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Workshop on '(reviewing) data management plans by Esther Plomp for the 'Spring Training Days' course on the 20th of May. This includes the short introduction presentation and the google doc that was used for the interactive part of the session.

In the transition towards Open Access (OA), institutional publishing is challenged by fragmentation and varying service quality, visibility, and sustainability. To address this issue, DIAMAS gathers 23 organisations from 12 European countries, well-versed in OA academic publishing and scholarly communication. The project will: 1. Map the current landscape of Institutional Publishing Service Providers (IPSPs) in 25 countries of the ERA with special attention for IPSPs that do not charge fees for publishing or reading. This will yield a taxonomy of IPSPs and an IPSP landscape report, a basis for the rest of the project. 2. Coordinate and improve the efficiency and quality of IPSPs by developing a European Quality Standard for Institutional Publishing (EQSIP). This quality seal will professionalise, strengthen and reduce the fragmentation of institutional publishing in Europe. EQSIP will serve as a benchmark for a gap analysis of the data. The DMP/RDMP outlines how data are to be handled (secured, stored, accessed, preserved) both during the project, and after the project is completed., Deliverable under EC review

The demands of Open Science increase the responsibilities of researchers, for example writing a data management plan. In this seminar, we will invite an expert from GESIS to address this topic by first outlining the benefits and the costs of Open Science, then focus on data management plans and data management plan tools available. A recent work done at GESIS will also be presented in which they analyzed the time spent on data curation, i.e. making data ready to be published. We welcome those who want to know more about data management plan and those who are involved in data sharing process.

Writing a good data management plan is an integral part of successful open social science practice and a key factor in securing research funding. Yet many researchers have difficulty in fully engaging with writing and implementing their data management plan. This can become a barrier to the publishing high quality, create extra work in depositing discoverable research data, or even lead to irretrievable data losses. Hannah Boroudjou and Helen Porter showed how to incorporate best practice in data management from the earliest stages of a research project. Key steps include: Demonstrating and following quality assurance measures; Making sure you keep good documentation and descriptions of your data; Addressing technical and storage issues; Thinking about copyright and ownership of your data; Identifying all of the data that you can publish or need to deposit in an open science database; and, Deciding the appropriate levels of access for different parts of your dataset. This event was part of a series of workshops organised to support the development of theCIVICA Research Open Science Handbook for the Social Sciences.

Research Data Management (RDM) is an active process and should be considered throughout the research lifecycle. Ethical principles such as FAIR (Findable, Accessible, Interoperable and Reproducible) data sharing and the CARE principles are outlined. Data Management Plans and where to store research data are also addressed., The attached include the slides and recording of this paper and an edited transcript. The transcript can be viewed using a text editor such as Notepad or used for subtitles., Repository Training for Cultural Heritage Professionals: First online event

This presentation is from the CIVICA Research Open Science for the Social Sciences workshop on Introduction to Research Data Management and Data Management Plans. Dr Thomas Bourkeprovided participants with an overview on the following topics relating to the management of research data: Data discovery, input and quality control; Data protection and database copyright; Data generation, data processing and ethical use; Managing data during the research project cycle; Data management plans; Repositing and preserving data; and, ICT support and international guidelines.

Preprint of a paper submitted to Gigascience. Abstract:The relationship between people, place, and data underpins some of the greatest challenges and opportunities of the 21st century. While there has been general enthusiasm for and work towards Findable, Accessible, Interoperable, and Reusable (FAIR) data for Open Science, only more recently have these data-centric principles been extended into dimensions important to people and place. Notably, the CARE Principles for Indigenous Data Governance, which affect collective benefit, authority to control, responsibility, and ethics. The FAIR Island Project seeks to translate these ideals into practice leveraging the institutional infrastructure provided by scientific field stations. Starting with field stations in French Polynesia as key use cases that are exceptionally well connected to international research networks, FAIR Island builds interoperability between different components of critical research infrastructure, helping connect these to societal benefit areas. The goal is not only to increase reuse of scientific data and the awareness of work happening at the field stations, but more generally to accelerate place-based research for sustainable development. FAIR Island works reflexively, aiming to scale horizontally through networks of field stations and to serve as a model for other sites of intensive long-term scientific study.

ELIXIR Portugal | BioData.pt, is strongly committed to ELIXIR’s mission, particularly with respect to the development and adoption of best practices in data management and open science principles. “Ready for BioData Management?” is a capacity building program in data management for the life sciences to empower researchers and institutions in managing their data more effectively and efficiently. To guide researchers´ efforts BioData hired the 1st Data Steward for Life Sciences in Portugal. The work has been carried out at the Instituto Gulbenkian de Ciência, where the Data Steward assists researchers in research data management policies and practices and help to define policies, workflows, and procedures of the institute.

This is a two-year National Leadership Grant for Libraries Demonstration Project to facilitate a multi-university study of faculty data management plans (DMPs). The primary outputs of this project will be an analytic rubric to standardize the review of data management plans as a means to inform targeted expansion or development of research data services at academic libraries; and a study utilizing the rubric that presents the results of data management plan analyses at five universities. This project was made possible in part by the Institute of Museum and Library Services grant number LG-07-13-0328. Until we migrate all of the content from the DART web site, more information (papers, presentations, etc.) can be found: http://dmpresearch.library.oregonstate.edu/

The Standardized Data Management Plan for Educational Research (in Germany) has been developed since 2019 as part of the project Domain Data Protocols for Educational Research (DDP-Bildung), funded by the Federal Ministry of Education and Research. The Stamp can be individually adapted to the needs of different projects and supports data management from the application to the archiving of data. It assists researchers implementing the rules of good scientific practice as well as complying with possible requirements of funding institutions, e.g., to make data available for subsequent use by third parties. After a brief presentation of the Stamp, workshop-participants from various research disciplines discussed approaches to transfer the Stamp to other disciplines., KonsortSWD is funded by Deutsche Forschungsgemeinschaft (DFG) as part of NFDI – project number: 442494171

Presentation slides forIntroduksjon til datahåndteringsplaner The webinar will introduces Data Management Plans as tool to ensure good data handling practice in a research project and as required by research funders such as the Research Council of Norway or the Horizon Europe funding scheme. The slides are in Norwegian

The poster is about Argos (argos.openaire.eu), OpenAIRE’s machine actionable (Data Management Planning) DMP service, which is also available as an EOSC resource. Argos is a ready-to-use RDA compliant service for creating and publishing DMP outputs according to Open and FAIR principles. It is hooked into the OpenAIRE ecosystem and interconnects with its underlying services and the Research Graph to offer maximum capabilities for metadata contextualisation, integration with diverse research workflows, and validation of input data comprising DMPs. Argos caters to researchers and has implemented mechanisms that minimize the effort needed to write DMPs by automating the retrieval of scientific information from more than 12.000 validated sources. That way it makes gathering of information that is scattered across diverse RDM platforms easier and helps with portraying complete Research Data Management (RDM) paths and lifecycles. It does so by providing apt solutions to timely issues and challenges regarding the discovery, content, re-use and exploitation of DMPs, such as: Having a collection of structured and ready-to-use machine actionable DMP templates describing and publishing DMPs according to global controlled vocabularies, such as COAR exposing DMPs appropriately to enable DMPs' discovery and enhancing OpenAIRE's discovery portal with distinct entities that can be easily searched and found. assigning licenses and DOIs describing individual datasets separately which can be copied and used in multiple DMPs Using tags to distinguish reused datasets from others that are described in single DMPs. sending its DMP data to MONITOR for tracking and exploitation purposes. The poster aims to offer a better understanding of how Argos can be used by libraries to support their researchers in writing DMPs, both as a means to foster data engagement within their institutions and as the tool to comply with Horizon Europe RDM requirements. Finally, libraries can leverage on the Argos capabilities to integrate with ad-hoc services within their institutions and enhance the European Research and Innovation landscape by building interconnected local RDM ecosystems.

As policies, good practices and funder mandates on research data management evolve, more emphasis has been put on the licencing of data. Licencing information allow potential re-users to quickly identify what they can do with the data in question and is therefore an important component to ensure the reusability of research. In my research I analyse a pre-existing collection of 840 Horizon 2020 public data management plans (DMPs) available on the repository of the University of Vienna, Phaidra,, to determine which ones mention creative commons licences and among those who do, what licences are being used. I find that 36% of DMPs mention creative commons and among those a number of different approaches towards licencing (overall policy per project, licencing decisions per dataset, licencing decisions per partner, licensing decision per data format, licensing decision per perceived stakeholder interest) exist, often clad in rather vague language with CC licences being “recommended” or “suggested”. Some DMPs also “kick the can further down the road” by mentioning that “a” CC licence will be used, but not which one. However, among those DMPs that do mention specific CC licences, a clear favourite emerges: the CC-BY licence, which accounts for half of the total mentioning of a specific licence. The fact that 64% of DMPs did not mention creative commons at all is an indication for the need for further training and awareness raising on data management in general and licencing in particular in Horizon Europe. For those DMPs that do mention specific licences, 60% would be compliant with Horizon Europe requirements (CC-BY or CC0). However, it should be carefully monitored whether the other 40% of content that is currently licenced with non-Horizon Europe compliant licences will in the future move to CC-BY or CC0 or whether such content will in the future simply be kept fully closed by projects through invoking the “as open as possible, as close as necessary” principle.

As part of FAIRsFAIR's policy support programme, the project team reviewedthe draft Tetiaroa Research Data Policy against our set of policy enhancement recommendations and provided a brief summary report outlining the results and suggestions. For more on the FAIRsFAIR support programme and instruments used, please seehttps://fairsfair.eu/policy-recommendations-and-support-programme.&nbsp

Background: Data Management Plans (DMPs) are at the heart of many research funder requirements for data management and open data, including the EU’s Framework Programme for Research and Innovation, Horizon 2020. This article provides a summary of the findings of the DMP Use Case study, conducted as part of OpenAIRE Advance. Methods: As part of the study we created a vetted collection of over 800 Horizon 2020 DMPs. Primarily, however, we report the results of qualitative interviews and a quantitative survey on the experience of Horizon 2020 projects with DMPs. Results & Conclusions: We find that a significant number of projects had to develop a DMP for the first time in the context of Horizon 2020, which points to the importance of funder requirements in spreading good data management practices. In total, 82% of survey respondents found DMPs useful or partially useful, beyond them being “just” an European Commission (EC) requirement. DMPs are most prominently developed within a project’s Management Work Package. Templates were considered important, with 40% of respondents using the EC/European Research Council template. However, some argue for a more tailor-made approach. The most frequent source for support with DMPs were other project partners, but many beneficiaries did not receive any support at all. A number of survey respondents and interviewees therefore ask for a dedicated contact point at the EC, which could take the form of an EC Data Management Helpdesk, akin to the IP helpdesk. If DMPs are published, they are most often made available on the project website, which, however, is often taken offline after the project ends. There is therefore a need to further raise awareness on the importance of using repositories to ensure preservation and curation of DMPs. The study identifies IP and licensing arrangements for DMPs as promising areas for further research.

The Canadian Tri-Agency Research Data Management Policy, released early in 2021, introduced new requirements for researchers applying for grants from CIHR, SSHRC, and NSERC. The various requirements can be intimidating, but data management doesn’t need to be a headache. This workshop will cover current and anticipated requirements, teach you about the most important elements of a data management plan, and discuss data sharing and archiving. This workshop will also introduce a new Western-customized assistant for writing Data Management Plans that will help you choose the most appropriate, locally supported technologies.

These are the slides of a presentation delivered duringthe Open Science Cafe on February 3, 2022. The presentation provides an introduction to data management plans, discussing what data management plans are, why they matter, and how to write them. The Open Science Cafes arerecurring, informal virtual meetings of the Italian scientific community to dicuss various topics and new developments related to open science. Further information about the Open Science Cafe can be found here: https://www.icdi.it/it/attivita/tf-cc/open-science-cafe&nbsp

Data management plans (DMPs) are recognised as an important element of good practice in research management, including by the European Commission and Science Europe. Especially since the beginning of the EC Horizon 2020 programme, funders at national and international level expect research grant holders to complete a DMP demonstrating they have planned how data will be managed from the outset of a research project. Research Producing Organisations (RPOs) are expected to play their part, to help their researchers in producing data that is FAIR, and in depositing it in a trustworthy repository that can keep it in FAIR condition. And in some cases including the EC Horizon Europe programme, there is a need for DMPs to cover all research outputs (data, code, models, samples etc.), to be updated throughout the project, and ultimately made available as a project deliverable. ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of Supporting data management planning. The guide aims to help Research Performing Organisations assess their own needs to support DMPs, taking into account what they currently have in place and where improvements may be needed. Please give us your comments in any of the ways detailed on p.5.

Because of the importance of Research Data Management (RDM) in the life sciences, where vast amounts of research data in different complex formats are being produced, this study aimed to assess the state of RDM readiness in the life sciences at Wits to ascertain what support is needed with regards to RDM. In order to achieve the aim, the current RDM practices and needs of researchers, as well as the challenges they face, were investigated. The Jisc Research Data Lifecycle (Jisc, 2021a) was used to guide the literature review, frame data collection, analyse data and advise on some of the main findings and recommendations. A mixed methods approach and an explanatory sequential design were used to achieve the research objectives. For the quantitative phase of research, an online questionnaire was used to collect data. As the total target population (282) was not big, a census was conducted. The questionnaire was administered using SurveyMonkey software. During the qualitative part of the research, semi-structured interviews were used to explain the quantitative results. Five participants were purposively sampled to take part in interviews. The statistical package, MS Excel, was used to analyse quantitative data whilst qualitative data were analysed by thematic analysis. The study showed that life sciences researchers at Wits have adopted many RDM practices, and researchers are increasingly becoming aware of the importance of the openness of data. However, they are dealing with similar RDM issues as their peers worldwide. Results highlighted challenges of, amongst others, the lack of an RDM policy as well as the lack of, or unawareness of, appropriate RDM training and support at Wits. As formal implementation of RDM still needs to take place at Wits, it is recommended that Wits puts an RDM policy in place, followed by suitable RDM infrastructure and awareness making of current services.

Presentation of SU-EOSC Nordic maDMP project at DMP Online Dropin session 2021-10-26. TheSU-EOSC Nordic maDMP project as such is described in more detail in a (still only draft) record and dataset in Dataverse (when published to be accessed throughhttps://doi.org/10.7910/DVN/MGZBAL, as draft accessible only through "private link" https://dataverse.harvard.edu/privateurl.xhtml?token=345aaf2e-4648-4ba3-b93a-7ce3547f9354).&nbsp

This is the presentation,as well as the video recording of the final webinar of a project"Integrating DMPonline with institutional systems at TU Delft" organised on 9 December 2021. The webinar presented the key deliverables of the project and explained some of the lessons learnt. Related resources: The API scripts and documentation on the GitHub repository under GNU GPL-3.0 open source licence are available at: https://github.com/TU-Delft-DCC/ma-dmponline A statistics dashboard can be accessed at: https://dmponline-reports.tudelft.nl/ ---------------------------------------------------------------------------------------------------------------------- The project has been funded by a support grant from SURF (20210203-001-MABO-FRJA) &nbsp

Data management practices for systematic reviews and other types of knowledge syntheses are variable, with some reviews following open science practices and others with poor reporting practices leading to lack of transparency or reproducibility. Reporting standards have improved the level of detail being shared in published reviews, and also encourage more open sharing of data from various stages of the review process. Similar to project planning or completion of an ethics application, systematic review teams should create a data management plan alongside creation of their study protocol. This commentary provides a brief description of a Data Management Plan Template created specifically for systematic reviews. It also describes the companion LibGuide which was created to provide more detailed examples, and to serve as a living document for updates and new guidance. The creation of the template was funded by the Portage Network.

OpenAIRE session atMICCAI 2021, the 24thInternational Conference on Medical Image Computing and Computer Assisted Intervention. Agenda: Welcome - GiuliaMalaguarnera Menti questions - Elli Papadopoulou Introduction to Open Science and OpenAIRE - Elli Papadopoulou Amnesia tool for anonymization - Danae Plan Karidi CONNECT service to build research communities - Alessia Bardi Argos tool to write and publish Data Management Plans (DMPs) - Elli Papadopoulou

This poster was presented Alt+Shift+Archive: Unpacking the past, present and future of digital archive - an online digital archiving symposium between September 20th-28th, 2021. The poster aims to show how data management planning tools like DMPonline can help facilitate a collaborative approach to data acquisition between Archivists and potential data depositors., {"references":["DMPonline https://dmponline.dcc.ac.uk/","Digital Curation Centre https://dcc.ac.uk/"]}

ARDC's Data Management Planning Interest Group hosted a meetup on persistent identifiers and data management planning infrastructure on 17 June 2021. These slides accompanied Siobhann McCafferty's talk on PIDs infrastructure, RAiD and the Instruments for Identifiers Australasia Interest Group (I4IOZ).

Data Management Plans (DMPs) are required increasingly to be submitted alongside ethical approval and funding applications for research projects, requiring researchers to consider what data will be produced as part of their research and how that will be managed and stored going forwards. These are typically managed in separate siloed systems, and stored in unstructured formats (eg. PDFs). Recording a DMP in a structured “machine-actionable” format enables systems to report and act on the planning information held within these documents. In this session we will examine how DMPs can be structured in a machine-actionable way, and explore some of the benefits of managing them in the repository alongside dataset deposit and management features. This will include discussion of the challenges in adapting institutional and funder forms to map to a machine-actionable data model, and the use of the RDA Common Standard for machine-actionable DMPs. The implementation of machine-actionable DMPs in Haplo Repository will be used as a case study. We will look at “quick wins” for attendees looking to implement maDMPs in their institutions, as well as consider some of the possible longer term benefits this approach enables.

The Research Data Aliance and ARDC's Data Management Planning Interest Group co-hosted a webinar on infrastructure and data management plans. Specific tools for managing DMPs, infrastructure that uses DMPs and research infrastructure that is provisioned by DMP infrastructure. Updates from the recent Research Data Alliance Virtual Plenary 17 will also be included. Confirmed speakers ARDC Facilitators Liz Stokes and Kathryn Unsworth Stefanie Kethers, Research Data Alliance Peter Neish, University of Melbourne Rowland Mosbergen, Walter and Elizabeth Hall Institute Maria Praetzellis (John Chodacki), University of California - DMP Tool Andrew Brazzatti, Queensland Cyber Infrastructure Fund - ReDBox Peter Sefton, University of Technology. A video of this presentation can be found on ARDC's YouTube channel:https://youtu.be/9l5D78J4ULo

The poster was presented in the poster session of the 17th Virtual Plenary Meeting of the Research Data Alliance:https://rd-alliance.org/rdas-17th-plenary-meeting-posters-0. The poster analyses Argos (argos.openaire.eu) dynamic model for producing machine actionable Data Management Plans (ma-DMPs) in compliance with the RDA DMP Common Standard (https://github.com/RDA-DMP-Common/RDA-DMP-Common-Standard). It informs about Argos key features to highlight the importance of offering control over individual datasets described in single DMP records, so that diversity in handling data is recognized and addressed for: - the different types of datasets, grouped by their common needs and workflows in the Research Data Management (RDM) lifecycles. - new versus re-used datasets, that require different criteria to be met throughout the RDM steps. - sensitive datasets, that carry information about human or confidential activities. - scientific domains, that introduce disciplinary standards and protocols in RDM activities. Moreover, the poster displays Argos integrations and connections with reference services and data sources. It explains the integration with Zenodo repository which closes the DMP publication lifecycle while correctly exposes DMP outputs according to Open Access best practices and the FAIR principles. It also informs about ongoing integrations centralized to the Open Access Infrastructure for Research in Europe (OpenAIRE) and the European Open Science Cloud (EOSC) to create a two way communication with services, such as PROVIDE (repositories network), MONITOR (custom indicators for funders) and the OpenAIRE Research Graph (https://graph.openaire.eu/) for DMPs contextualisation and further exploitation. Finally, the poster highlights Argos collaborations with funders, research projects and communities, including the RDA, and informs about future work.

Presentation for a focused discussion on DMP integrations organized by KU Leuven for colleagues-subscribersof the JISC RDM emailing list.

Was ist ein Datenmanagementplan? Welche Vorgaben sollte ich beachten? Wie erstelle ich einen solchen für mein Forschungsprojekt und welche nützlichen Tools kann ich hierfür verwenden? Die Anforderungen der Forschungsförderer zum Datenmanagement steigen stetig. Damit verbunden ist häufig auch das Erstellen eines Datenmanagementplans. Dabei erwarten DFG, BMBF oder die EU jeweils unterschiedliche Angaben zur Erhebung, Speicherung und Veröffentlichung von projektbezogenen Forschungsdaten. Zudem bietet das Erstellen eines Datenmanagementplans viele Vorteile und hilft Ihnen nicht zuletzt, die Anforderungen der guten wissenschaftlichen Praxis strukturiert umzusetzen. Was im ersten Moment unübersichtlich und überfordernd wirkt, soll in diesem Kurs anhand einer grundlegenden theoretischen Einführung im ersten und praxisorientierter Beispiele im zweiten Teil der Veranstaltung handhabbar gemacht werden. Sie lernen, was hinter den Anforderungen der Forschungsförderer steckt, welche Elemente ein Datenmanagementplan enthalten sollte und wie sie einen solchen mithilfe interaktiver Tools selbst erstellen können.

Workshop on '(reviewing) data management plans by Esther Plomp for the 'Helis Academy: FAIR Data Stewardship' course on the 17th of March. This includes the short introduction presentation and the google doc that was used for the interactive part of the session.

A training seminar delivered to MPhil Criminology/Criminological Research students at the Institute of Criminology, University of Cambridge on 2nd February 2021. The aim of this seminar was to introduce students to good research data management practices and discuss the application of these practices to criminological research.

This article will use the example of the University of Vienna to show how DMP consulting can succeed and that all parties involved benefit from it. Data Management Plans (DMPs), which are increasingly required by research funders and describe the life cycle of data within a research project, are not only important for the funders, but also for the repository operators and, above all, for the researchers themselves. The funders hope that this will result in the highest possible re-use rate of the data they have paid for, the repository operators know through DMPs what they need to focus their repository on, how much data of what size and complexity should be stored, and for the researchers it is a self-designed guide through the project. They define responsibilities for data protection, backup, etc. and have to think about legal and ethical issues, licensing, data description, necessary technical implementations, archiving and storage options. If the questions are clarified in the DMP's, one also receives an overview of which data can be further used under which conditions. Optimally completed data management plans also make the data fit for further use in a Citizen Science project and possibly for further improvement. Data management plans are therefore useful even where they are not yet mandatory, because they structure the workflow and help to plan the necessary resources. Data management plans, which should be living documents, are also usefully linked to other services such as repositories, DOI allocation, ORCID, etc. In the best case, the DMP also shows that there are still no appropriate solutions for some requirements, for example for the long-term accessibility of databases.

The aphorism quoted in the title by the Swiss political scientist and health economist Dr Gerhard Kocher alludes to making research data available, which has become an indispensable part of research work. Making data available for subsequent use by third parties in turn requires adequate data management, for example with regard to the comprehensibility of the data or with regard to the legal requirements. To support researchers in empirical educational research, the collaborative project Domain Data Protocols for Empirical Educational Research has been developing so-called Domain Data Protocols since June 2019. These are customised, discipline-specific sample protocols that guide researchers in their data management. A central aspect in the development of these protocols is the involvement of various stakeholders in the research community. In order to improve contact with our experts and to keep the interested (international) research community continuously informed about the work and progress of the project, a project website is now being published: www.ddp-bildung.org., Der im Titel zitierte Aphorismus des Schweizer Politologen und Gesundheitsökonoms Dr. Gerhard Kocher spielt auf das Verfügbarmachen von Forschungsdaten an, das inzwischen in der Forschungsarbeit nicht mehr wegzudenken ist. Das Verfügbarmachen von Daten zur Nachnutzung durch Dritte setzt wiederum ein adäquates Datenmanagement voraus, etwa im Hinblick auf die Verständlichkeit der Daten oder in Bezug auf die rechtlichen Voraussetzungen. Zur Unterstützung für Forschende der empirischen Bildungsforschung entwickelt das Verbundprojekt Domain-Data-Protokolle für die empirische Bildungsforschung seit Juni 2019 sogenannte Domain-Data-Protokolle. Dabei handelt es sich um maßgeschneiderte, disziplin-spezifische Musterprotokolle, die Forschende in ihrem Datenmanagement anleitend unterstützen. Ein zentraler Aspekt in der Entwicklung dieser Musterprotokolle ist die Einbeziehung unterschiedlichster Stakeholder der Forschungsgemeinschaft. Um den Kontakt mit unseren Experten*innen zu verbessern und um die interessierte (internationale) Forschungsgemeinschaft kontinuierlich über die Arbeiten und Fortschritte im Projekt zu informieren, wird jetzt eine projekteigene Webseite veröffentlicht: www.ddp-bildung.org., GESIS Blog