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La condivisione dei dati generati dalla ricerca scientifica è fondamentale per l’avanzamento della conoscenza, come ampiamente dimostrato durante la pandemia di Covid-19. Quest’emergenza sanitaria ha evidenziato le lacune esistenti nella gestione e condivisione dei dati, pratiche ancora non pienamente consolidate nella cultura scientifica. Affinché i dati possano essere condivisi e riutilizzati in modo efficace, i ricercatori devono adottare specifiche procedure per renderli FAIR (Findable, Accessible, Interoperable, Reusable). I principali enti finanziatori della ricerca, come Horizon Europe e i National institutes of health (Nih), richiedono inoltre la presentazione di piani dettagliati per la gestione dei dati (Data management plans), nei quali i ricercatori devono specificare come intenderanno gestire e condividere tutti i dati prodotti nell’ambito dei progetti finanziati. Nell’ultima parte di questo articolo, ci soffermeremo sulle politiche editoriali relative alla condivisione dei dati, analizzando le sfide che ostacolano questa pratica e le nuove tecnologie e figure professionali indispensabili per una gestione efficiente dei dati scientifici.

Une enquête au sein du Front national comme celle conduite par l’auteur de 1996 à 1999 serait sans doute irréalisable aujourd’hui du fait de l’encadrement bureaucratique auquel les sociologues sont désormais astreints par le biais des dispositifs éthiques (notamment le RGPD) et des plans de gestion des données. C’est ce qui est apparu en toute clarté lors du traitement des archives de cette enquête pour la « banque de données qualitatives » beQuali. Comment protéger les militants, pour certains admirateurs de Hitler et hostiles aux mélanges entre races, dont aucun accord par ailleurs n’a été sollicité, sans désincarner les données et les rendre inutilisables ? Comment protéger l’enquêteur, dont certaines réactions semblent racistes ou réactionnaires, sans occulter une partie de son journal, jusqu’à le rendre insipide ? Contre les tentatives de mise au pas au nom de la morale et du Bien public, nous avons à faire valoir un héritage qui nous vient de nos prédécesseurs : l’aventure du savoir critique sur le monde social.

L’accès aux enquêtes et le partage de données sont fondamentaux pour la recherche en sciences sociales. Pourtant, les activités d’archivage qui permettent un accès aux enquêtes mises à disposition sont peu connues. Cet article se concentre sur les données des enquêtes quantitatives. Il passe en revue le développement des archives de données d’enquêtes en sciences sociales depuis leur création dans les années 1950, ainsi que l’émergence de normes internationales. En France, les archives de données d’enquêtes ont été établies relativement tard. L’article montre ensuite l’importance des archives pour l’accès aux enquêtes en s’appuyant sur l’exemple du service des enquêtes et des sondages de l’Institut national d’études démographiques (Ined), cofondateur du Réseau Quetelet, qui centralise aujourd’hui l’accès à la plupart des enquêtes quantitatives en sciences sociales en France. Les activités d’archivage et de mise à disposition des données et métadonnées d’enquêtes à des fins de recherche sont ensuite discutées, en montrant l’importance de la collaboration avec les producteurs de données dans un contexte d’ouverture croissante des données ( open data ). Sharing data and providing access to surveys are paramount to social research. Yet there is little knowledge of the archiving activities involved. This article focuses on quantitative survey data. It reviews the development of social science survey data archives from their creation in the 1950s and the emergence of international standards. France was a late starter in this domain. It then demonstrates the importance of archives for providing access to survey data via the example of the Surveys Department of the French Institute for Demographic Studies (INED), a co-founder of the Réseau Quetelet, which today centralizes access to most social science surveys in France. The work done to make survey data and metadata available for re-use is discussed, highlighting the importance of collaboration with data producers in a context of a strengthening trend towards open data.

Cet article s’intéresse au partage de l’information à l’intérieur de la législation REACH. Les membres d’un forum d’échange d’information ont l’obligation de partager les données qu’ils possèdent sur une substance chimique. Ce partage de l’information conduit à la mise en place d’un mécanisme de compensation : les membres non propriétaires d’une information compensent financièrement les membres propriétaires. Nous nous intéressons au choix d’un mécanisme de compensation équitable pour l’ensemble des participants. Pour cela, nous modélisons la procédure de partage des coûts de production des informations en reprenant une partie du formalisme récemment proposé par Dehez et Tellone [2010]. Nous listons une série d’axiomes pour les mécanismes de compensation. Différentes combinaisons de ces axiomes font émerger plusieurs mécanismes de compensation. Certains de ces mécanismes coïncident avec des solutions connues d’un jeu coopératif à utilité transférable associé aux problèmes de partage de données. The information exchanged under REACH: A cost-sharing analysis This article addresses the question of data-sharing mechanisms under REACH. The members of an information exchange forum have to share their data. This exchange requires the adoption of a compensation scheme : the owner of a data receives a monetary compensation in return for the access to his/her data. We are interested in the choice of a compensation scheme that would be fair for all participants. In order to answer this question, the exchange of information is modeled as in Dehez and Tellone [2010]. We list a collection of axioms for the compensation schemes. Various combinations of these axioms characterize several compensation schemes. Some of them coincide with well-known solutions of an associated cooperative game with transferable utility.

La diffusione e la condivisione dei dati contenuti nelle Biobanche è studiato attraverso lo statuto normativo di queste istituzioni, con particolare attenzione al diritto d'autore. Queste istituzioni sono rappresentate da un complesso organizzato di campioni biologici umani con finalità diagnostiche, terapeutiche e di ricerca. Data la relativa novità dell'argomento, il loro statuto è molto controverso e particolarmente complicato è il caso dello sfruttamento di eventuali scoperte. La titolarità della proprietà dei materiali (cellule, tessuti o organi) e la titolarità della proprietà della biobanca, intesa come entità che si occupa della gestione della banca dati, è infatti fondamentale al fine di determinare eventuali diritti su ricerche brevettabili. In Europa esiste il diritto sui generis, che stabilisce i diritti per il costitutore della banca dati, il quale stanzia un investimento economico al fine di costituire un insieme organizzato di informazioni.Tuttavia, il principale problema di questo tipo di banche dati è legato alla qualità dell'oggetto brevettabile: la materia organica, vivente ed autoreplicante. Al riguardo, vi è una netta contrapposizione tra coloro che spingono per la privatizzazione di questi beni biologici, al fine del loro possibile sfruttamento commerciale, e coloro che si rifanno ai modelli di open data sharing, che considerano Commons, \"beni comuni\", anche questo tipo di materiali organici. La tendenza generale risulta essere la seconda, proteggere il corpo umano e il suo genoma da ogni forma di sfruttamento economico, pur riconoscendo in alcuni casi la possibilità di profitti connessi con la proprietà intellettuale derivante dall'opera dell'ingegno. [Testo dell'editore].The circulation and sharing of contents in biobanks is approached with the study of the normative statutes of these institutions, with careful attention to copyright. Such institutions are an organized set of human biological specimens with diagnostic, therapeutic, and research aims. Since the issue is quite new, their statutes are controversial; moreover, the exploitation of new detections is particularly complicated. The ownership of samples (tissues, cells, organs) and the ownership of the biobank as the entity managing the database is crucial in order to determine any rights on researches that can be patented.The sui generic right in Europe states some rights for the database builder, whom allocates economic resources to organize information. However, the main issue of this kind of databases is related to the quality of the patented object: organic and living material. Regarding this fact, there exist stances for privatizing those biological specimens, while the majority consider models of open data sharing as a more suitable way, considering organic samples as \"commons\". The latter tendency seems to predominate, protecting the human body and its genome from economical exploitation, although acknowledging some kinds of profits related to the intellectual property. [Publisher's Text].

Ongoing debates surrounding Open Access to the scholarly literature are multifaceted and complicated by disparate and often polarised viewpoints from engaged stakeholders. At the current stage, Open Access has become such a global issue that it is critical for all involved in scholarly publishing, including policymakers, publishers, research funders, governments, learned societies, librarians, and academic communities, to be well-informed on the history, benefits, and pitfalls of Open Access. In spite of this, there is a general lack of consensus regarding the advantages or disadvantages of Open Access at multiple levels. This review aims to to be a resource for current knowledge on the impacts of Open Access by synthesizing important research in three major areas of impact: academic, economic and societal. While there is clearly much scope for additional research, several key trends are identified, including a broad citation advantage for researchers who publish openly, as well as additional benefits to the non-academic dissemination of their work. The economic case for Open Access is less well-understood, although it is clear that access to the research literature is key for innovative enterprises, and a range of governmental and non-governmental services. Furthermore, Open Access has the potential to save publishers and research funders considerable amounts of financial resources. The social case for Open Access is strong, in particular for advancing citizen science initiatives, and leveling the playing field for researchers in developing countries. Open Access supersedes all potential alternative modes of access to the scholarly literature through enabling unrestricted re-use, and long-term stability independent of financial constraints of traditional publishers that impede knowledge sharing. Open Access remains only one of the multiple challenges that the scholarly publishing system is currently facing. Yet, it provides one foundation for increasing engagement with researchers regarding ethical standards of publishing. We recommend that Open Access supporters focus their efforts on working to establish viable new models and systems of scholarly communication, rather than trying to undermine the existing ones as part of the natural evolution of the scholarly ecosystem. Based on this, future research should investigate the wider impacts of an ecosystem-wide transformation to a system of Open Research.

The 2019 coronavirus disease (COVID-19) pandemic increased efforts for rapid data sharing and dissemination among researchers as well as to data repositories. Researchers and studies prioritized data sharing, which increased understanding of SARS-CoV-2's pathology. Eventually, this effort to maximize collaboration and data dissemination, led to the development of mRNA vaccines. This successful effort has highlighted the importance of data sharing and the implementation of data management policies, including the National Institutes of Health's (NIH) Data Sharing Policy of 2023. Moreover, programs such as the National Institute of Allergy and Infectious Diseases (NIAID) funded Collaborative Influenza Vaccine Innovation Centers (CIVICs), have beta-tested this policy, with the help of the Statistical, Data Management and Coordination Center (SDMCC) and its data standards, and deemed it useful. However, the process has also initiated pertinent discussion on potential improvements and optimizations for the future of data sharing. Here, I use the CIVICs data sharing reporting standards and process as a data sharing example, and suggest logistical improvements to propose a better-equipped model for the vaccinology community.