Open Science and research data

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(Nouvelle page : Category:formationCategory:MRCategory:en coursCategory:données de la recherche While the issue of open access to scientific publications (Open Access) is about twen...)
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(13 révisions intermédiaires masquées)
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[[Category:formation]][[Category:MR]][[Category:en cours]][[Category:données de la recherche]] [[Category:formation]][[Category:MR]][[Category:en cours]][[Category:données de la recherche]]
 +original in french: [[Open Science et données de la recherche]]
-While the issue of open access to scientific publications (Open Access) is about twenty years old, today we are talking about access to the data themselves, about sharing research data. What are the reasons for this shift in scale and what are the issues at stake? Scientific issues, but also economic and legal issues. But first, what are we talking about? What exactly are research data? We will see that there are several kinds, each of which raises specific questions. Finally, we will consider the consequences of this new issue for the researcher's own activity and the question of Data Management Plans (DMP). + 
 +<big>While the issue of open access to scientific publications (Open Access) is about twenty years old, today we are talking about access to the data themselves, about sharing research data. What are the reasons for this shift in scale and what are the issues at stake? Scientific issues, but also economic and legal issues. But first, what are we talking about? What exactly are research data? We will see that there are several kinds, each of which raises specific questions. Finally, we will consider the consequences of this new issue for the researcher's activity itself and the question of Data Management Plans (DMP). </big>
<center>[[Image:Science-nav.png|200px]]</center> <center>[[Image:Science-nav.png|200px]]</center>
<center>[http://ec.europa.eu/research/openscience/index.cfm?pg=home&section=monitor Open Science Monitor]</center> <center>[http://ec.europa.eu/research/openscience/index.cfm?pg=home&section=monitor Open Science Monitor]</center>
- 
=== First approach: a research and its data === === First approach: a research and its data ===
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:-> [http://www.inist.fr/?-Tutoriels-multimedias-H2020- '''Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »'''] :-> [http://www.inist.fr/?-Tutoriels-multimedias-H2020- '''Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »''']
-=== Qu'est-ce que "les données de la recherche"? ===+=== What is "research data"? ===
::> '''[https://donneesshs.hypotheses.org/39 Noëmie Rosemberg, "De la définition des données de la recherche," in ''En quête des données'', le 30/09/2015] ::> '''[https://donneesshs.hypotheses.org/39 Noëmie Rosemberg, "De la définition des données de la recherche," in ''En quête des données'', le 30/09/2015]
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These Principles and Guidelines are principally aimed at research data in digital, computer-readable format. It is indeed in this format that the greatest potential lies for improvements in the efficient distribution of data and their application to research because the marginal costs of transmitting data through the Internet are close to zero.These Principles and Guidelinescould also apply to analogue research data in situations where the marginal costs of giving access to such data can be kept reasonably low." These Principles and Guidelines are principally aimed at research data in digital, computer-readable format. It is indeed in this format that the greatest potential lies for improvements in the efficient distribution of data and their application to research because the marginal costs of transmitting data through the Internet are close to zero.These Principles and Guidelinescould also apply to analogue research data in situations where the marginal costs of giving access to such data can be kept reasonably low."
-'''[http://ands.org.au/guides/what-is-research-data.html Celle de l'Australian National Data Service]:'''+'''[http://ands.org.au/guides/what-is-research-data.html The one of the Australian National Data Service]:'''
''"Research Data: Data are facts, observations or experiences on which an argument, theory or test is based. Data may be numerical, descriptive or visual. Data may be raw or analysed, experimental or observational. Data includes: laboratory notebooks; field notebooks; primary research data (including research data in hardcopy or in computer readable form); questionnaires; audiotapes; videotapes; models; photographs; films; test responses."'' ''"Research Data: Data are facts, observations or experiences on which an argument, theory or test is based. Data may be numerical, descriptive or visual. Data may be raw or analysed, experimental or observational. Data includes: laboratory notebooks; field notebooks; primary research data (including research data in hardcopy or in computer readable form); questionnaires; audiotapes; videotapes; models; photographs; films; test responses."''
Ligne 30 : Ligne 31 :
[https://urfistinfo.hypotheses.org/2581 Sylvie Fayet:] [https://urfistinfo.hypotheses.org/2581 Sylvie Fayet:]
-"At the very least, we implicitly agree on the following idea: when we talk about "research data", we mean figures, readings, measurements, results of experiments, responses to surveys, statistics, counts, and other quantitative data on the basis of which a hypothesis will be developed, and/or which will be used to invalidate or validate this hypothesis... in short, essentially quantitative data, which can be processed, sorted, exploited, visualized in a homogeneous manner. The publication of such data is already part, at least in some disciplines, of the canons of scientific article writing (for example, the "Materials and methods" section in the recommendations for writing articles in medical journals)". +"At the very least, we implicitly agree on the following idea: when we talk about "research data", we mean figures, readings, measurements, results of experiments, responses to surveys, statistics, counts, and other quantitative data on the basis of which a hypothesis will be developed, and/or which will be used to invalidate or validate this hypothesis... in short, essentially quantitative data, which can be processed, sorted, exploited, visualized in a homogeneous manner. The publication of such data is already part, at least in some disciplines, of the canons of scientific article writing (for example, the "Materials and methods" section in the recommendations for writing articles in medical journals)".
-==== les différents types de données ====+==== the different types of data ====
-de la publication aux données: ''embedded data'', ''underlying data'', ''raw data''...:+from the published papers to the data: embedded data, underlying data, raw data... (reverse engineering): embedded data > underlying data > raw data...:
[[Media:Schema DR 170120.pdf]] [[Media:Schema DR 170120.pdf]]
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[[Image:Donnees recherche Francis Andre.png|500px]] [[Image:Donnees recherche Francis Andre.png|500px]]
-==== finalités du partage des données de la recherche ====+==== purposes of sharing research data ====
-* '''validation''' (science reproductible)+* '''validation''' (reproducible science)
-* '''réutilisation''' (science cumultaive)+* '''reuse''' (cumulative science)
-==== [http://doranum.fr/depot-des-donnees-en-5-questions/ le dépôt des données sur DoRANum] ==== 
[[Image:Depot données.png|500px]] [[Image:Depot données.png|500px]]
-=== Enjeux et contexte: ===+=== Issues and Context: ===
-* retour sur la formation '''[[Science 2.0]]+* back to the '''[[Science 2.0]]''' training
-'''+ 
-==== ''Open Science'' / "Science ouverte" ====+==== Open Science ====
* [https://www.fosteropenscience.eu/ Foster] * [https://www.fosteropenscience.eu/ Foster]
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:[http://michaelnielsen.org/blog/open-science-2/ Michael Nielsen] :[http://michaelnielsen.org/blog/open-science-2/ Michael Nielsen]
-===== concepts parents =====+===== related concepts =====
* "sciences" * "sciences"
-** ''[https://en.wikipedia.org/wiki/E-Science e-science]'': la science électronique / numérique+** ''[https://en.wikipedia.org/wiki/E-Science e-science]'': e-science / digital
-*** "documentation électronique" (cf. ''[https://en.wikipedia.org/wiki/Open_access open access]'')+*** "e-documentation" (cf. ''[https://en.wikipedia.org/wiki/Open_access open access]'')
-**** questions de granularité+**** granularity issues
-*** informatisation de l'activité scientifique (cf. ''big data''): ''"ideas like recursion, parallelism and abstraction taken from computer science will redefine modern science. Implicit in the idea of a fourth paradigm is the ability, and the need, to share data. In sciences like physics and astronomy, the instruments are so expensive that data must be shared. Now the data explosion and the falling cost of computing and communications are creating pressure to share all scientific data."'' ([http://www.nytimes.com/2009/12/15/science/15books.html John Markoff])+*** computerization of scientific activity (cf. ''big data''): ''"ideas like recursion, parallelism and abstraction taken from computer science will redefine modern science. Implicit in the idea of a fourth paradigm is the ability, and the need, to share data. In sciences like physics and astronomy, the instruments are so expensive that data must be shared. Now the data explosion and the falling cost of computing and communications are creating pressure to share all scientific data."'' ([http://www.nytimes.com/2009/12/15/science/15books.html John Markoff])
** ''[https://en.wikipedia.org/wiki/Open_access open access]'' [ [https://fr.wikipedia.org/wiki/Libre_acc%C3%A8s_%28%C3%A9dition_scientifique%29 fr] ] ** ''[https://en.wikipedia.org/wiki/Open_access open access]'' [ [https://fr.wikipedia.org/wiki/Libre_acc%C3%A8s_%28%C3%A9dition_scientifique%29 fr] ]
** ''[https://en.wikipedia.org/wiki/Science_2.0 Science 2.0]'' ** ''[https://en.wikipedia.org/wiki/Science_2.0 Science 2.0]''
** ''[https://en.wikipedia.org/wiki/Open_science Open Science]'' [ [https://fr.wikipedia.org/wiki/Open_data fr] ] ** ''[https://en.wikipedia.org/wiki/Open_science Open Science]'' [ [https://fr.wikipedia.org/wiki/Open_data fr] ]
-* ''data''+* data
** ''[https://en.wikipedia.org/wiki/Open_data Open data]'' ** ''[https://en.wikipedia.org/wiki/Open_data Open data]''
*** [https://fr.wikipedia.org/wiki/Libert%C3%A9_d%27acc%C3%A8s_aux_documents_administratifs libération des données publiques] ([http://www.cada.fr/l-acces-aux-documents-administratifs,1.html Loi CADA]) *** [https://fr.wikipedia.org/wiki/Libert%C3%A9_d%27acc%C3%A8s_aux_documents_administratifs libération des données publiques] ([http://www.cada.fr/l-acces-aux-documents-administratifs,1.html Loi CADA])
Ligne 80 : Ligne 80 :
*** [http://www.wired.com/2008/06/pb-theory/ ''The end of theory''] / [https://en.wikipedia.org/wiki/Chris_Anderson_%28writer%29 Chris Anderson] (2008): ''"The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all. "'' *** [http://www.wired.com/2008/06/pb-theory/ ''The end of theory''] / [https://en.wikipedia.org/wiki/Chris_Anderson_%28writer%29 Chris Anderson] (2008): ''"The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all. "''
**** [http://research.microsoft.com/en-us/collaboration/fourthparadigm/ ''Fourth paradigm?''] **** [http://research.microsoft.com/en-us/collaboration/fourthparadigm/ ''Fourth paradigm?'']
-** ''Web of data'' / Linked Data /[[Web sémantique]]): ''The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web – a web of data that can be processed directly or indirectly by machines.'' [https://en.wikipedia.org/wiki/Tim_Berners-Lee Tim Berners-Lee] (2000) ([http://tomheath.com/blog/2009/03/linked-data-web-of-data-semantic-web-wtf/ via])+** ''Web of data'' / Linked Data /[[Web sémantique|Semantic Web]]): ''The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web – a web of data that can be processed directly or indirectly by machines.'' [https://en.wikipedia.org/wiki/Tim_Berners-Lee Tim Berners-Lee] (2000) ([http://tomheath.com/blog/2009/03/linked-data-web-of-data-semantic-web-wtf/ via])
[[Image:LOD Cloud 2014.svg.png]][https://upload.wikimedia.org/wikipedia/commons/0/08/LOD_Cloud_2014.svg|source] [[Image:LOD Cloud 2014.svg.png]][https://upload.wikimedia.org/wikipedia/commons/0/08/LOD_Cloud_2014.svg|source]
[[Image:APIdays - APIculture DataCulture.018-001.jpg|400px]] [[Image:APIdays - APIculture DataCulture.018-001.jpg|400px]]
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[[Image:Science-nav.png|500px]] [[Image:Science-nav.png|500px]]
-==== crise de la validation ====+==== validation crisis ====
-* un exemple: [http://www.sciencepresse.qc.ca/actualite/2006/01/09/watergate-clonage le Watergate du clonage]+* an exemple: [http://www.sciencepresse.qc.ca/actualite/2006/01/09/watergate-clonage le Watergate du clonage]
-* un constat: [http://passeurdesciences.blog.lemonde.fr/2012/10/03/la-fraude-scientifique-est-plus-repandue-recherche/ La fraude scientifique est plus répandue qu’on le croit]+* a constat: [http://passeurdesciences.blog.lemonde.fr/2012/10/03/la-fraude-scientifique-est-plus-repandue-recherche/ La fraude scientifique est plus répandue qu’on le croit]
-* science expérimentale et validation+* experimental science and validation:> [http://raconterlavie.fr/collection/chercheur-au-quotidien/#.Vp6Aaud3eYVSébastien Balibar]
-:> [http://raconterlavie.fr/collection/chercheur-au-quotidien/#.Vp6Aaud3eYVSébastien Balibar]+
[[Image:69730b52558050bbdc3d1c69c982f764.jpg]] [[Image:69730b52558050bbdc3d1c69c982f764.jpg]]
-<big>"La règle est de décrire ses travaux avec suffisamment de précision pour que quelqu’un d’autre puisse les comprendre dans tous leurs détails, les reproduire, les vérifier, les confirmer ou les réfuter."</big>+<big>"The rule is to describe one's work with sufficient precision so that someone else can understand it in all its details, reproduce it, verify, confirm or refute it."</big>
-==== contexte juridique et réglementaire ====+==== legal and regulatory context ====
-> '''[http://doranum.fr/2017/02/21/ouverture-des-donnees-de-recherche-guide-danalyse-du-cadre-juridique-en-france/ Ouverture des données de la recherche: Guide d'analyse du cadre juridique en France]'''+COUNTRY DEPENDENT
-===== Quel cadre réglementaire suivre ? =====+==== disciplinary variations ====
-"Il existe beaucoup de textes de différentes formes (loi, circulaire, directive, etc.) qui régissent les données qui peuvent être produites par la recherche :+Roughly speaking (very roughly) in Humanities and Social Sciences the purpose "reuse" outweighs the purpose "validation". > [https://en.wikipedia.org/wiki/Text_mining '''Text mining''']
-* Texte principal : Loi n°78‐753 du 17.07.1978 dite « loi CADA » modifié par la loi du 28/12/15 relative à la gratuité et aux modalités de réutilisation des informations du secteur public,+
-* Code de la recherche : article L112‐1 « e) L'organisation de l'accès libre aux données scientifiques »,+
-* A venir : le projet de loi Lemaire pour une république numérique,+
-* Autres textes : loi Informatique et Libertés, circulaire pour la Protection du Patrimoine Scientifique et Technique, code de l’environnement (ex art L124‐ 2), directive Inspire, etc.+
-Est-ce que je produis des documents administratifs ? Oui si mon employeur est public+===== Digital Humanities =====
-* Tout ce que je fais dans le cadre de ma mission peut être considéré comme un document administratif+
-* '''Attention ! Pour les doctorants''' : si la thèse est cofinancée ou réalisée en collaboration avec un partenaire de l’employeur => il faut se reporter au contrat+
-* Cas particulier : je suis chercheur ou enseignant-chercheur: mes écrits, cartes, photographies, plans qui sont originaux et donc soumis au droit d’auteur m’appartiennent (exception – loi DADVSI 2006-961). Mais le reste appartient bien à mon employeur."+
- +
-===== l'affaire de l'API d'Elsevier =====+
-cf. [http://scoms.hypotheses.org/98 Data Mining : quand Elsevier écrit sa propre loi…] / Pierre-Carl Langlais (février 2014)+
- +
-Accord [https://fr.wikipedia.org/wiki/Consortium_unifi%C3%A9_des_%C3%A9tablissements_universitaires_et_de_recherche_pour_l'acc%C3%A8s_aux_publications_num%C3%A9riques Couperin] / [https://fr.wikipedia.org/wiki/Elsevier_%28%C3%A9diteur%29 Elsevier]:+
-"Tous les contenus accessibles et souscrits sur ScienceDirect dans le cadre de cet accord seront utilisables à des fins de data et text mining via une interrogation des données par une API connectée à la plateforme ScienceDirect. Les modalités appliquées seront celle du cadre juridique défini par Elsevier pour ce type de service."+
- +
-"La licence Elsevier comprend trois conditions. Tout élément (output) issu de l’extraction :+
- +
-# peut comprendre des extraits de 200 caractères au maximum du texte original.+
-# doit être publié sous une licence non commercial (CC-BY-NC)+
-# doit inclure un lien DOI vers le contenu original."+
- +
-==== déclinaisons disciplinaires ====+
- +
-En gros (très gros) en SHS la finalité "réutilisation" l'emporte sur la finalité "validation" > [https://fr.wikipedia.org/wiki/Fouille_de_textes '''TDM''']+
- +
-===== les Humanités numériques =====+
* [http://www.huma-num.fr/la-tgir-en-bref Huma-Num]: "Huma-Num est une très grande infrastructure de recherche (TGIR) visant à faciliter le tournant numérique de la recherche en sciences humaines et sociales." * [http://www.huma-num.fr/la-tgir-en-bref Huma-Num]: "Huma-Num est une très grande infrastructure de recherche (TGIR) visant à faciliter le tournant numérique de la recherche en sciences humaines et sociales."
** [https://fr.wikipedia.org/wiki/Plateforme_Isidore Isidore][ [http://www.rechercheisidore.fr/ lien] ] ** [https://fr.wikipedia.org/wiki/Plateforme_Isidore Isidore][ [http://www.rechercheisidore.fr/ lien] ]
* [http://archinfo41.hypotheses.org/571 Text mining : quand le texte devient donnée] Emeline Mercier (2015) * [http://archinfo41.hypotheses.org/571 Text mining : quand le texte devient donnée] Emeline Mercier (2015)
-* un exemple: [http://web.stanford.edu/group/toolingup/rplviz/ Mapping the Republic of Letters]+* an exemple: [http://web.stanford.edu/group/toolingup/rplviz/ Mapping the Republic of Letters]
[[Image:Mapping the Republic of Letters.png|400px]] [[Image:Mapping the Republic of Letters.png|400px]]
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http://web.stanford.edu/group/toolingup/rplviz/ http://web.stanford.edu/group/toolingup/rplviz/
-* [https://www.maddyness.com/technologie/2016/04/07/panamapapers-linkurious/ Linkurious] et les "Panama Papers"+* [https://www.maddyness.com/technologie/2016/04/07/panamapapers-linkurious/ Linkurious] and the "Panama Papers"
-===== cultures disciplinaires (quelques exemples) =====+===== disciplinary cultures (some exemples) =====
-* [http://www.homo-numericus.net/article314.html#nb5 histoire]+* [http://www.homo-numericus.net/article314.html#nb5 history]
-* [http://ceur-ws.org/Vol-600/paper1.pdf médecine]+* [http://ceur-ws.org/Vol-600/paper1.pdf medecine]
-* [http://archaeologydataservice.ac.uk/learning/DataTrainDownload#section-DataTrainDownload-Module2 archéologie]+* [http://archaeologydataservice.ac.uk/learning/DataTrainDownload#section-DataTrainDownload-Module2 archeology]
-* [https://fr.wikipedia.org/wiki/Centre_de_donn%C3%A9es_astronomiques_de_Strasbourg astronomie]+* [https://fr.wikipedia.org/wiki/Centre_de_donn%C3%A9es_astronomiques_de_Strasbourg astronomy]
* [https://cloud.google.com/genomics/ génomique] * [https://cloud.google.com/genomics/ génomique]
-* [http://www.nytimes.com/2010/12/04/books/04victorian.html?hpw?src=ISMR_AP_LI_LST_FB&pagewanted=all&_r=0 littérature anglaise]+* [http://www.nytimes.com/2010/12/04/books/04victorian.html?hpw?src=ISMR_AP_LI_LST_FB&pagewanted=all&_r=0 english literature]
-* [http://phonotheque.hypotheses.org/16378 musique]+* [http://phonotheque.hypotheses.org/16378 music]
-* [http://www.cairn.info/revue-management-2006-3-page-199.htm gestion]+* [http://www.cairn.info/revue-management-2006-3-page-199.htm management]
-=== Gérer et partager ses données ===+=== Managing and sharing our data ===
> [https://data.hypotheses.org/1016 Faut-il partager ses données?] > [https://data.hypotheses.org/1016 Faut-il partager ses données?]
-===== DMP / PGD =====+===== DMP =====
:-> [http://www.inist.fr/?-Tutoriels-multimedias-H2020- '''Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »'''] :-> [http://www.inist.fr/?-Tutoriels-multimedias-H2020- '''Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »''']
-* Les plans de gestion de données+* The Data Management Plan
-* Organisation et description+* Organazing and describing
-* Stockage et conservation+* Storage and conservation
-* Partage et diffusion+* Sharing and dissemination
- +
-===== et les doctorants? =====+
-* déposer la thèse / déposer les données: [http://hal-univ-lille3.archives-ouvertes.fr/hal-01192930/document Les données de la recherche dans les thèses de doctorat - Livre blanc]: "les thèses appartiennent à l’enseignement supérieur, hors tout circuit commercial, et elles ont, du fait de leur nombre, leur richesse et qualité mais aussi leur représentativité, un grand intérêt pour la veille et l’innovation."+
-[[Image:Capture d’écran 2016-01-20 à 12.06.05.png]]+
-* cf. supra "cadre législatif"+
- +
-==== retour sur l'étude de cas ====+
- +
- +
-----+
- +
-=== Seconde Partie (ED niçoises): Gérer et diffuser ses données : principes et bonnes pratiques / Mathieu Saby (BU UNS) ===+
- +
-Support sur Jalon: '''[http://jalon.unice.fr/cours/msaby/Cours-msaby-20160517105450 Gérer et diffuser ses données : principes et bonnes pratiques]'''+
- +
- +
-----+
-===[https://groups.diigo.com/group/bsn9-donnes-de-la-recherche Syndication]===+==== back to the exemple case ====
-<rss desc=off>https://groups.diigo.com/group/bsn9-donnes-de-la-recherche/rss</rss>+

Version actuelle

original in french: Open Science et données de la recherche


While the issue of open access to scientific publications (Open Access) is about twenty years old, today we are talking about access to the data themselves, about sharing research data. What are the reasons for this shift in scale and what are the issues at stake? Scientific issues, but also economic and legal issues. But first, what are we talking about? What exactly are research data? We will see that there are several kinds, each of which raises specific questions. Finally, we will consider the consequences of this new issue for the researcher's activity itself and the question of Data Management Plans (DMP).

Open Science Monitor

Sommaire

[modifier] First approach: a research and its data

case study (Workshop by Yvette Lafosse and Françoise Cosserat)

-> Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »

[modifier] What is "research data"?

> Noëmie Rosemberg, "De la définition des données de la recherche," in En quête des données, le 30/09/2015

[modifier] definitions (data and validation)

That of the OCDE:

"In the context of these Principles and Guidelines, “research data” are defined as factual records (numerical scores, textual records, images and sounds) used as primary sources for scientific research, and that are commonly accepted in the scientific community as necessary to validate research findings. A research data set constitutes a systematic, partial repre-sentation of the subject being investigated.

This term does not cover the following: laboratory notebooks, pre-liminary analyses, and drafts of scientific papers, plans for future research, peer reviews, or personal communications with colleagues or physical objects (e.g. laboratory samples, strains of bacteria and test animals such as mice). Access to all of these products or outcomes of research is governed by different considerations than those dealt with here.

These Principles and Guidelines are principally aimed at research data in digital, computer-readable format. It is indeed in this format that the greatest potential lies for improvements in the efficient distribution of data and their application to research because the marginal costs of transmitting data through the Internet are close to zero.These Principles and Guidelinescould also apply to analogue research data in situations where the marginal costs of giving access to such data can be kept reasonably low."

The one of the Australian National Data Service:

"Research Data: Data are facts, observations or experiences on which an argument, theory or test is based. Data may be numerical, descriptive or visual. Data may be raw or analysed, experimental or observational. Data includes: laboratory notebooks; field notebooks; primary research data (including research data in hardcopy or in computer readable form); questionnaires; audiotapes; videotapes; models; photographs; films; test responses."

Sylvie Fayet:

"At the very least, we implicitly agree on the following idea: when we talk about "research data", we mean figures, readings, measurements, results of experiments, responses to surveys, statistics, counts, and other quantitative data on the basis of which a hypothesis will be developed, and/or which will be used to invalidate or validate this hypothesis... in short, essentially quantitative data, which can be processed, sorted, exploited, visualized in a homogeneous manner. The publication of such data is already part, at least in some disciplines, of the canons of scientific article writing (for example, the "Materials and methods" section in the recommendations for writing articles in medical journals)".

[modifier] the different types of data

from the published papers to the data: embedded data, underlying data, raw data... (reverse engineering): embedded data > underlying data > raw data...:

Media:Schema DR 170120.pdf

[modifier] purposes of sharing research data

  • validation (reproducible science)
  • reuse (cumulative science)


[modifier] Issues and Context:

[modifier] Open Science

“Open science is the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process.”

Michael Nielsen
[modifier] related concepts
  • "sciences"
    • e-science: e-science / digital
      • "e-documentation" (cf. open access)
        • granularity issues
      • computerization of scientific activity (cf. big data): "ideas like recursion, parallelism and abstraction taken from computer science will redefine modern science. Implicit in the idea of a fourth paradigm is the ability, and the need, to share data. In sciences like physics and astronomy, the instruments are so expensive that data must be shared. Now the data explosion and the falling cost of computing and communications are creating pressure to share all scientific data." (John Markoff)
    • open access [ fr ]
    • Science 2.0
    • Open Science [ fr ]
  • data

Image:LOD Cloud 2014.svg.png[1]

[modifier] Open Science

[Open Science Monitor http://ec.europa.eu/research/openscience/index.cfm?pg=home&section=monitor]

[modifier] validation crisis

Image:69730b52558050bbdc3d1c69c982f764.jpg

"The rule is to describe one's work with sufficient precision so that someone else can understand it in all its details, reproduce it, verify, confirm or refute it."

[modifier] legal and regulatory context

COUNTRY DEPENDENT

[modifier] disciplinary variations

Roughly speaking (very roughly) in Humanities and Social Sciences the purpose "reuse" outweighs the purpose "validation". > Text mining

[modifier] Digital Humanities

http://web.stanford.edu/group/toolingup/rplviz/

[modifier] disciplinary cultures (some exemples)

[modifier] Managing and sharing our data

> Faut-il partager ses données?

[modifier] DMP
-> Tutoriels « Le libre accès aux résultats de la recherche dans le cadre d’Horizon 2020 »
  • The Data Management Plan
  • Organazing and describing
  • Storage and conservation
  • Sharing and dissemination

[modifier] back to the exemple case