22 research outputs found
At the crossroads of big science, open science, and technology transfer
Les grans infraestructures cientĂfiques s’enfronten a demandes creixents de responsabilitat pĂşblica, no nomĂ©s per la seva contribuciĂł al descobriment cientĂfic, sinĂł tambĂ© per la seva capacitat de generar valor econòmic secundari. Per construir i operar les seves infraestructures sofisticades, sovint generen tecnologies frontereres dissenyant i construint solucions tècniques per a problemes d’enginyeria complexos i sense precedents. En paral·lel, la dècada anterior ha presenciat la rĂ pida irrupciĂł de canvis tecnològics que han afectat la manera com es fa i es comparteix la ciència, cosa que ha comportat l’emergència del concepte d’Open Science (OS). Els governs avancen rĂ pidament vers aquest paradigma de OS i demanen a les grans infraestructures cientĂfiques que "obrin" els seus processos cientĂfics. No obstant, aquestes dues forces s'oposen, ja que la comercialitzaciĂł de tecnologies i resultats cientĂfics requereixen normalment d’inversions financeres importants i les empreses nomĂ©s estan disposades a assumir aquest cost si poden protegir la innovaciĂł de la imitaciĂł o de la competència deslleial. Aquesta tesi doctoral tĂ© com a objectiu comprendre com les noves aplicacions de les TIC afecten els resultats de la recerca i la transferència de tecnologia resultant en el context de les grans infraestructures cientĂfiques. La tesis pretĂ©n descobrir les tensions entre aquests dos vectors normatius, aixĂ com identificar els mecanismes que s’utilitzen per superar-les. La tesis es compon de quatre estudis: 1) Un estudi que aplica un mètode de recerca mixt que combina dades de dues enquestes d’escala global realitzades online (2016, 2018), amb dos cas d’estudi de dues comunitats cientĂfiques en fĂsica d’alta energia i biologia molecular que avaluen els factors explicatius darrere les prĂ ctiques de compartir dades per part dels cientĂfics; 2) Un estudi de cas d’Open Targets, una infraestructura d’informaciĂł basada en dades considerades bens comuns, on el Laboratori Europeu de Biologia Molecular-EBI i empreses farmacèutiques col·laboren i comparteixen dades cientĂfiques i eines tecnològiques per accelerar el descobriment de medicaments; 3) Un estudi d’un conjunt de dades Ăşnic de 170 projectes finançats en el marc d’ATTRACT (un nou instrument de la ComissiĂł Europea liderat per les grans infraestructures cientĂfiques europees) que tĂ© com a objectiu comprendre la naturalesa del procĂ©s de serendipitat que hi ha darrere de la transiciĂł de tecnologies de grans infraestructures cientĂfiques a aplicacions comercials abans no anticipades. ; i 4) un cas d’estudi sobre la tecnologia White Rabbit, un hardware sofisticat de codi obert desenvolupat al Consell Europeu per a la Recerca Nuclear (CERN) en col·laboraciĂł amb un extens ecosistema d’empreses.Las grandes infraestructuras cientĂficas se enfrentan a crecientes demandas de responsabilidad pĂşblica, no solo por su contribuciĂłn al descubrimiento cientĂfico sino tambiĂ©n por su capacidad de generar valor econĂłmico para la sociedad. Para construir y operar sus sofisticadas infraestructuras, a menudo generan tecnologĂas de vanguardia al diseñar y construir soluciones tĂ©cnicas para problemas de ingenierĂa complejos y sin precedentes. Paralelamente, la dĂ©cada anterior ha visto la irrupciĂłn de rápidos cambios tecnolĂłgicos que afectan la forma en que se genera y comparte la ciencia, lo que ha llevado a acuñar el concepto de Open Science (OS). Los gobiernos se están moviendo rápidamente hacia este nuevo paradigma y están pidiendo a las grandes infraestructuras cientĂficas que "abran" el proceso cientĂfico. Sin embargo, estas dos fuerzas se oponen, ya que la comercializaciĂłn de tecnologĂa y productos cientĂficos generalmente requiere importantes inversiones financieras y las empresas están dispuestas a asumir este coste solo si pueden proteger la innovaciĂłn de la imitaciĂłn o la competencia desleal. Esta tesis doctoral tiene como objetivo comprender cĂłmo las nuevas aplicaciones de las TIC están afectando los resultados cientĂficos y la transferencia de tecnologĂa resultante en el contexto de las grandes infraestructuras cientĂficas. La tesis pretende descubrir las tensiones entre estas dos fuerzas normativas e identificar los mecanismos que se emplean para superarlas. La tesis se compone de cuatro estudios: 1) Un estudio que emplea un mĂ©todo mixto de investigaciĂłn que combina datos de dos encuestas de escala global realizadas online (2016, 2018), con dos caso de estudio sobre dos comunidades cientĂficas distintas -fĂsica de alta energĂa y biologĂa molecular- que evalĂşan los factores explicativos detrás de las prácticas de intercambio de datos cientĂficos; 2) Un caso de estudio sobre Open Targets, una infraestructura de informaciĂłn basada en datos considerados como bienes comunes, donde el Laboratorio Europeo de BiologĂa Molecular-EBI y compañĂas farmacĂ©uticas colaboran y comparten datos cientĂficos y herramientas tecnolĂłgicas para acelerar el descubrimiento de fármacos; 3) Un estudio de un conjunto de datos Ăşnico de 170 proyectos financiados bajo ATTRACT, un nuevo instrumento de la ComisiĂłn Europea liderado por grandes infraestructuras cientĂficas europeas, que tiene como objetivo comprender la naturaleza del proceso fortuito detrás de la transiciĂłn de las tecnologĂas de grandes infraestructuras cientĂficas a aplicaciones comerciales previamente no anticipadas ; y 4) un estudio de caso de la tecnologĂa White Rabbit, un sofisticado hardware de cĂłdigo abierto desarrollado en el Consejo Europeo de InvestigaciĂłn Nuclear (CERN) en colaboraciĂłn con un extenso ecosistema de empresas.Big science infrastructures are confronting increasing demands for public accountability, not only within scientific discovery but also their capacity to generate secondary economic value. To build and operate their sophisticated infrastructures, big science often generates frontier technologies by designing and building technical solutions to complex and unprecedented engineering problems. In parallel, the previous decade has seen the disruption of rapid technological changes impacting the way science is done and shared, which has led to the coining of the concept of Open Science (OS). Governments are quickly moving towards the OS paradigm and asking big science centres to "open up” the scientific process. Yet these two forces run in opposition as the commercialization of scientific outputs usually requires significant financial investments and companies are willing to bear this cost only if they can protect the innovation from imitation or unfair competition. This PhD dissertation aims at understanding how new applications of ICT are affecting primary research outcomes and the resultant technology transfer in the context of big and OS. It attempts to uncover the tensions in these two normative forces and identify the mechanisms that are employed to overcome them. The dissertation is comprised of four separate studies: 1) A mixed-method study combining two large-scale global online surveys to research scientists (2016, 2018), with two case studies in high energy physics and molecular biology scientific communities that assess explanatory factors behind scientific data-sharing practices; 2) A case study of Open Targets, an information infrastructure based upon data commons, where European Molecular Biology Laboratory-EBI and pharmaceutical companies collaborate and share scientific data and technological tools to accelerate drug discovery; 3) A study of a unique dataset of 170 projects funded under ATTRACT -a novel policy instrument of the European Commission lead by European big science infrastructures- which aims to understand the nature of the serendipitous process behind transitioning big science technologies to previously unanticipated commercial applications; and 4) a case study of White Rabbit technology, a sophisticated open-source hardware developed at the European Council for Nuclear Research (CERN) in collaboration with an extensive ecosystem of companies
The Nexus of Translational Action
Sensors, actuators, and controllers are digital objects fundamental to automation-intensive industries such as transportation, manufacturing, and energy. As technologies that enable and arbitrate the transition from physical to digital worlds, they are increasingly pervasive in all facets of industry and logistics, consumer technologies, or even medicine. Hybrid digital objects with physical and digital components are composed of bitstrings that are inscribed onto a material bearer. Translational action refers to how bitstrings are accessed in the material bearer or how they are moved from one layer of the bearer to another. We perform an inductive study of 170 sensing, computational, and imaging technologies originating from leading scientific research institutions to better understand the nature of translational action. Across four physical and digital configurations, we identify seven forms of translational action. The findings offer insight into cybernetic control theory central to automated systems to understand the nature of their logic, processes, and interdependence
At the crossroads of big science, open science, and technology transfer
Les grans infraestructures cientĂfiques s’enfronten a demandes creixents de responsabilitat pĂşblica, no nomĂ©s per la seva contribuciĂł al descobriment cientĂfic, sinĂł tambĂ© per la seva capacitat de generar valor econòmic secundari. Per construir i operar les seves infraestructures sofisticades, sovint generen tecnologies frontereres dissenyant i construint solucions tècniques per a problemes d’enginyeria complexos i sense precedents. En paral·lel, la dècada anterior ha presenciat la rĂ pida irrupciĂł de canvis tecnològics que han afectat la manera com es fa i es comparteix la ciència, cosa que ha comportat l’emergència del concepte d’Open Science (OS). Els governs avancen rĂ pidament vers aquest paradigma de OS i demanen a les grans infraestructures cientĂfiques que "obrin" els seus processos cientĂfics. No obstant, aquestes dues forces s'oposen, ja que la comercialitzaciĂł de tecnologies i resultats cientĂfics requereixen normalment d’inversions financeres importants i les empreses nomĂ©s estan disposades a assumir aquest cost si poden protegir la innovaciĂł de la imitaciĂł o de la competència deslleial. Aquesta tesi doctoral tĂ© com a objectiu comprendre com les noves aplicacions de les TIC afecten els resultats de la recerca i la transferència de tecnologia resultant en el context de les grans infraestructures cientĂfiques. La tesis pretĂ©n descobrir les tensions entre aquests dos vectors normatius, aixĂ com identificar els mecanismes que s’utilitzen per superar-les. La tesis es compon de quatre estudis: 1) Un estudi que aplica un mètode de recerca mixt que combina dades de dues enquestes d’escala global realitzades online (2016, 2018), amb dos cas d’estudi de dues comunitats cientĂfiques en fĂsica d’alta energia i biologia molecular que avaluen els factors explicatius darrere les prĂ ctiques de compartir dades per part dels cientĂfics; 2) Un estudi de cas d’Open Targets, una infraestructura d’informaciĂł basada en dades considerades bens comuns, on el Laboratori Europeu de Biologia Molecular-EBI i empreses farmacèutiques col·laboren i comparteixen dades cientĂfiques i eines tecnològiques per accelerar el descobriment de medicaments; 3) Un estudi d’un conjunt de dades Ăşnic de 170 projectes finançats en el marc d’ATTRACT (un nou instrument de la ComissiĂł Europea liderat per les grans infraestructures cientĂfiques europees) que tĂ© com a objectiu comprendre la naturalesa del procĂ©s de serendipitat que hi ha darrere de la transiciĂł de tecnologies de grans infraestructures cientĂfiques a aplicacions comercials abans no anticipades. ; i 4) un cas d’estudi sobre la tecnologia White Rabbit, un hardware sofisticat de codi obert desenvolupat al Consell Europeu per a la Recerca Nuclear (CERN) en col·laboraciĂł amb un extens ecosistema d’empreses.Las grandes infraestructuras cientĂficas se enfrentan a crecientes demandas de responsabilidad pĂşblica, no solo por su contribuciĂłn al descubrimiento cientĂfico sino tambiĂ©n por su capacidad de generar valor econĂłmico para la sociedad. Para construir y operar sus sofisticadas infraestructuras, a menudo generan tecnologĂas de vanguardia al diseñar y construir soluciones tĂ©cnicas para problemas de ingenierĂa complejos y sin precedentes. Paralelamente, la dĂ©cada anterior ha visto la irrupciĂłn de rápidos cambios tecnolĂłgicos que afectan la forma en que se genera y comparte la ciencia, lo que ha llevado a acuñar el concepto de Open Science (OS). Los gobiernos se están moviendo rápidamente hacia este nuevo paradigma y están pidiendo a las grandes infraestructuras cientĂficas que "abran" el proceso cientĂfico. Sin embargo, estas dos fuerzas se oponen, ya que la comercializaciĂłn de tecnologĂa y productos cientĂficos generalmente requiere importantes inversiones financieras y las empresas están dispuestas a asumir este coste solo si pueden proteger la innovaciĂłn de la imitaciĂłn o la competencia desleal. Esta tesis doctoral tiene como objetivo comprender cĂłmo las nuevas aplicaciones de las TIC están afectando los resultados cientĂficos y la transferencia de tecnologĂa resultante en el contexto de las grandes infraestructuras cientĂficas. La tesis pretende descubrir las tensiones entre estas dos fuerzas normativas e identificar los mecanismos que se emplean para superarlas. La tesis se compone de cuatro estudios: 1) Un estudio que emplea un mĂ©todo mixto de investigaciĂłn que combina datos de dos encuestas de escala global realizadas online (2016, 2018), con dos caso de estudio sobre dos comunidades cientĂficas distintas -fĂsica de alta energĂa y biologĂa molecular- que evalĂşan los factores explicativos detrás de las prácticas de intercambio de datos cientĂficos; 2) Un caso de estudio sobre Open Targets, una infraestructura de informaciĂłn basada en datos considerados como bienes comunes, donde el Laboratorio Europeo de BiologĂa Molecular-EBI y compañĂas farmacĂ©uticas colaboran y comparten datos cientĂficos y herramientas tecnolĂłgicas para acelerar el descubrimiento de fármacos; 3) Un estudio de un conjunto de datos Ăşnico de 170 proyectos financiados bajo ATTRACT, un nuevo instrumento de la ComisiĂłn Europea liderado por grandes infraestructuras cientĂficas europeas, que tiene como objetivo comprender la naturaleza del proceso fortuito detrás de la transiciĂłn de las tecnologĂas de grandes infraestructuras cientĂficas a aplicaciones comerciales previamente no anticipadas ; y 4) un estudio de caso de la tecnologĂa White Rabbit, un sofisticado hardware de cĂłdigo abierto desarrollado en el Consejo Europeo de InvestigaciĂłn Nuclear (CERN) en colaboraciĂłn con un extenso ecosistema de empresas.Big science infrastructures are confronting increasing demands for public accountability, not only within scientific discovery but also their capacity to generate secondary economic value. To build and operate their sophisticated infrastructures, big science often generates frontier technologies by designing and building technical solutions to complex and unprecedented engineering problems. In parallel, the previous decade has seen the disruption of rapid technological changes impacting the way science is done and shared, which has led to the coining of the concept of Open Science (OS). Governments are quickly moving towards the OS paradigm and asking big science centres to "open up” the scientific process. Yet these two forces run in opposition as the commercialization of scientific outputs usually requires significant financial investments and companies are willing to bear this cost only if they can protect the innovation from imitation or unfair competition. This PhD dissertation aims at understanding how new applications of ICT are affecting primary research outcomes and the resultant technology transfer in the context of big and OS. It attempts to uncover the tensions in these two normative forces and identify the mechanisms that are employed to overcome them. The dissertation is comprised of four separate studies: 1) A mixed-method study combining two large-scale global online surveys to research scientists (2016, 2018), with two case studies in high energy physics and molecular biology scientific communities that assess explanatory factors behind scientific data-sharing practices; 2) A case study of Open Targets, an information infrastructure based upon data commons, where European Molecular Biology Laboratory-EBI and pharmaceutical companies collaborate and share scientific data and technological tools to accelerate drug discovery; 3) A study of a unique dataset of 170 projects funded under ATTRACT -a novel policy instrument of the European Commission lead by European big science infrastructures- which aims to understand the nature of the serendipitous process behind transitioning big science technologies to previously unanticipated commercial applications; and 4) a case study of White Rabbit technology, a sophisticated open-source hardware developed at the European Council for Nuclear Research (CERN) in collaboration with an extensive ecosystem of companies
Time as a Service: White Rabbit at CERN
While pushing forward the boundaries of human understanding of the fundamental structure of the Universe, scientists and engineers at CERN also contributed to innovation above and beyond their immediate scientific mission by developing White Rabbit (WR)
The stickiness of scientific data
Researchers are generating unprecedented volumes of data. As the expectations of big scientific data grow, the expectations on the potential of sharing it grow as well. Government-funding entities have placed data sharing at the crux of scientific policy. Yet, considering the apparent barriers to its wide adoption, we lack a recent overview of whether researchers share their data, how and what mechanisms enable research data sharing (why). Our study engages in a mixed-method design by combining survey data collected in 2016 and 2018; and qualitative data from two case studies sequentially sampled within two scientific communities: high-energy physics and molecular biology. As a lens to understand the factors behind data sharing practices, we draw upon the notion of epistemic cultures and the collective action theory perspective to shed light on the incentives and deterrents that scientists confront when considering contributions to the collective goods of data sharin
From Bits to Atoms: Open Source Hardware at CERN
Although considered a relatively recent phenomenon of the past decade, open source hardware (OSH) is already influencing commercial hardware development. However, a common belief is that the greater economic cost and complexity of hybrid digital objects (i.e., digital objects with both hardware and software) precludes their development with open source methods traditionally used for software. We study a sophisticated OSH named White Rabbit initiated at CERN and developed through a vibrant and heterogenous open source community. Our findings show that the assumption that hardware and software require fundamentally distinctive development and production modes should be replaced with a more nuanced differentiation characterized by three main attributes describing an object’s composition: embodiment, modularity, and granularity. Taken together, these three attributes determine how a hybrid object is developed throughout its evolution in an open source community. Our research offers several contributions. First, we provide a more nuanced view of the consequences of the material embodiment of hardware. Once considered a simple deterrent to open source development, we describe how economic cost is subordinate to more influential aspects of an object’s physical layers: as the open source community modifies the object to accommodate the operating requirements of diverse physical instantiations, such modifications can be incorporated in the logical design covered by the open source license. Additionally, we show how embodiment, modularity, and granularity progress through the object’s evolution and how this maturation subsequently affects development modes. We trace the implications of our findings for hybrids and digital object conceptualizations in IS research, open source development and, more broadly, normative implications for OSH in scientific and commercial computing
DigComp into Action: Get inspired, make it happen. A user guide to the European Digital Competence Framework
This Guide supports stakeholders in the implementation of the European Digital Competence Framework (DigComp) through sharing of 38 existing inspiring practices of DigComp implementations. These are illustrated by 50 content items consisting of Case studies and Tools.
The list of examples provided in the Guide’s annex is not exhaustive and aims to illustrate the wide range of DigComp implementation practices.JRC.B.4-Human Capital and Employmen
Obsessed with time? White rabbit at CERN
To conduct research in fundamental science, big-science research infrastructures develop some of the most sophisticated technologies in existence. As such, mechanisms that can facilitate the transfer and commercialization of these technologies have vast potential to contribute to economic and social welfare. Scientists and engineers at CERN were confronted with the problem of minute data latency that was corrupting scientific measurements in their geographically distributed computing network. In response, they developed White Rabbit (WR) as open source hardware (OSH). In a context of basic research and a deliberate decision to share the R&D process openly with no IP restrictions, WR is now commercialized in diverse economic sectors including finance, telecommunications, energy, Internet of Things (IoT), and air traffic control. We analyze the emergence, development, and exploitation of WR to a) identify the antecedents in which complex R&D-intensive OSH differs from open source software (OSS), b) capture the mechanisms employed by CERN to stimulate firms’ R&D revelation and WR collaborative development, and c) investigate the business model configurations that companies have adopted in the commercial implementation of WR