There is now a whole range of tools to support researchers during each step of the data lifecycle. Data Management Planning tools, for example, facilitate the creation of data management plans either using text modules RDMO Organiser on GitHub RDMO University  Marburg or one is guided through a catalogue of questions. There are usually different templates for different funders and purposes that often provide web-based DMP tools that help you to draft your own suitable DMP [1]. GFBio, for instance, offers a Data Management Plan Tool (GFBio DMP-Tool, DMP Tool, DMP online) that is tailored to create customised DMPs according to DFG guidelines based on the requirements of biodiversity, ecological, and environmental projects. Further, GFBio offers professional support. Thus, your DMP will be cross-checked by experts in the field.

Figure 3. User interface (left) and final DMP (right) of the GFBio DMP Tool.

Furthermore, there are Data Management tools which support data management during the active project phase. Data management tools are software applications or platforms designed to efficiently collect, store, organise, process, and analyse data, but they often have to be set up and hosted by your institution or project partners. Here's a brief explanation of key aspects of data management tools:

Data Collection: Data management tools often provide capabilities to collect data from various sources, including databases, sensors, forms, and external APIs. They streamline the process of gathering information and ensure data is standardised for consistency.

Data Storage: These tools often provide storage solutions, such as databases, data warehouses, or cloud-based storage. Data is typically organised into structured formats for easy retrieval.

Data Organisation: Data management tools allow users to categorise and label data, assign metadata (information about the data), and create data dictionaries to maintain order and accessibility.

Data Processing: Many tools include data transformation and processing features for tasks like cleaning, aggregating, and merging data. This ensures data is accurate and ready for analysis.

Data Analysis: Advanced data management tools often integrate with analytics and visualisation tools, enabling users to derive insights, generate reports, and make data-driven decisions.

Data Security: Security features like encryption, access control, and authentication are critical to protect sensitive data from unauthorised access or breaches.

Data Backup and Recovery: Reliable tools include data backup and recovery mechanisms to prevent data loss due to accidents or system failures.

Data Compliance: Data management tools often assist in compliance with data regulations by providing features for data anonymization, audit trails, and consent management.

Data Collaboration: Some tools offer collaboration features, allowing teams to work together on data-related tasks, share insights, and maintain version control.

Data Governance: Data governance features help organisations establish policies, standards, and procedures for managing data, ensuring data quality, and maintaining data integrity.

Integration: Data management tools often integrate with other software and systems, enhancing their capabilities and enabling data flow between different parts of an organisation.

GFBio provides two different tools for biodiversity data management: Diversity Workbench (DWB) and BExIS2. DWB facilitates efficient data entry, storage, and management for biodiversity research, encompassing various data types. It enforces data standardisation to maintain consistency. BExIS2 specialises in managing large-scale biodiversity data, integrating diverse sources for easier analysis. It emphasises metadata and documentation to provide context for datasets. Both tools can further help you during data collection. In addition, various tools exist which help you collecting and managing your data in the lab as well as in the field such as Smatrix, RightField and Laboratory Information Management Systems (LIMS) or Electronic Lab Notebooks (ELNs) [2][3][4] [5] . Smatrix and RightField aid in data collection and structuring, while LIMS systems provide comprehensive solutions for data organisation and management within laboratory environments. ELNs, on the other hand, offer digital platforms for recording, storing, and sharing experimental findings, streamlining the research process. Together, these tools play a pivotal role in advancing data management capabilities.