{"type":"data","nodes":[{"type":"data","data":[{"lab":1,"legalFooterLinks":37},{"identity":2,"contacts":13,"office_hours":30,"web":32,"languages":34,"locale":36},{"name":3,"short_name":4,"description":5,"organisation":6,"organisation_url":7,"organisation_logo":8,"university":9,"university_url":10,"university_logo":11,"established":12},"Human-Centered Intelligent Systems Lab","HCIS Lab","We are shaping the future of automotive technology through intelligent systems that seamlessly integrate human needs with cutting-edge AI innovation.","AImotion Bavaria","https://www.thi.de/forschung/aimotion/","/content/lab/aimotion-bavaria.png","Ingolstadt University of Applied Sciences","https://www.thi.de/","/content/lab/thi.png",2025,{"addresses":14,"emails":21,"phones":24,"primary_type":16,"primary_email":23,"emailsByType":27,"addressesByType":28,"phonesByType":29},[15],{"type":16,"title":9,"street":17,"city":18,"postal_code":19,"country":20},"office","Esplanade 10","Ingolstadt","85049","Germany",[22],{"type":16,"email":23},"hcis@thi.de",[25],{"type":16,"number":26},"+49 841 9348 0",{"office":23},{"office":15},{"office":26},{"days":31,"timezone":-1},{},{"social":33},{},["Set",35,36],"DE","EN",[38,42,47],{"slug":39,"name":40,"label":40,"href":41},"datenschutzerklaerung","Datenschutzerklärung","/legal/privacy/datenschutzerklaerung",{"slug":43,"name":44,"label":45,"href":46},"barrierefreiheitserklaerung","Erklärung zur Barrierefreiheit","Barrierefreiheit","/legal/accessibility/barrierefreiheitserklaerung",{"slug":48,"name":49,"label":49,"href":50},"impressum","Impressum","/legal/impressum"],"uses":{}},{"type":"data","data":[{"meta":1,"summary":7,"sections":11},{"slug":2,"title":3,"description":4,"updatedAt":5,"isPublished":6},"data-handling-principles","Data Handling Principles","How research and study data is collected, stored, secured, and retained within HCIS projects.","2025-11-15",true,{"id":8,"title":9,"content":10},"summary","Summary","\u003Cp>These principles describe how HCIS projects handle research data – from collection and storage to sharing and deletion. They are designed to balance scientific value with strong privacy and security requirements.\u003C/p>\n",[12,17,22,27,32],{"id":13,"title":14,"number":15,"content":16},"data-collection","Data Collection",1,"\n\u003Cp>When collecting data, HCIS aims to:\u003C/p>\n\u003Cul>\n\u003Cli>Limit collection to what is necessary to answer the research question\u003C/li>\n\u003Cli>Avoid collecting identifiers unless required for the study design\u003C/li>\n\u003Cli>Clearly distinguish between anonymous, pseudonymous, and directly identifiable data\u003C/li>\n\u003C/ul>\n\u003Cp>Examples include survey responses, interaction logs, or sensor data recorded during driving simulations.\u003C/p>\n",{"id":18,"title":19,"number":20,"content":21},"data-storage-and-security","Data Storage and Security",2,"\n\u003Cp>Research data is stored using secure, access-controlled systems. Typical measures are:\u003C/p>\n\u003Cul>\n\u003Cli>Use of THI-managed infrastructure or approved external systems\u003C/li>\n\u003Cli>Role-based access control for project members\u003C/li>\n\u003Cli>Encryption in transit and, where appropriate, at rest\u003C/li>\n\u003C/ul>\n\u003Cp>Access is granted only to team members who need the data to work on the project.\u003C/p>\n",{"id":23,"title":24,"number":25,"content":26},"pseudonymization-and-anonymization","Pseudonymization and Anonymization",3,"\n\u003Cp>Whenever possible, data is:\u003C/p>\n\u003Cul>\n\u003Cli>Pseudonymized (replacing direct identifiers with codes)\u003C/li>\n\u003Cli>De-identified before analysis, especially for sharing within larger teams\u003C/li>\n\u003C/ul>\n\u003Cp>The key that links pseudonyms to real identities is stored separately and with additional protection, if it needs to exist at all.\u003C/p>\n",{"id":28,"title":29,"number":30,"content":31},"data-retention-and-deletion","Data Retention and Deletion",4,"\n\u003Cp>Retention periods depend on:\u003C/p>\n\u003Cul>\n\u003Cli>The requirements of the research project\u003C/li>\n\u003Cli>Legal or contractual obligations (e.g., funding conditions)\u003C/li>\n\u003Cli>Reusability for follow-up studies where participants have consented\u003C/li>\n\u003C/ul>\n\u003Cp>After the retention period, data is securely deleted or anonymized in such a way that re-identification is no longer reasonably possible.\u003C/p>\n",{"id":33,"title":34,"number":35,"content":36},"data-sharing-and-reuse","Data Sharing and Reuse",5,"\n\u003Cp>Data may be shared in anonymized or aggregated form:\u003C/p>\n\u003Cul>\n\u003Cli>Within the HCIS lab or the broader THI research community\u003C/li>\n\u003Cli>With external collaborators under appropriate agreements\u003C/li>\n\u003Cli>Publicly, as open data, if the consent and risk assessment permit it\u003C/li>\n\u003C/ul>\n\u003Cp>Any data sharing complies with data protection law and the promises made to participants in the consent documents.\u003C/p>"],"uses":{"params":["slug"]}}]}