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Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled to mass spectrometry (MS) data sets, due to the high levels of data reduction that occur between raw data and machine learning-ready data. Since predictive proteomics is an emerging field, when predicting peptide behavior in LC-MS setups, each lab often uses unique and complex data processing pipelines in order to maximize performance, at the cost of accessibility and reproducibility. For this reason we introduce ProteomicsML, an online resource for proteomics-based data sets and tutorials across most of the currently explored physicochemical peptide properties. This community-driven resource makes it simple to access data in easy-to-process formats, and contains easy-to-follow tutorials that allow new users to interact with even the most advanced algorithms in the field. ProteomicsML provides data sets that are useful for comparing state-of-the-art machine learning algorithms, as well as providing introductory material for teachers and newcomers to the field alike. The platform is freely available at https://www.proteomicsml.org/, and we welcome the entire proteomics community to contribute to the project at https://github.com/ProteomicsML/ProteomicsML.

This deliverable contains the specifications document that describes the technicalrequirements and the plan for implementation of the Community Platform based on the technical and user needs from the consortium partners.

Conference within thewithin Citizen Social Science & Complex Systems Science (CCS’20 Satellite Workshop) You can access to the program in this link [Here]&nbsp

Open Access and Open Scholarship have revolutionized the way scholarly artefacts are evaluated and published, while the introduction of new technologies and media in scientific workflows has changed the “how” and to “whom” science is communicated, and how stakeholders interact with the scientific community and the broader public. The EU funded project OpenUP is connecting people, information and tools and provides a knowledge hub and a validated framework for the review, assessment and dissemination aspects of the research lifecycle, under the prism of a gender-sensitive Open Science.

Producción Científica, Learning design tools aim at supporting practitioners in their task of creating more innovative and effective computer-supported learning situations. Despite there being a myriad of proposed tools, their use presents challenges that recent studies link with practitioners' varied pedagogical approaches and context restrictions, as well as with barriers to practical application derived from the fact that most tools only cover limited functionality and do not support cooperation between practitioners. In this paper we investigate whether it is possible to provide a flexible community system that supports multiple learning design tasks. We propose an Integrated Learning Design Environment (ILDE), which is a networked system integrating collaboration functions, design editors and middleware that enables deployment of the designed learning situations into Virtual Learning Environments. We describe the iterative user-centered process adopted in the design of ILDE as well as its architecture. The architecture is implemented to show its feasibility and that it is capable of providing the targeted functionality. We also present the results of its use in training workshops with 148 practitioners from five different institutions in vocational training, higher and adult education. Some of the learning designs were deployed in VLEs and enacted with students in real learning situations.

Este trabalho tem como objetivo apresentar o Hived, um projeto que oferece resposta às necessidades de formação, rede de contactos e oportunidades de trabalho dos freelancers criativos, oferecendo um espaço online onde estes podem progredir ao longo das suas carreiras. Na primeira parte do trabalho apresenta-se o enquadramento teórico, cultural e económico que sustenta a necessidade identificada anteriormente e o contexto de criação do Hived como uma plataforma comunitária online. Este enquadramento inclui o contexto da criatividade no mundo globalizado e o estado do mercado freelancer atualmente. De seguida é apresentado o modelo de negócio do Hived, assim como o estudo do mercado e público-alvo e a análise da concorrência. Segue-se o plano de marketing e a análise financeira que prova a viabilidade do projeto. This paper aims to present Hived, a project that answers to the necessities of education, net-working and job opportunities for creative freelancers, offering them and online space where they can progress on the course of their careers. A cultural and economic theoretical framework is presented in the first part of this project in order to sustain the necessity identified before and the context of the creation of Hived as an online community platform. This framework includes the context of creativity in the globalized world and the current state of the freelancer market. Then it is introduced the business model of Hived, as well as the market study, target audience and an analysis of the competition. It follows the marketing plan and the financial analysis that proves the viability of the project.

The amount of open data available for hydrology research is continually growing and provides opportunities for new science and products. Although the existing digital infrastructures (GEOSS Portal, INSPIRE community geoportal and other initiatives) provide access to open data, many hydrologists still encounter difficulties in finding and using open data. Since the time spent on collecting and preparing data usually amounts to more than the time spent on an experiment, any improvement on finding, understanding, accessing and using open data is greatly beneficial. The Spatial Information Platform (SIP) has been developed to tackle these issues within the SWITCH-ON European funded FP7 project. The SIP has been designed as a toolbox of interconnected software components based on open standards that provide to the user all the necessary functionalities as described in the Publish-Find-Bind (PFB) pattern. In other words, this means that the SIP enables users to locate relevant and suitable data for the task they are carrying out and to access and transform it (filtering, extraction, selection, conversion, aggregation). Moreover, the SIP can be used to provide descriptive information about the data and to publish it so others can find it and use it. The SIP is based on existing open data protocols such as OGC-CSW, OGC-WMS, OpenDAP and open-source technologies such as PostgreSQL/PostGIS, GeoServer and pyCSW among others. The SIP is divided in three main user interfaces: the BYOD (Browse your open dataset) web interface, the Expert GUI tool and the Upload Data and Metadata web interface. The BYOD (Browse Your Own Data) HTML5 client is the main entry point for end users that want to search and browse open data in the SIP. The BYOD has a map interface based on Leaflet JavaScript libraries so that the users can search more efficiently. The Expert GUI is an integrated desktop application which can be run by verified experts and members of the SWITCH-ON project only and provides full metadata editing capabilities. The web-based Open Data Registration Tool is designed to provide a user-friendly upload and metadata description interface the end users community. In conclusion, the Spatial Information Platform (SIP) provides to the hydrological science community a set of tools for better understanding and ease of use of hydrological open-data. Moreover, the SIP has been based on well-known OGC standards that will allow the connection and data harvesting from popular EU open data portals such as the GEOSS system of systems.

The amount of open data available for hydrology research is continually growing and provides opportunities for new science and products. Although the existing digital infrastructures (GEOSS Portal, INSPIRE community geoportal and other initiatives) provide access to open data, many hydrologists still encounter difficulties in finding and using open data. Since the time spent on collecting and preparing data usually amounts to more than the time spent on an experiment, any improvement on finding, understanding, accessing and using open data is greatly beneficial. The Spatial Information Platform (SIP) has been developed to tackle these issues within the SWITCH-ON European funded FP7 project. The SIP has been designed as a toolbox of interconnected software components based on open standards that provide to the user all the necessary functionalities as described in the Publish-Find-Bind (PFB) pattern. In other words, this means that the SIP enables users to locate relevant and suitable data for the task they are carrying out and to access and transform it (filtering, extraction, selection, conversion, aggregation). Moreover, the SIP can be used to provide descriptive information about the data and to publish it so others can find it and use it. The SIP is based on existing open data protocols such as OGC-CSW, OGC-WMS, OpenDAP and open-source technologies such as PostgreSQL/PostGIS, GeoServer and pyCSW among others. The SIP is divided in three main user interfaces: the BYOD (Browse your open dataset) web interface, the Expert GUI tool and the Upload Data and Metadata web interface. The BYOD (Browse Your Own Data) HTML5 client is the main entry point for end users that want to search and browse open data in the SIP. The BYOD has a map interface based on Leaflet JavaScript libraries so that the users can search more efficiently. The Expert GUI is an integrated desktop application which can be run by verified experts and members of the SWITCH-ON project only and provides full metadata editing capabilities. The web-based Open Data Registration Tool is designed to provide a user-friendly upload and metadata description interface the end users community. In conclusion, the Spatial Information Platform (SIP) provides to the hydrological science community a set of tools for better understanding and ease of use of hydrological open-data. Moreover, the SIP has been based on well-known OGC standards that will allow the connection and data harvesting from popular EU open data portals such as the GEOSS system of systems.

In this paper a concept for a community platform is introduced focusing on human factors of motivation and barriers in the context of innovation. Building on the state of the art, a three year case study in cooperation with Dr. Ing. h.c. F. Porsche AG is at the core. In a first step, a questionnaire and interviews are used to point out that a new attractive channel for ideas is needed. Based on these findings, in a second step, a software prototype is being designed and introduced in a pilot project with ca. 200 users. By using a questionnaire and expert workshops, in a last step, this project is evaluated as appealing to the community and the generated content demonstrates to be valueable to specific design activities.