As Local Digital Twin (LDT) technology becomes increasingly complex and integrated with disruptive technologies, like Artificial Intelligence (AI) and Machine Learning (ML), new ethical, legal and transparency challenges arise. Particular concerns centre around personal information protection, data usage, and the ethics of algorithmic decision-making. This paper explores these challenges, including both personal and non-personal data governance, future regulatory impact, and the implications of new and proposed legislation, including e-privacy, the Digital Markets Act, and the AI Act. Drawing on the perspectives of various scholars, as well as European digital twin projects, this paper emphasises the importance of human intelligence in balancing the impacts of AI and ML, the need for societal assessment frameworks to integrate broader social elements, and the necessity of transparency in decision-making processes. It proposes strategies for the responsible and ethical implementation of LDTs, emphasising risk mitigation measures, such as using trusted data processors, ensuring data transparency, and adopting robust data governance frameworks to protect fundamental rights and freedoms. This paper also aims to contribute to the ongoing discourse by highlighting legal frameworks, underlining ethical aspects, and facilitating the practical application of ethics and relevant legislation through gap analysis methodologies. Alternative ways to manage LDT data and information are also presented, reflecting the key role of data and information management in this domain.