMIER SONDAGE Sondage: http://etc.ch/dQ68 Résultats: http://directpoll.com/r?XDbzPBd3ixYqg8RE6D9gU3CMFoU9fqOuh9n0P5P6 Quelles des méthodes suivantes avez-vous déjà utilisées pour publier des données en ligne?
- 27. MÉTHODES DE PUBLICATION DE DONNÉES - SONDAGES Cet exercice sera expliqué dans la séance
- 28. MÉTHODES DE PUBLICATION DE DONNÉES – DEUXIÈME SONDAGE Sondage: http://etc.ch/re74 Résultats: http://directpoll.com/r?XDbzPBd3ixYqg8xmOHP25WFCV81TJYwb1aGgrVyX5 Quelles des méthodes suivantes utilisez-vous régulièrement à publier des données en ligne? (à savoir l'année dernière)
- 29. INDEX Le « paysage » de la publication des données La publication des données sur la biodiversité Les types de données Les normes de données La normalisation des données et la qualité des données Les méthodes de publication des données La promotion de la publication de données Les cas d'utilisation
- 30. PROMOTION DE LA PUBLICATION DE DONNÉES Sujet de discussion lors de la formation de nœuds à Berlin en 2013. Elément clé du travail quotidien de gestionnaires de points nodaux.
- 31. PROMOTION DE LA PUBLICATION DE DONNÉES Obstacles psychologiques et culturels 1. Manque de connaissance 2. Manque de compréhension 3. Manque de volonté 4. Valeur perçue des données 5. Questions de confidentialité 6. Absence d’autorisation 7. Manque de temps / planning 8. Manque de moyens 9. Manque de fonds 10. Manque d’infrastructures http://www.gbif.org/publishing-data/benefits, http://www.gbif.org/resource/81196 Obstacles institutionnels Obstacles liés aux ressources Obstacles pratiques
- 32. NIVEAUX DE RESTRICTION DE DONNÉES 1. Refus de partager. 2. Refus de partager jusqu'à ce que l'utilisation. prévue des données soit terminée. 3. Partage payant des données. 4. Partage des données avec des restrictions. 5. Partage libre des données.
- 33. PROMOTION DE LA PUBLICATION DE DONNÉES - STRATÉGIES 1. Faciliter l'accès à un soutien financier. 2. Appel à des engagements ou des mandats légaux. 3. Appel à un accès ouvert/principes moraux. 4. Montrer les avantages d'une meilleure gestion des données. 5. Montrer les avantages pour les carrières scientifiques. 6. Pression des pairs 7. Démarrer/soutenir de grands programmes de numérisation. 8. Démarrer/soutenir les efforts de rapatriement des données.
- 34. PROMOTION DE LA PUBLICATION DE DONNÉES - DISCUSSIONS Stratégies • Commencez petit - seulement les méta-données • Promotion du fait qu’avec une seule publication au GBIF les données seront ensuite exposées dans de multiples réseaux • Fournir des IPTs hébergés pour éliminer les barrières technique • Illustrer des licences avec des exemples éloquents. • Promouvoir et organiser des formations sur les « data papers » Défis • Ne pas voulant publier / ne pas voulant publier toutes les données • Exigences/ capacities techniques pour utliser l’IPT • Licences restrictives des données http://community.gbif.org/pg/forum/topic/48616/precourse-activity-promoting-data-publishing/
- 35. INDEX Le « paysage » de la publication des données La publication des données sur la biodiversité Les types de données Les normes de données La normalisation des données et la qualité des données Les méthodes de publication des données La -promotion de la publication de données Les cas d'utilisation
- 36. CAS D’UTILISATION - INTRODUCTION Explorez quatre cas d'utilisation basés sur de pratiques de publication actuelles • Littérature • Données d'observation • Collections d'histoire naturelle • Checklistes Remplir deux exercices • Définition des stratégies de publication • Publier des jeux de données
- 37. CAS D’UTILISATION: DONNÉES À BASE DE LITERATURE Blue Group
- 38. CAS D’UTILISATION 2: DONNÉES D’OBSERVATIONS Green Group Red Group
- 39. CAS D’UTILISATION 3: DONNÉES DE COLLECTION D’HISTOIRE NATURELLE Yellow Group
- 40. CAS D’UTILISATION 4: CHECKLISTES TAXONOMIQUES Purple Group
- 41. GB22 TRAINING EVENT FOR NODES – 4 OCTOBER 2015 Séance 02: Le paysage de la publication de données en 2015 Laura Russell
Notes de l'éditeur
- Image from Piotr Lewandowski, shared via http://www.freeimages.com/photo/learning-with-pencil-1415671
- Data/chart provided by Kyle Braak, GBIF.
- Data/chart provided by Kyle Braak, GBIF.
- Good and needs improvement The data publishing area is in continuous evolution and expansion. The standards are refined and expanded, the software is improved and debugged, the social norms evolve. That requires that we all recycle our knowledge periodically. Despite biodiversity data publication in a standard way is possible for a long time now, most of the data is still published in a very simple way: just the occurrence core, single identifications, few/no connections among objects, simple metadata... Much richness of the original data is still non accessible because of the way data is published. This is one of the main reasons to organize this course. · The data already published determines (although only to a certain extent) the technical developments in the GBIF network, namely in GBIF.org and its API. Only when a certain amount of data of certain type is published (e.g. through an extension), the priority to enable discovery and retrieval of that information raises in importance. Examples of this is the indexing of occurrences published using the occurrence extension of the taxon core, and the possibility to search and retrieve images from the simple multimedia extension. Most data still published with simple occurrence core and is missing the known richness of the original data Without the rich data, portal developers do not have the priority to enhance with features to support rich data
- Reused slide from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Modified from Reused slide from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 Review of the data types for publishing (http://www.gbif.org/publishing-data/summary#datatypes). This will be the first attempt to cover the instructional objectives 1a, 1b & 1c. GBIF now deals with four types of biodiversity data: Occurrences (observations, specimens etc) Checklists (names) Metadata (data about data) - http://www.gbif.org/dataset/search?type=METADATA Occurrences are records that document a 'collection event'—evidence that a particular, named organism was found at a particular time and place. Also known as primary biodiversity data, occurrences document the 'what, where, when, how and by whom' of our exploration of the planet's species. An occurrence record can be based on an observation in the field, vouchered (labeled) specimen in a museum or herbarium, or other evidence. Checklists are lists of scientific names of organisms grouped into taxonomic hierarchies. They serve two main functions: first, they provide data that help to enrich information about particular species, for example by including them on national checklists, and on lists of invasive or threatened species; and they provide taxonomic 'backbones' around which species information can be organized. Metadata are structured descriptions of datasets giving essential details such as the geographic and taxonomic scope of the data, methods of collection or observation, contact details and citation requirements. They help to give context to datasets and enable users to assess whether data are fit for use in a particular research project or application.
- introduce the need/push for sample-based datasets (introduction of the event core) (http://www.gbif.org/page/82105) - released March 24, 2015 beyond “presence only” data -- more quantitative information used in other areas of scientific discovery and research, particularly ecological monitoring and assessment. Sample-based data (ecological monitoring and assessment data) Sample-based data are records from thousands of different kinds of environmental, ecological, and natural resource monitoring and assessment investigations. These events range from one-off surveys to ongoing monitoring and includes activities like freshwater and marine sampling, plant cover and vegetation plots, and citizen science bird counts, among others.
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 This section will cover the instructional objective 2a. Biodiversity Information Standards (TDWG), also known as the Taxonomic Databases Working Group, is a not for profit scientific and educational association that is affiliated with the International Union of Biological Sciences. TDWG was formed to establish international collaboration among biological database projects. TDWG promoted the wider and more effective dissemination of information about the World's heritage of biological organisms for the benefit of the world at large. Biodiversity Information Standards (TDWG) now focuses on the development of standards for the exchange of biological/biodiversity data. Our Mission Develop, adopt and promote standards and guidelines for the recording and exchange of data about organisms Promote the use of standards through the most appropriate and effective means and Act as a forum for discussion through holding meetings and through publications
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 It includes a glossary of terms intended to facilitate the sharing of information about biological diversity by providing reference definitions, examples, and commentaries. It is primarily based on taxa, their occurrence in nature as documented by observations, specimens, and samples, and related information.
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 Flat table Few restrictions
- A data file (occurrence.txt) conforming to the SIMPLEDWC in a CSV format. The first row includes Darwin Core standard term names. A meta file (meta.xml) in an XML format. It contains technical details to instruct a computer on how to use the data file. A meta file (eml.xml) in an XML format. It contains explanatory details about the records contained within the data file to instruct a user if the data will be fit for their use.
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Cores updated based on updated
- Modified from Standards and sharing complex primary biodiversity data; and what is an extension anyway? ~ Deb Paul ~ Data Sharing, Data Standards, and Demystifying the IPT Workshop – Day 1, Jan. 13, 2015 ~ Gainesville, FL
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Modified from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015
- Database normalization is process used to organize a database into tables and columns. The idea is that a table should be about a specific topic and that only those columns which support that topic are included. There are three main reasons to normalize a database. The first is to minimize duplicate data, the second is to minimize or avoid data modification issues, and the third is to simplify queries. To assist in achieving these objectives, some rules for database table organization have been developed. The stages of organization are called normal forms; there are three normal forms most databases adhere to using. First Normal Form – The information is stored in a relational table and each column contains atomic values, and there are not repeating groups of columns. Second Normal Form – The table is in first normal form and all the columns depend on the table’s primary key. Third Normal Form – the table is in second normal form and all of its columns are not transitively dependent on the primary key There are further norms if there is interest in learning more. For the purposes of the Star Schema, you’ll find your data adhering to the…
- Tweet image - https://twitter.com/Iteration23/status/646085874963337216 GBIF community group in conjunction with TDWG group on Data Quality Excel is a wonderful tool, but you must understand how Excel works or it can change your data in unexpected ways! Suggest watching -- Encoding Excel OpenRefine – Tutorials See pre-course activities for some recommendations/tutorials
- Slide from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 Ways to publish (strengths and weaknesses of each; include stats for numbers of datasets published via each way; how to identify what method was used when viewing datasets on gbif.org). This will cover the instructional objective 2b. simple spreadsheets IPT custom-created DwCA
- Slide from 1B Publishing Primary Biodiversity Data by Alberto González-Talaván1~ Data Sharing, Data Standards, and Demystifying the IPT ~ Gainesville, FL, USA. 13 January 2015 IPT currently under development with future planned updates Web tools and templates for excel tools were contracted for development in ???? And have not been updated since then. DiGIR protocol development ceased in 2006 TAPIR protocol last updated in 2010 BioCASE protocol last updated 2015
- Online poll Which of the following methods have you ever used to publish data online (or to help others to do so)? o DiGIR provider o TAPIR provider o BioCASe provider o IPT o DwC-A through “DwC-A spreadsheet processor” o Customized DwC-A through “DwC-A Assistant” Other custom created DwC-A o None There are simple online poll tools that show the progress of the voting as you speak and can be displayed in the screen as people vote. It communicates very well and makes the exercise very dynamic.
- Online poll Which of the following methods do you use REGULARLY to publish data online (i.e. in the last year) o DiGIR provider o TAPIR provider o BioCASE provider o IPT o DwC-A via“DwC-A spreadsheet processor” o Customized DwC-A via“DwC-A Assistant” Other custom created DwC-A o None Which of the following methods do you use regularly to publish data online (or to help others to do so) (i.e. used at least once in the last year) There are simple online poll tools that show the progress of the voting as you speak and can be displayed in the screen as people vote. It communicates very well and makes the exercise very dynamic.
- Online poll Which of the following methods do you use REGULARLY to publish data online (i.e. in the last year) o DiGIR provider o TAPIR provider o BioCASE provider o IPT o DwC-A via“DwC-A spreadsheet processor” o Customized DwC-A via“DwC-A Assistant” Other custom created DwC-A o None Which of the following methods do you use regularly to publish data online (or to help others to do so) (i.e. used at least once in the last year) There are simple online poll tools that show the progress of the voting as you speak and can be displayed in the screen as people vote. It communicates very well and makes the exercise very dynamic.
- This section will aim to start covering the instructional objective 3. Core element for Nodes managers to do Review from Berlin Extended documents --- review prior to use cases and exercises on day 2 Identify and assess data holders
- Slide from Module 3 – Knowledge exchange I Supporting data digitization and publishing ~ Alberto González-Talaván ~ 4 October 2013, GBIF Nodes Training ~ Berlin, Germany Barriers to publishing On these points: Lack of knowledge: The holder may not be aware how sharing on the internet works, and the existence of initiatives such as GBIF. Lack of understanding: the holder may have heard about GBIF and data publishing, but thinks it must be complicated, bureaucratic, very technical… Lack of will: The holder understand the process but does not want to go through it because of cultural issues, perceived sensitivity of the data, Perceived data value: the holder thinks that the data has economic or intrinsic value that (s)he wants to exploit. Privacy concerns: Lack of authorization: The holder would like to share the data, but institutional policies prevent it. Lack of time / planning: The holder never finds an appropriate moment to start the digitization, data transformation or publishing. Or got discouraged after not properly planned attempts. Lack of capacity: the holder would like to digitize and share the data, but (s)he doesn’t know what is the best (or any) way to do it. Lack of resources/funding: the holder would like to digitize and share the data, but there is no spare capacity in the institution to carry out such tasks. Lack of infrastructure: the holder would like to digitize and share the data, but (s)he does not have the technical infrastructure to do it. ----- Meeting Notes (10/3/15 07:09) ----- Least to most open Objective is to get to 5 or any advancement on the scale is positive
- Slide from Module 3 – Knowledge exchange I Supporting data digitization and publishing ~ Alberto González-Talaván ~ 4 October 2013, GBIF Nodes Training ~ Berlin, Germany Least to most open Objective is to get to 5 or any advancement on the scale is positive
- Slide from Module 3 – Knowledge exchange I Supporting data digitization and publishing ~ Alberto González-Talaván ~ 4 October 2013, GBIF Nodes Training ~ Berlin, Germany Strategies and arguments to overcome barriers/Incentives for publishing On these points: Facilitate access to financial support: provide digitization grants or help the data holders to obtain funding that funds directly or indirectly the digitization. Call upon commitments or legal mandates: Try to use commitments or legal mandates that apply to the institution or the country as a way to convince the data holder. Call upon open access / moral principles: the results of publicly funded research should be made public, access to science should not be restricted, etc. Show the benefits of a better data management: management of digital information can facilitate the data holder’s daily work. Show the benefit for their scientific careers: publishing data can provide scientific credit through data papers, citations and data usage indexes. Peer pressure: competing/fellow institutions are already sharing data and the holder’s institution is being left behind. Start / support big digitization programmes: promote the start of big digitization programmes that will benefit many holders at the same time. Start / support data repatriation efforts: start programmes that will allow the return of digital data describing your county’s biodiversity.
- Summarize community discussion on this topic examples publishing networks/nodes and how they’ve been successful or had difficulties in publishing data? Cees provided some great examples and strategies Nico introduced topic of licensing, mentioning Peter Desmet’s blog post, Why we should publish under CC0 as an illustrative example of what more restrictive licenses prevent users from doing or not doing with data. http://www.canadensys.net/2012/why-we-should-publish-our-data-under-cc0 Faustin, Hanna, and Cees provided some additional discussion on licensing And Anne-Sophie, introduced organizing trainings on topics like Data Papers as an easier sell to data publishers as who could observe the direct impact on the visibility and numbers of downloads of their data sets for their published data papers.
- 4 use cases based on current publishing practices: literature, observational data, natural history collections and checklists. The FIRST EXERCISE will last up to 20 minutes and will be around the definition of data publishing strategies. Based in the description included in their use case, each group will work on identifying suitable technical solutions, challenges and strategies. Each group will reflect the outcome of their discussions in a single page. The SECOND EXERCISE will use the all the remaining time and will consist on the publishing of a dataset using the test IPT installation made available for the course. There are two datasets available, depending on the level of challenge that the participant is seeking. Links to the datasets will be provided as part of the use case description document. Those seeking certification, will need to fill a template describing the process and send it to the group facilitator ONLY.
- Birds occurrence records from “Birds at the Danish Lighthouses 1883-1939”
- Camera trap database of Tiger sightings from India French and English
- Prairie Habitat Restoration Study
- VASSY, the database of vascular plants of Syldavia and Eskeastein
- Image from Piotr Lewandowski, shared via http://www.freeimages.com/photo/learning-with-pencil-1415671