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SUMMARY:GESIS Summer School in Survey Methodology
DESCRIPTION:If you are interested in survey design and implementation\, you may explore factorial survey design\, advanced questionnaire design\, or advanced survey design. You can also learn about bots used in web studies and discover AI tools that support different stages of the survey research process. For those interested in data analysis techniques\, we offer courses on causal inference\, latent variable modeling\, and data science techniques for analyzing both survey and big data. Finally\, you can also learn about survey sampling and weighting.  \n\n\n\nIn addition to our one-week courses\, we offer two- to three-day short courses. This year\, you can discover methods for pretesting survey questions as well as for aggregating evidence over multiple studies\, and you can enhance your knowledge of how to use DAGs for causal inference. If you are looking to expand your software skills\, you can choose between our courses on introduction to Stata or R.  \n\n\n\nOur Summer School offers a unique opportunity to learn from leading experts in the field\, and to network with peers who share your interests. Join us for a stimulating and engaging experience that will take your skills and knowledge to the next level.  \n\n\n\nSince 2012\, we have been organizing Europe’s leading Summer School covering survey methodology\, research design\, and data collection and analysis. Initially held exclusively at GESIS in Cologne\, Germany\, we expanded to online options in 2020. This setup brings together lecturers and participants from all over the world and many different fields\, fostering a collaborative\, global learning environment. \n\n\n\nReasons to attend \n\n\n\nAs a graduate or PhD student\, post-doc\, junior or senior researcher\, or survey professional\, you will: \n\n\n\n\nreceive high quality training in state-of-the-art techniques and methods of survey research.\n\n\n\nobtain a comprehensive overview of different survey methods or delve deeply into niche topics of interest to you.\n\n\n\nacquire essential skills in how to design\, plan\, conduct\, and document all kinds of surveys.\n\n\n\ngain insights into survey data collection processes.\n\n\n\nlearn techniques for analyzing survey data and assessing data quality.\n\n\n\nnetwork with peers from different fields and from all over the world to discuss research and share ideas.\n\n\n\n\nWe are happy to assist you!\n\n\n\nShould you be unsure which course is the right one for you\, please do not hesitate to contact us. \n\n\n\nPrerequisites\n\n\n\nEach course has specific prerequisites\, which will be detailed on the course webpages. \n\n\n\nIn addition\, you are expected to: \n\n\n\nhave a good command of English. \n\n\n\nhave a basic knowledge of empirical research methods.
URL:https://www.crossda.hr/event/gesis-summer-school-in-survey-methodology-2/
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DTSTART;TZID=Europe/Zagreb:20260819T140000
DTEND;TZID=Europe/Zagreb:20260819T150000
DTSTAMP:20260818T073658Z
CREATED:20260818T071954Z
LAST-MODIFIED:20260818T073658Z
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SUMMARY:Get to know CESSDA with Alen and Irena! DRI Webinar series
DESCRIPTION:Summary \n\n\n\nStarting in February 2026\, DCC launched a series of webinars to showcase the digital research infrastructure projects and communities in the UK and beyond in collaboration with UK Research and Innovation (UKRI). Tune in to learn more about CESSDA from two of the people who the organisation best: CESSDA Head of IT Alen Vodopijevec and Vipavc Brvar (Slovenian Social Science Data Archives (ADP)). \n\n\n\n\n\n\n\nDescription\n\n\n\nResearch support professionals increasingly need to guide researchers through a complex landscape of research data management (RDM) services\, repositories\, standards\, and digital research infrastructures (DRIs). This webinar introduces CESSDA ERIC as a key European research infrastructure for the social sciences and demonstrates how its services\, tools\, training resources\, and community initiatives can support researchers throughout the entire research data lifecycle. CESSDA provides training resources such as the Data Management Expert Guide (DMEG) and Data Archiving Guide (DAG)\, as well as services that enable data discovery\, reuse\, citation\, and long-term preservation. \n\n\n\nParticipants will learn how researchers can discover data through the CESSDA Data Catalogue\, use multilingual controlled vocabularies such as ELSST\, and benefit from community-driven developments in metadata standards\, repository technologies\, and trustworthy digital repositories. By the end of the webinar\, attendees will be better equipped to signpost researchers towards appropriate European research data services and infrastructures that enhance data management\, sharing\, discoverability\, and reuse. \n\n\n\nAbout the speakers\n\n\n\nIrena Vipavc Brvar is a senior research data specialist and Director of Administration at the Slovenian Social Science Data Archives (ADP)\, University of Ljubljana. She has over twenty years’ experience in research data management\, digital preservation\, and Open Science. She’s actively involved in CESSDA\, contributing to training activities\, guidance development\, and capacity-building programmes for researchers\, data stewards\, librarians\, and research support professionals with expertise in FAIR data\, metadata standards\, data citation\, and repository certification. She’s a member of the OPERAS Scientific Advisory Committee and co-chair of RDA Node Slovenia. \n\n\n\nAlen Vodopijevec is Head of IT at CESSDA ERIC\, based at the CESSDA Main Office in Bergen\, Norway\, where he’s responsible for CESSDA’s technical roadmap and strategy\, IT processes\, and service management across the CESSDA Main Office and its national Service Providers. Before joining CESSDA in 2024\, he spent two decades at the Ruđer Bošković Institute in Zagreb\, working on national research infrastructure and repository initiatives and helping establish the Croatian Social Science Data Archive (CROSSDA). His expertise spans interoperability\, research data management\, and Open Science infrastructure. \n\n\n\nVisit website
URL:https://www.crossda.hr/event/get-to-know-cessda-with-alen-and-irena-dri-webinar-series/
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DTSTART;TZID=Europe/Zagreb:20260831T080000
DTEND;TZID=Europe/Zagreb:20260929T173000
DTSTAMP:20260818T072905Z
CREATED:20260818T072153Z
LAST-MODIFIED:20260818T072905Z
UID:3222-1788163200-1790703000@www.crossda.hr
SUMMARY:GESIS Fall Seminar in Computational Social Science
DESCRIPTION:Summary \n\n\n\nThe GESIS Fall Seminar in Computational Social Science features introductory and advanced courses on collecting and analyzing digital behavioral data from the web\, social media\, or digital archives. Courses are taught by leading experts in the field and offer plenty of opportunities to learn from and connect with other like-minded researchers. Lectures in each course are complemented by hands-on exercises\, giving you the opportunity to directly implement your newly acquired skills and knowledge. \n\n\n\n\n\n\n\nDescription\n\n\n\nIf you are new to computational social science\, you may want to get an overview of debates and methods in the field in one of our blended learning introductions to computational social science with R or Python. If you plan to collect your own textual or visual data from the web\, have a look at web data collection with R or Python\, or learn how to collect data with smartphones and analyze the resulting data with intensive longitudinal methods. For those interested in data analysis\, we offer courses on machine learning for text analysis for beginners\, cutting-edge text analysis methods\, computer vision\, causal machine learning\, and agent-based modeling. \n\n\n\nWe are happy to assist you!\n\n\n\nShould you be unsure which course is the right one for you\, please do not hesitate to contact us. \n\n\n\nFor those without prior experience in R or Python and those who would like a refresher\, we additionally offer two introductory online pre-courses for R and Python in the week before the start of the Fall Seminar – join those for optimal preparation!  \n\n\n\nAll courses in the GESIS Fall Seminar are stand-alone and can be booked separately – feel free to mix and match courses to build your own personal Fall Seminar experience! Contact us if we can assist with tailored recommendations for possible course combinations or if you have any other questions. Learn more about our course fees and ECTS credits on our website. \n\n\n\nCourse overview\n\n\n\nWeek 1 (31 August-04 September) \n\n\n\nIntroduction to Computational Social Science with R (blended learning online course) \n\n\n\nIntroduction to Computational Social Science with Python (blended learning online course) \n\n\n\nWeek 2 (07-11 September) \n\n\n\nWeb Data Collection with R (live online course) \n\n\n\nWeb Data Collection with Python (live online course) \n\n\n\nWeek 3 (14-18 September) \n\n\n\nIntroduction to Machine Learning for Text Analysis with Python (in-person course) \n\n\n\nAgent-Based Modeling & Simulation (in-person course) \n\n\n\nComputer Vision for Image and Video Data Analysis with Python (live online course) \n\n\n\nWeek 4/5 (21-29 September) \n\n\n\nFrom Embeddings to LLMs: Advanced Text Analysis with Python (in-person course) \n\n\n\nMobile Data Collection and Analysis: Intensive Longitudinal Methods (in-person course) \n\n\n\nCausal Machine Learning (live online course) \n\n\n\n \n\n\n\nVisit website
URL:https://www.crossda.hr/event/gesis-fall-seminar-in-computational-social-science/
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