4.3 Data Management Policies
At the organizational level, there are good examples of complehensive data management policies such as the one developed and implemented by the Science sector of the Department of Fisheries and Oceans Canada (DFO)1. The main objective of this policy is to ensure the preservation of science data and therefore to ensure long-term use through interoperability, accessibility and standards. DFO's expected results are:
- secure data now and in future,
- interconnected and interoperable data;
- useful data discoverable and accessible through standard means; and
- cost effective data management.
Another example is the International Polar Year (IPY) 2007-2008 data management policy, an international interdisciplinary observation and research program for the advancement of the global knowledge of polar processes. "The overarching objective of IPY 2007-2008 data management is to ensure the security, accessibility and free exchange of relevant data that both support current research and leave a lasting legacy."2
Generally speaking, scientific data management underlying policies include:
- recognizing the value (priceless and irreplaceable) of scientific data and the need to ensure they are well managed to guarantee their conservation and sustainability;
- making sure data are available, accessible, relevant and reliable by managing the entire data life cycle, from acquisition to dissemination;
- implementing structured and secured data repositories to ensure long-term preservation;
- acknowledging that recent data are the most critical for decision making and making sure they are timely and accessible;
- fostering open access while respecting the confidential and/or sensitive nature of data;
- promoting data exchange and sharing with the international scientific community to enhance knowledge.