P1DT1H31M40S306LibreOffice/7.0.4.2$Linux_X86_64 LibreOffice_project/00$Build-2Modèle et mini-guideModèle Jres 20212022-02-24T08:43:22.578989903Olivier Langella
300163
3604
22382
8251
true
false
view2
3771
228778
3604
300163
25984
308412
0
0
false
181
false
false
false
false
false
true
true
true
true
true
false
0
false
false
false
false
true
false
true
true
false
false
true
true
true
false
false
false
false
false
false
true
true
false
false
false
false
false
false
true
0
1
true
high-resolution
true
false
false
true
false
true
true
false
true
fr
FR
true
29294562
true
false
true
0
false
false
false
false
false
true
true
false
true
true
true
false
false
false
false
false
false
false
false
false
false
false
false
false
376182
false
false
true
false
false
true
false
true
true
JRES 2021 – Marseille11/11
Logiciels libres : à la recherche du bien commun
Edlira Nano
Informaticienne indépendante – Associations April, La Quadrature Du Net
eda@mutu.net / eda@laquadrature.net
Olivier Langella
Ingénieur au CNRS – Plateforme PAPPSO - Laboratoire GQE-Le Moulon
Ferme du Moulon 91190 Gif-sur-Yvette France
olivier.langella@universite-paris-saclay.fr
Filippo Rusconi
Chercheur au CNRS – Plateforme PAPPSO - Laboratoire GQE-Le Moulon
Ferme du Moulon 91190 Gif-sur-Yvette France
filippo.rusconi@universite-paris-saclay.fr
Résumé
Le logiciel libre et la recherche publique partagent un objectif : le bien commun, au service de tous. Cette présentation revient sur ce que sont le bien commun et la science ouverte pour essayer de les analyser à l'aide de l'exemple de la Plateforme scientifique Analyses Protéomiques de Paris Sud-Ouest (PAPPSO).
PAPPSO s'est dotée d'une infrastructure informatique complète basée exclusivement sur du logiciel libre : réseau, serveurs, stockage, calcul et postes personnels. Elle développe plusieurs logiciels scientifiques sous licence libre, dont ceux qui forment la chaîne de traitement des données de spectrométrie de masse. Ce choix naturel facilite la reproductibilité des traitements, apporte la maîtrise des logiciels et permet l'intégration de code source tiers eux-mêmes publiés sous licence libre.
Historiquement, l'apport majeur du logiciel libre à la recherche publique a d'abord résidé dans la mise en place de systèmes informatiques complexes tirant au mieux parti des réseaux. Progressivement, le logiciel libre s'est implanté avec force dans les laboratoires. En effet, d'un point de vue scientifique, l'ouverture du code source et les licences libres garantissent une plus grande réutilisation du code source et sa vérification par les pairs; la science gagnait ainsi en fiabilité. Cet élan a débordé le cadre strict du code source des logiciels pour irriguer le secteur stratégique des formats de fichier. C'est bien le monde du logiciel libre qui a contraint les éditeurs de logiciels à ouvrir les formats de leurs fichiers, jusqu'alors conservés secrets comme « arme » commerciale redoutable. De manière intéressante, l'impact a été encore plus profond, avec la prise de conscience que les données aussi devaient être ouvertes. Code source libre, formats ouverts et données publiques forment un bien commun qui est protégé par des licences. De nombreux laboratoires y contribuent en utilisant ou en produisant des logiciels libres, ou encore en publiant les données en accès libre, comme en témoignent la forge du code source du secteur public (https://code.gouv.fr) et les actions ministérielles spécifiques (https://www.ouvrirlascience.fr).
Comment contribuer efficacement ? Quelles sont les recommandations et obligations pour les établissements publics ? Quelle licence choisir ? Comment une licence copyleft peut-elle aussi séduire les partenaires privés ? Nous apporterons des réponses et des éléments de réflexion pour corriger quelques fausses croyances et promouvoir la construction collective d'une culture libre, au service du bien commun.
Mots-clefs
Logiciel libre, logiciel scientifique, biens communs, science ouverte, open source, copyleft, protéomique, infrastructure
Une plateforme pour la recherche sous logiciel libre
Contexte scientifique
La protéomique est l’étude de l’ensemble des protéines produites par une cellule, un organe ou un organisme. Elle permet d’analyser sans a priori les changements qualitatifs ou quantitatifs dans la composition en protéines en fonction de traitements, du développement ou de variations génétiques, et de comprendre par exemple comment un organisme répond à un stress ou à une maladie.
L’apparition du terme « protéomique » en 1995 coïncide avec le début de l’utilisation de la spectrométrie de masse pour l’identification des protéines puis pour leur quantification. Aujourd’hui la méthode utilisée quasi exclusivement est l’analyse de peptides issus de la digestion triptyque des protéines, par un spectromètre de masse couplé à une chaîne de chromatographie liquide. Les appareils n’ont pas cessé d’évoluer mais au final il s’agit toujours de mesurer la masse moléculaire des peptides ayant pénétré dans le spectromètre et/ou de leurs fragments et de quantifier leur intensité.
Les analyses par spectrométrie de masse produisent de grandes quantités de données, directement en sortie de l'instrument. Chaque fabricant a son propre format de données, qui est le plus souvent propriétaire. Ordinairement, les données aux formats propriétaires sont traitées par les logiciels fournis avec l'instrument, eux aussi propriétaires. Comme souvent dans le domaine des formats de fichiers, ces formats ne sont pas pérennes et les licences d'utilisation des logiciels propriétaires sont très coûteuses. Il y a donc ici un problème majeur d'interopérabilité.
Depuis 2005, la plateforme scientifique « Analyses protéomiques de Paris Sud-Ouest » (PAPPSO) a fait le choix du logiciel libre pour garantir la pérennité de ses chaînes de traitement, la reproductibilité des expériences et la capitalisation de son savoir-faire.
Transition des logiciels propriétaires au logiciel libre
Le passage progressif au logiciel libre a permis une rationalisation de l’utilisation des ressources informatiques. Nous sommes passés de postes dédiés à licence unique pour usage unique à une infrastructure collective combinant stockage, calcul et enchaînement des traitements depuis n’importe quel poste de travail.
Durant la période 2005–2015, notre travail a été facilité par la définition de formats standards en protéomique, l’émergence de nombreux logiciels libres dans le domaine [1] et le développement de nouvelles solutions logicielles sous licence libre (PROTICdb [2], mineXpert2 [3], X!TandemPipeline [4], MassChroQ [5]).
Choix du système d’exploitation
Le choix de PAPPSO1
http://pappso.inrae.fr/ s’est porté d’abord sur la distribution GNU/Linux Ubuntu, puis sur Debian. Un groupe de développeurs officiels Debian, dont un auteur de ce rapport, s'attache à fournir dans la distribution de nombreux logiciels pour la chimie, et en particulier pour la spectrométrie de masse (team debichem). L'intérêt principal de la distribution Debian est la richesse de son offre logicielle qui permet de disposer d'un socle de fonctionnalités robuste couvrant les exigences « serveur » et les impératifs « bureautique ». Tous les logiciels développés par PAPPSO sont disponibles sous forme de paquets Debian dans des dépôts publics. Le déploiement des logiciels, dépendances comprises, sur les serveurs et les postes de travail de l’équipe est ainsi simplifié et totalement automatisé.
Stockage des données
Les besoins en stockage de la plateforme évoluent constamment en fonction des progrès techniques des spectromètres de masse. Chaque nouvelle génération d'instruments apporte des améliorations, en particulier sur la précision de mesure de masse, qui provoquent une augmentation significative du volume des données générées. Cette progression des besoins en volume de stockage sur les quinze dernières années est illustrée dans la figure ci-dessous.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Figure 1– Évolution des besoins de stockage de la plateforme en To/an, en relation avec la production des données par les générations d'instruments
Le système de stockage des données de spectrométrie de masse doit permettre une adaptation en continu de la volumétrie d'espace disque disponible ainsi que les meilleures performances en lecture et écriture. Les solutions classiques de type NAS ont été écartées pour éviter la dépendance matérielle et les problèmes liés au renouvellement des équipements.
Dès 2011, nous avons été parmi les premiers à faire confiance à une solution nouvelle de stockage distribué : Ceph2
https://ceph.io/. La principale caractéristique de ce système de stockage est de ne requérir que des serveurs standard. La flexibilité et l'adaptabilité de ce système à des besoins perpétuellement en évolution en ont fait la solution la plus robuste que nous connaissions.
Calcul scientifique
La plateforme PAPPSO est spécialisée dans les traitements en protéomique haut débit (nombreux échantillons à traiter dans les plus brefs délais). Pour assurer la disponibilité de nos moyens de calcul à l’ensemble des utilisateurs, nous utilisons le gestionnaire de processus HTCondor3
https://htcondor.org/.
Les besoins en calcul évoluent eux aussi en fonction des instruments utilisés. Avec l’évolution des techniques, de nouvelles possibilités sont apparues dans le traitement de données en protéomique, exigeant elles aussi des capacités de calcul supplémentaires. De la même manière que pour les capacités de stockage, les machines dédiées au calcul doivent être ainsi renouvelées régulièrement et intégrées au fur et à mesure.
Retour d’expérience sur 10 ans
Matériel
L’intégration de nouvelles machines de calcul ou de stockage s’est faite de manière transparente. Nous sommes passés d’une capacité de stockage initiale de 18 To (3 serveurs R515, disques de 3 To) en 2011 à une capacité de 917 To (8 serveurs hétérogènes). Le réseau est passé du 1 Gb cuivre au 10 Gb SFP+. Il n’y a pas eu de transfert de données/migration, pas de modification de l’architecture logique pour les utilisateurs. Le système de fichiers cephfs permet un accès direct aux données depuis chaque nœud de calcul. Globalement, les performances ont suivi les évolutions matérielles (augmentation du débit, augmentation des capacités de calcul). La résistance aux pannes a été mise à rude épreuve (panne électrique, disques ou erreurs humaines) et nous n’avons jamais eu de perte de données.
Logiciel
Les systèmes pour les serveurs et pour les postes utilisateurs ont été migrés en 2013 de Ubuntu GNU/Linux vers Debian. Nous y avons gagné en stabilité et en simplicité lors des mises à jour de version. La stratégie consiste à maintenir le parc informatique sous Debian « stable » et effectuer le passage à la version successive dans les mois qui suivent sa publication officielle. Le stockage centralisé est disponible pour tous les postes dans une arborescence commune, via un montage automatique sur les nœuds de calculs (cephfs via systemd sur les serveurs, sshfs sur les postes clients). Les logiciels sont les mêmes sur les serveurs et les postes utilisateurs. L’accès distant au cluster de calcul se fait avec x2go, via une clé publique SSH.
Scientifique
Les analyses de la plateforme ont évolué pour passer de la technique chronophage des gels d’électrophorèse 2D4
Technique visant à séparer les nombreuses protéines d'un échantillon complexe en fonction de leur poids moléculaire, dans l'épaisseur d'un feuillet qui agit comme un tamis moléculaire. vers des analyses uniquement basées sur la spectrométrie de masse. Le traitement des images des gels 2D était majoritairement effectué avec des logiciels propriétaires sous Windows, sur des postes dédiés, ce qui limitait les capacités de traitement. Le passage progressif à des processus analytiques qui faisaient l'économie de l'étape d'électrophorèse a coïncidé avec les apports massifs du logiciel libre dans le domaine scientifique, au milieu des années 2000. Nous avons alors pu commencer la transition vers certains logiciels libres qui émergeaient à cette époque. Cependant, ces logiciels étaient principalement des bibliothèques partagées encore imparfaitement dotées des fonctionnalités requises dans notre domaine. Nous avons alors entrepris le développement de nos logiciels sur la base des besoins scientifiques particuliers à notre plateforme. Le logiciel MassChroQ est né ainsi, de nos besoins en protéomique quantitative. Notre indépendance vis-à-vis des formats de données propriétaires des fabricants nous a permis de produire un logiciel évolutif et pérenne dès le départ, évitant l’effet « boîte noire ». Ainsi, notre offre logicielle a pu être adaptée au fur et à mesure aux nouvelles techniques, à des instruments significativement différents de génération en génération, absorbant ainsi les « chocs » technologiques : doublement des fréquences d’acquisition à chaque génération (3 ans), doublement du pouvoir résolutif (précision des mesures des masses).
La dernière « rupture technologique » a été l’apparition du timsTOF Pro du fabricant Bruker. Cet appareil dispose d’une fréquence d’acquisition 10 fois supérieure à celle de la génération précédente ainsi que d’une nouvelle dimension de séparation des peptides (mobilité ionique). Fait unique depuis les débuts de la protéomique, Bruker nous a confié les spécifications techniques de son format de fichier de données. Cela nous a permis d’adapter MassChroQ pour pouvoir utiliser de manière native les données obtenues sur cet instrument. Notre savoir-faire en développement C++ nous a ainsi permis d’obtenir des gains de performances remarquables par rapport aux logiciels commerciaux, ainsi que de meilleurs résultats scientifiques.
Importance de la culture libre dans la recherche scientifique
Culture libre, communs et recherche publique
La recherche publique vise à produire et à développer des connaissances, à les améliorer sans cesse, puis à les rendre disponibles à la société, au cours des générations, constituant ainsi un corpus de savoirs qui caractérisent notre civilisation. La recherche scientifique est par essence incrémentale, elle se nourrit du savoir établi, pour venir à son tour nourrir cet ensemble commun de savoirs. Pour ce faire, elle a besoin d’accéder aux connaissances établies sans entrave, puis de pouvoir à son tour faire l’objet d’une diffusion libre.
Nous avons là les caractéristiques d’un logiciel libre ou, plus largement, d’un bien libre : quelque chose qu’on peut utiliser librement, distribuer librement autour de nous, mais aussi en modifier le contenu, pour l’adapter ou l’améliorer, pour ensuite le redistribuer tout aussi librement. La culture du libre n’est pas unique aux logiciels. Elle peut concerner du code source, un algorithme, un service informatique en ligne, un document (article scientifique, livre, poème), un produit artistique (œuvre numérique, reproduction numérique d’une œuvre physique d’un musée, photo numérique d'un monument historique), une semence agricole (les graines libres de droit), un médicament ou un vaccin que l’on peut fabriquer librement (libre de brevet).
Cette culture du libre est inhérente à la recherche publique également, et plus largement à ce qu’on appelle les communs. Les communs sont des ressources, naturelles ou culturelles, partagées et gérées collectivement, accessibles et disponibles pour tous, et qui n’appartiennent pas à qui que ce soit au sens de la propriété, qu’elle soit publique ou privée (Elinor Ostrom, prix Nobel d’économie pour ses travaux sur les communs, parle par exemple de « ressources de propriété commune » [6]).
La recherche publique, en ce qu’elle vise à améliorer, à rendre accessibles et disponibles les savoirs communs, peut ainsi être vue comme un processus cumulatif et collectif dont les résultats constituent un « bien commun » [7] .
Vers une science ouverte
La recherche publique en France (voir Figure ci-dessous, sources 2018) est financée à 75 % par des fonds publics français (MIRES, hors MIRES, administrations), et parmi les 25 % restants on ne retrouve que 5 % de ressources contractuelles provenant d’entreprises, les autres 20 % sont un mélange de fonds publics étrangers, notamment européens, ressources propres tels que les prestations de services des structures de recherche elles-mêmes, et enfin des ressources privées provenant d’entreprises étrangères) [8].
En dépit de la très faible proportion de financements privés, la recherche publique fait face à la mise en place progressive de mécanismes de privatisation et de verrouillage de ses productions par des acteurs privés de plus en plus envahissants, malheureusement soutenus par des politiques publiques de plus en plus tournées vers les transferts de technologies à tout prix et la valorisation, de type brevet entre autres. Une autre difficulté est liée au financement sur projet de la recherche publique, à un niveau insuffisant du financement public face à l’augmentation du nombre d’étudiants, au recours massif à des contrats temporaires, qui perturbent grandement son fonctionnement (voir le rapport 2019 du Comité national du CNRS [9], qui souhaite « un soutien public mû par la volonté de faire progresser les connaissances ».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Figure 2– Nature des ressources de la recherche publique en 2018 (en %)
Pascal AUBRY
2022-02-03T05:54:56.784000000
PA
Centrer l’image ?
Olivier Langella
2022-02-24T08:40:05.432977211
OL
Répondre à Pascal AUBRY (03/02/2022, 05:54): "..."
C’est fait
La culture libre, au service du savoir commun, que la recherche publique incarne et qui la structure, est illustrée par les nombreux mouvements pour une science ouverte, mouvements qui ont souvent vu le jour au sein des organismes de recherche. Ce sont des chercheurs, des étudiants ou des bibliothécaires, confrontés sans doute à cette nécessité d’ouverture, qui œuvrent, parfois leur vie durant, pour faire avancer l’ouverture des productions scientifiques. Ce n’est qu’après ces premières impulsions venant du terrain, qu’on voit s’opérer petit à petit une institutionnalisation progressive de cette ouverture.
Ainsi le mouvement de l’« open access » en est un bel exemple. ArXiv5
https://fr.wikipedia.org/wiki/ArXiv a été l'une des premières archives ouvertes de publications scientifiques, créée dès 1991 par le physicien Paul Ginsparg et maintenue par des laboratoires de recherche. L’équivalent français de ArXiv, HAL6
https://fr.wikipedia.org/wiki/HAL_(archive_ouverte), a été créé en 2001 par des chercheurs et s’est institutionnalisé au cours des années suivantes. Avant HAL, les travaux précurseurs de la bibliothécaire de l’INRAE Hélène Bosc sont également remarquables [10]. Témoignant de l’institutionnalisation progressive de la démarche, la plateforme de publications ouvertes orientée sciences humaines et sociales Open Edition7
https://www.openedition.org/ a vu, elle, le jour en 2011 en France.
Du côté des hacktivistes, en cette même année 2011, naissait le projet de captation et de diffusion d’articles scientifiques Sci-Hub8
https://fr.wikipedia.org/wiki/Sci-Hub. Initié par Alexandra Elbakyan, une étudiante chercheuse, ce projet consiste en un logiciel de captation d’articles scientifiques (y compris ceux fermés dans les plateformes de publications propriétaires), qui sont ensuite diffusés sur des portails web décentralisés et autonomes. Sci-Hub témoigne de cette culture de hacktivisme, dont les projets sont conçus de manière à être résilients aux pannes, aux fermetures et interdictions administratives, de par leur caractère décentralisé : chaque portail d’accès est géré de façon indépendante, mettant en commun les données en mode miroir ; si un portail ferme, d’autres miroirs sont toujours là pour assurer l’accès aux données. Quelques années auparavant, Aaron Swartz, un hacktiviste important de la culture libre, jouait aussi un rôle déterminant dès 2008 avec ses multiples actions de mise en place d’un portail d’accès aux documents publics administratifs d’abord, puis d’accès aux publications scientifiques. Swartz est également à l’origine de la création des licences libres Creative Commons, du projet Open Library, une des nombreuses fonctionnalités de l’Internet Archive, ce multi-projet d’archivage du web. Tout comme Alexandra Elbakyan, il a fait l’objet de poursuites pénales et de pressions administratives conséquentes. Tous deux ont pourtant joué un rôle déterminant de lanceurs d’alerte dans le domaine de l’ouverture des données publiques et de la science ouverte, termes ces derniers qui seront, quelques années après leur condamnation, tant repris dans les discours et les orientations affichées des politiques publiques.
Vers des codes sources sous licences libres
En matière de code source, le combat s’est également déroulé en grande partie dans le milieu de la recherche et par des hacktivistes d’un internet et d’une informatique libres. La Free Software Foundation a été créée en 1985 sous l’impulsion du chercheur Richard Stallman, pour tenter de donner un cadre légal de protection et de promotion des logiciels libres. C’est ainsi que la plus emblématique des licences libres dites copyleft a vu le jour : la GNU General Public Licence (GPL). Cette licence va non seulement introduire les quatre libertés fondamentales qui caractérisent le logiciel libre9
https://www.gnu.org/philosophy/, mais elle va également s’assurer de la pérennité de cette liberté à travers la notion de copyleft, également appelée share-alike (le « SA » des licences Creative Commons). Le copyleft va permettre à un code libre de ne pas se retrouver enfermé dans un code propriétaire non libre au cours de son existence et va ainsi assurer la persistance du caractère libre du code à travers les modifications et les transformations de celui-ci. C’est là un principe protecteur très fort, qui revendique la centralité de la notion éthique de liberté dans l’idéologie et la culture du Libre. Ainsi, le principe de copyleft est-il fondamental pour éviter que du code ouvert ne soit enfermé dans du code source propriétaire, comme il advient de plus en plus dans les grandes sociétés privées monopolistiques et privatrices telles que les GAFAM (Google, Amazon, Facebook, Apple et Microsoft).
En 1995, l’Open Source Initiative présente la définition de logiciel Open Source. Cette définition peu connue en détails, et employée à tort pour désigner tout code ouvert dans l'acception de « accessible », renferme en réalité dix conditions10
https://opensource.org qui assurent entre autres les quatre libertés fondamentales des logiciels libres. Les deux types de licences, libres et open source vont coïncider la plupart du temps, mais le terme de logiciel libre est préféré par ceux qui souhaitent mettre l’accent sur la notion de liberté ainsi que sur le caractère idéologique et politique qu’elle revêt.
En France, l’April est la plus grande association de défense et de promotion les logiciels libres, qui était nommée ainsi au départ en tant qu’acronyme d’Association Pour la Recherche en Informatique Libre. Notons également deux autres grandes associations dans le domaine : Framasoft d’une part, qui met l’accent sur l’éducation populaire via la culture libre au sens général et d’autre part, La Quadrature du Net, qui focalise ses actions sur les libertés numériques. Ces associations jouent un rôle important dans le plaidoyer, l’activisme, et la défense de la culture libre.
Notons également une ressource européenne importante que l’on doit à la campagne « Public Money, Public Code » portée par la Free Software Foundation Europe, qui résume dans sa brochure les bénéfices et apports multiples de l’ouverture du code source produit et utilisé dans le cadre de la recherche publique [12].
Vers des obligations légales, mais des pratiques en demi-teinte
En termes de politiques publiques, les expressions science ouverte et données ouvertes sont progressivement entrées dans le vocabulaire et dans les plans des gouvernements et tutelles de la recherche. En France, l’obligation légale s’instaure enfin en 2016 à l’occasion du Plan pour une République numérique11
Loi pour une République numérique.. Depuis cette date, les données de la recherche, y compris le code source des logiciels produits, sont considérées comme des données administratives publiques et sont soumises à ce titre à la même obligation de publication que ces dernières, au titre du Code des Relations entre le Public et l’Administration. Ce plan sera renommé en 2018 Plan national pour la science ouverte et porte désormais comme sous-inscription : « les résultats de la recherche scientifique ouverts à tous, sans
Filippo Matteo Rusconi
2022-01-12T09:34:34.740752134
FMR
On ne comprend pas si ce sont les résultats qui sont ouverts à tous ou la recherche scientifique qui est ouverte à tous. Je ne crois pas que la deuxième proposition soit la bonne :-)
David Verdin
2022-01-13T18:21:02.981498651
DV
Reply to Filippo Matteo Rusconi (12/01/2022, 09:34): "..."
Pourtant on dirait bien que c’est la deuxième : « ouverte » fait référence à « recherche », pas à « résultats ».
Filippo Matteo Rusconi
2022-01-19T13:25:22.064634883
FMR
Reply to David Verdin (01/13/2022, 18:21): "..."
Non, c’est bien ce que je pensais : les résultats sont ouverts. Vérification : https://www.enseignementsup-recherche.gouv.fr/fr/le-plan-national-pour-la-science-ouverte-les-resultats-de-la-recherche-scientifique-ouverts-tous-49241
entrave, sans délai, sans paiement ».
Les logiciels libres et open source se retrouvent aujourd’hui partout autour de nous, et cela bien souvent de manière non visible : les serveurs, les sites web, les objets intelligents, les services dans le cloud, reposent en grande majorité sur des logiciels et des systèmes d’exploitation libres. Ce n’est pas le cas des environnements personnels de travail, ni des services utilisés au quotidien sur ces environnements, dominés et monopolisés par les GAFAM qui proposent des outils la plupart du temps non libres et soumis à des restrictions d’usage diverses et variées (coût élevé, code source fermé, usage unique, DRM12
« Digital Rights Management » (gestion [restrictive] des droits numériques, principalement des droits d'auteur, contre laquelle lutte la campagne « Defective by design »).
intégrés, captation de données personnelles en échange de service, obsolescence, etc.).
Auteur inconnu
2022-01-12T20:19:21.755000000
Tous sauf un petit ENT breton qui s’appelle Toutatice pour les 1er et 2e cycles et ESUP-Portal pour le supérieur. C’est un breton ex ESUP qui parle… :-).
Ce n’est pas non plus le cas des environnements de travail de l’administration publique, ni de celui des millions d’élèves et d’étudiants qui sont confrontés de plus en plus tôt à un environnement et des services informatiques dominés par les contrats publics passés avec les GAFAM et autres sociétés aux pratiques privatrices et liberticides
eda
2022-02-23T14:02:48.572830909
e
Reply to Auteur inconnu (12/01/2022, 20:19): "..."
Et oui heureusement il y a des belles initiatives qui ne vont pas que dans ce sens <3 Mais là je parle des gros contrats surtout.
David Verdin
2022-01-13T18:23:05.371083161
DV
Reply to Auteur inconnu (12/01/2022, 20:19): "..."
💘
Filippo Matteo Rusconi
2022-01-19T13:32:50.121086221
FMR
Reply to David Verdin (01/13/2022, 18:23): "..."
+1 :-)
(citons par exemple le partenariat en 2015 entre Microsoft et l’Éducation Nationale13
https://www.april.org/microsoft-educ-nat-partenariat-indigne/, ou encore les tablettes numériques pour tous au collège sous système Windows de Microsoft).
Apports du libre
L’exemple de la plateforme PAPPSO ci-dessus nous démontre l’intérêt scientifique à libérer ses codes sources et son infrastructure de travail. Le logiciel libre et les infrastructures libres en milieu de recherche permettent et facilitent :
Pascal AUBRY
2022-02-03T05:57:15.409000000
PA
Style Liste 1
Olivier Langella
2022-02-24T08:42:15.288176333
OL
Répondre à Pascal AUBRY (03/02/2022, 05:57): "..."
Est-ce que le style des listes est le bon ?
un niveau de technicité et d’autonomie incomparable avec celui des logiciels propriétaires : le paramétrage fin des logiciels libres, leur adaptabilité et l’autonomie dans la réalisation de ces adaptations, l'émulation positive entre développeurs ainsi que l'auto-apprentissage (le code source ouvert et libre est un outil didactique en soi) ;
une meilleure productivité / efficacité : le mode de développement et de production scientifique libre est agile par construction : les besoins de la recherche peuvent être rapidement assouvis par le paramétrage et l’adaptation du code source, ou par la réutilisation de code source libre tiers. Ce code source bénéficie à son tour de la recherche scientifique pour s’enrichir de nouvelles fonctionnalités lors de cycles développement, test et mise en production courts et nombreux ;
une meilleure collaboration grâce au caractère ouvert du code source et aux libertés conférées par les licences d’utilisation ;un premier pas indispensable vers la sécurité logicielle : l’accès au code source permet un audit de sécurité par la communauté et ne nécessite pas de croire sur parole des fabricants aux conflits d’intérêts évidents ;une meilleure reproductibilité des résultats scientifiques : nul besoin de devoir acquérir les droits d’utilisation pour pouvoir reproduire des résultats obtenus avec des logiciels libres ;
une meilleure interopérabilité : les formats de données des logiciels libres sont ouverts et souvent standardisés. Les logiciels propriétaires reposent souvent sur des formats de données fermés et propres à chaque éditeur, rendant l’interopérabilité impossible ou difficile. Cela provoque des achats forcés et une obsolescence matérielle et logicielle qui a un coût économique et écologique non négligeable.
Le libre en pratique
Etalab est le département de la direction interministérielle du numérique (DINUM) qui coordonne la politique d’ouverture et de partage des données publiques des administrations de l’État. Ce département apporte son appui aux administrations pour leur permettre de répondre aux obligations légales d’ouverture. Il propose et maintient notamment :
la plateforme https://code.gouv.fr/ qui recense aujourd’hui les dépôts et le code source des logiciels du secteur public et qui invite ceux qui n’y sont pas répertoriés à s’y ajouter ;
la plateforme https://data.gouv.fr de diffusion de données publiques ;
le SILL : Socle Interministériel de Logiciels Libres (https://sill.etalab.gouv.fr), un catalogue qui référence les logiciels libres recommandés pour les administrations ;
un guide légal des obligations des publications administratives : https://guides.etalab.gouv.fr/algorithmes/guide/;
un accompagnement sur mesure pour assurer les obligations d’ouverture des données ;
un groupe de travail logiciels libres sur la plateforme https://communs.numerique.gouv.fr/ du Plan d’action logiciels libres et communs numériques. Notons en particulier la gazette et les ateliers vidéo BlueHats14
https://communs.numerique.gouv.fr/bluehats/.
Le portail https://www.ouvrirlascience.fr/ mis en place par le Comité pour la science ouverte du MESRI, propose lui aussi différents guides et recommandations.
Le portail du CNRS pour la science ouverte (https://www.science-ouverte.cnrs.fr/) référence également des dépôts publics de code source, de publications scientifiques et de données de la recherche.
Notons également l’initiative publique Software Heritage15
https://www.softwareheritage.org, qui vise à créer une archive universelle des logiciels à laquelle vous pouvez vous-même contribuer en y inscrivant votre code source.
Enfin, l’initiative REUSE16
https://reuse.software/ de la Free Software Foundation Europe vise à faciliter, voire à automatiser la mise sous licence libre de logiciels qui comportent différentes briques de code source, chacune portant potentiellement une licence libre différente. REUSE calcule l’intercompatibilité de ces licences et permet ainsi de les combiner pour une mise sous licence du logiciel complet.
Bilan
Le passage au logiciel libre pour tous les besoins informatiques de la plateforme PAPPSO a permis une maîtrise totale de ses outils, depuis la production des données brutes jusqu’à l’interprétation biologique. Les sommes importantes économisées en licences de logiciels propriétaires (20 k€ par an) ont été investies dans la maintenance des ressources de calcul et de stockage. Toutes les analyses sont complètement vérifiables et reproductibles, les logiciels étant tous librement téléchargeables, sous licence GPLv3+, sans demande préalable. Le savoir-faire développé par PAPPSO dans l’analyse protéomique à haut débit est reconnu au niveau international (129 articles citant MassChroQ depuis 2011, publication d’un article de référence en métaprotéomique [11]).
L’exemple de la plateforme PAPPSO n’est pas unique, de multiples autres initiatives locales similaires ont lieu constamment. L’initiative apps.education.fr17
https://apps.education.fr/, cette plateforme de services libres et éthiques pour travailler à distance née à l’occasion de la crise pandémique que l’Education Nationale est en train de pérenniser et d’étendre, en est un superbe exemple. Le monde de la recherche a toujours joué un rôle de précurseur, se positionnant comme un acteur primordial dans le long processus d’ouverture de la science, des formats de données, des données publiques et de la préservation des savoirs communs. Aidé par les mouvements militants et activistes, le chemin parcouru est considérable. Mais les politiques publiques de financement et d’orientation de la recherche semblent contradictoires et insuffisantes. Les récentes avancées comme la remise « prix science ouverte des données de recherche et du logiciel libre de la recherche » seront peut-être l’occasion de prendre conscience de la richesse de nos productions et de favoriser la cohérence entre les discours et les actes.
eda
2022-02-23T14:30:15.900769570
e
Reply to Auteur inconnu (12/01/2022, 20:28): "..."
Merci pour vos commentaires. J’ai un peu changé la conclusion, j’ai ajouté un exemple et je laisse la question ouverte.
David Verdin
2022-01-13T18:28:42.810427314
DV
Reply to Auteur inconnu (12/01/2022, 20:28): "..."
Assez d’accord. Pourquoi pas un hypothèse de collaboration entre structures de recherche publique dans un contexte de soudaine pandémie ? Aurions-nous vécu la même gabegie ?
Bibliographie
Auteur inconnu
2022-01-24T16:22:22.397000000
Remise en forme des références biblio pour une meilleure présentation des items > 10.
Rusconi F. Free Open Source Software for Protein and Peptide Mass Spectrometry- based Science. Curr Protein Pept Sci, 2 (22) 134-147, 2021 ; https://doi.org/10.2174/1389203722666210118160946
Langella O. , Valot B., Jacob D., Balliau T., Flores R., Hoogland C., Joets J., Zivy M.. (2013) Management and dissemination of MS proteomic data with PROTICdb: Example of a quantitative comparison between methods of protein extraction. Proteomics, 9 (13) 1457-66
Langella O, Rusconi F. mineXpert2: Full-Depth Visualization and Exploration of MSn Mass Spectrometry Data. J. Am. Soc. Mass Spectrom., 4 (32) 1138-114, mars 2021 ; https://doi.org/10.1021/jasms.0c00402
Langella O, Valot B, Balliau T, Blein-Nicolas M, Bonhomme L, Zivy M. X!TandemPipeline: A Tool to Manage Sequence Redundancy for Protein Inference and Phosphosite Identification. J. Proteome Res., 2 (16) 494-503, décembre 2016 ; https://doi.org/10.1021/acs.jproteome.6b00632
Valot B, Langella O, Nano E, Zivy M. MassChroQ: a versatile tool for mass spectrometry quantification. Proteomics, 17 (11) 3572-3577, juin 2011 ; https://doi.org/10.1002/pmic.201100120
Elinor Ostirom. Governing the Commons : the evolution of institutions for collective actions, 1990, Cambridge University Press ; https://archive.org/details/ElinorOstromGoverningTheCommons
Maurel Lionel. L’ouverture des données de recherche : un retour aux sources de l’Ethos de la Science ? Colloque Intégrité Scientifique et Science Ouverte, avril 2019 ; https://scinfolex.com/2019/06/05/louverture-des-donnees-de-recherche-un-retour-aux-sources-de-lethos-de-la-science
MESRI, L’état de l'Enseignement supérieur, de la Recherche et de l'Innovation en France n°14, 2021 ; https://publication.enseignementsup-recherche.gouv.fr/eesr
CNRS. La recherche publique en France en 2019 : diagnostic et propositions du Comité national, 2019; https://www.cnrs.fr/comitenational/Actualites/Propositions_Comite-national_Juillet-2019.pdf
Bosc H, Poynder R. The Open Access Interviews, 2009 ; https://www.richardpoynder.co.uk/Helene_Bosc_Interview.pdf
Van Den Bossche T, Kunath BJ, Schallert K, Schäpe SS, Abraham PE, Armengaud J, Arntzen M, Bassignani A, Benndorf D, Fuchs S, Giannone RJ, Griffin TJ, Hagen LH, Halder R, Henry C, Hettich RL, Heyer R, Jagtap P, Jehmlich N, Jensen M, Juste C, Kleiner M, Langella O, Lehmann T, Leith E, May P, Mesuere B, Miotello G, Peters SL, Pible O, Queiros PT, Reichl U, Renard BY, Schiebenhoefer H, Sczyrba A, Tanca A, Trappe K, Trezzi JP, Uzzau S, Verschaffelt P, von Bergen M, Wilmes P, Wolf M, Martens L, Muth T. Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows. Nature Communiations, 1 (12) 7305, décembre 2021 ; https://doi.org/10.1038/s41467-021-27542-8
FSFE. Public Money Public Code : Modernising Public Infrastructure with Free Software, 2019; https://download.fsfe.org/campaigns/pmpc/PMPC-Modernising-with-Free-Software.pdf