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Reference card for researchers on anonymization - in order to engage them with research supporters and privacy specialists in their research institutions to deal with research data about people and risk management in a proper way. Also a Dutch version available through www.lcrdm.nl
This matrix is generic. It is a tool for data stewards or other research supporters to assist researchers in taking appropriate measures for the safe use and protection of data about people in scientific research. It is a template that you can adjust to the context of your own institution, faculty and / or department by taking into consideration your setting’s own policies, guidelines, infrastructure and technical solutions. In this way you can more effectively determine the appropriate technical and organizational measures to protect the data based on the context of the research and the risks associated with the data.
ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform online dashboard monitoring online hate speech. The case under study is the project for the European Observatory of Online Hate (EOOH). Results: We outline the process taken for design and prototype development for which a design thinking approach was followed, including multiple potential user groups of the dashboard. The paper presents this process's outcome and the dashboard's initial use. The identified issues, such as obfuscation of the context or identity of user accounts of social media posts limiting the dashboard's usability while providing a trade-off in privacy protection, may contribute to the discourse on privacy and data protection in (big data) social media analysis for practitioners. Research limitations/implications: The results are from a single case study. Still, they may be relevant for other online hate speech detection and monitoring projects involving big data analysis and human annotation. Practical implications: The study emphasises the need to involve diverse user groups and a multidisciplinary team in developing a dashboard for online hate speech. The context in which potential online hate is disseminated and the network of accounts distributing or interacting with that hate speech seems relevant for analysis by a part of the user groups of the dashboard. International Information Management Association
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A huge amount of data are being generated, collected, analysed and distributed in a fast pace in our daily life. This data growth requires efficient techniques for analysing and processing high volumes of data, for which preserving privacy effectively is a crucial challenge and even a key necessity, considering the recently coming into effect privacy laws (e.g., the EU General Data Protection Regulation-GDPR). Companies and organisations in their real-world applications need scalable and usable privacy preserving techniques to support them in protecting personal data. This research focuses on efficient and usable privacy preserving techniques in data processing. The research will be conducted in different directions: - Exploring state of the art techniques. - Designing and applying experiments on existing tool-sets. - Evaluating the results of the experiments based on the real-life case studies. - Improving the techniques and/or the tool to meet the requirements of the companies. The proposal will provide results for: - Education: like offering courses, lectures, students projects, solutions for privacy preservation challenges within the educational institutes. - Companies: like providing tool evaluation insights based on case studies and giving proposals for enhancing current challenges. - Research centre (i.e., Creating 010): like expanding its expertise on privacy protection technologies and publishing technical reports and papers. This research will be sustained by pursuing following up projects actively.