Data disclosure and data sharing also raises a host of ethical issues. For one, if a researcher has access to proprietary information, the researcher might have a duty not to reveal that information to other individuals unless they are entitled to have access to it. Further, privacy and confidentiality concerns can emerge if data from research with human beings is shared without consulting relevant ethical and legal guidelines (see your insitution's Human Subject Policies). Additional issues surround the excluding data from a manuscript submitted for publication, modification of images, etc. [Note: Information quoted from Georgia Tech's Data Management site.]
Everyone with a role in research has a responsibility to ensure the integrity of the data. Failure to do so has serious implications on the ethics of researchers. Resources for Research Ethics Education provides the foundation for promoting awareness and understanding of the highest standards of responsible conduct of research.
Information courtesy Georgia Tech's Data Management site
Data ownership is a key issue pertaining to research, because of the research opportunities that may emerge from the data, the potential commercial applications that might stem from the data, funder requirements regarding the sharing of data and institutional requirements.
Do I Own The Data I've Collected?
Open Data Commons is the home of a 'set' of legal tools to help you provide and use open data via licensing.
How Do I Tell Others How They Should Use My Data?
Best practices in the Web environment include making data available along with a license that clearly sets out the terms under which the data is being made available. Without such a license, users can never be sure of their rights to use the data, which can impede innovation.
What's copyrightable? (recommendations from Dorthea Salo) Generally:
Usually patentable stuff like genetically-modified organisms, gizmo/gadget descriptions, etc.
Worry less about raw observational data off instruments in numeric form -- really anything you might stick in an Excel spreadsheet or an Access database.
Currently there is no universal method for citing data. Some data sets that are found via data aggregators often have a suggested citation within the record. Best practice is to cite the material in such a way that others can find the data themselves. For example, include the author(s), title, year and distributor of the data (only the title is required, but authors and year are strongly recommended).