IAI Institute on Information Management: free and open access to, and use of data and information



The IAI has supported a wide range of multinational and multidisciplinary research and capacity building activities to contribute to the understanding of global change processes and to use this understanding in the adaptation to and mitigation of global change impacts. The free and open exchange of information is an important part of the IAI’s mandate. This involves a number of conditions and processes: the scientific data and information must be of reliably high quality; the information must be accessible across disciplines, institutions and countries; it must be in formats that facilitate access, analysis and meta-analysis; it must be accompanied by tools that facilitate the generation of knowledge, communication and visualization from data and information; and it must be governed by secure and reliable protocols of storage, access, use and distribution.

The first institute on data and information management was held by The Water Center for the Humid Tropics of Latin America and the Caribbean (CATHALAC). For IAI it is urgent to support research project teams in issues relevant to information management and data exchange. One aim of the institute was to expand international and interdisciplinary scientific interactions through improved information management. This activity was funded by the US National Science Foundation (NSF).


The principal goals of the institute were:
1) to provide recommendations to help IAI develop its data and information policy as part of its IAI strategic planning;
2) to encourage IAI supported projects (CRN II, SGP-HD) to make data available and expand international and interdisciplinary scientific interactions through improved information management.

Besides these goals, the institute aimed to
promote discussion on institutional and policy aspects of information sharing, management and access;
foster scientific and technical discussions on information analysis and meta-analysis to inform decision makers and policy;
identify opportunities and constraints for open access, data storage and preservation of data, as well as share information, access practices and policies;
show existing data consortia and identify how they are dealing with this matter and who are their target audience and users; and
identify mechanisms to synthesize data for policy through a meta analysis process.


Institute Report

Working Group: Alberto Piola (Chair), Alicia Aleman; Beatriz Torres; Carlos Martínez; Christopher Scott (Rapporteur); Fabien Quétier; Giri Palanisamy; Luis Marcelo Achite; Luiz Horta; Paul Filmer; Puneet Kishor; Rômulo Menezes; Vanderlei Canhos


The ultimate objective for the IAI data and information system (DIS) is to make data and information available and accessible to various audiences. These audiences vary from scientists to policy-makers to the general public.

In making data available to these audiences, the guiding principle is that the system is designed for the good of society in general and more specifically for the good of science. The system must also account for requirements arising from intellectual property rights in several areas: the rights of donors, grantees, investigators and publishers.

General recommendations

IAI projects represented at this training workshop will need to consult with the full group of PIs and collaborators on many of these policy issues.
IAI Directorate needs to act on this list of recommendations for decision by PIs, Strategic Planning Group, Scientific Advisory Committee, and Executive Council.
IAI should make official the relationship with the Oak Ridge National Laboratory (ORNL) in order to be fully integrated in the Mercury Consortium and have the DIS system updated on a regular basis.

Thematic recommendations from working groups

Translating scientific knowledge to support decision making

Recommendation: The IAI staff, in consultation with its research constituents and stakeholders, should develop a comprehensive strategic plan for influencing policy makers and supporting decision makers (e.g., the white paper mentioned below) consistent with its organizational mission and capabilities.
Fact: Integrating socioeconomic data and information with environmental data is likely to make the information more interesting, relevant, and useful, especially to policy makers.

Recommendation: Both the IAI collectively and each IAI-funded project should identify potential users among decision makers and policy makers, and then prioritize communications with them and monitor the outcomes.
Fact: The IAI at the project and staff levels, however, does not have all the expertise or resources needed to pursue the objective of interacting with and influencing policy and decision makers.

Recommendation: IAI should establish partnerships with organizations and individuals that have the expertise, activities, and resources focused on translating scientific knowledge to support decision making and policy action.
Fact: Data visualization is just one way of using data to support decision-making and influence policy makers.

Recommendation: There needs to be a strong effort to link IAI-funded projects to decision and policy makers in order to establish ongoing channels of communication to get science results to support decision making.

Global data policy

Fact: Free and open access is not “exchange” in negotiated terms. Mercury will distribute the metadata to GCMD, Google, GEO One Stop, etc.
Recommendation: The IAI Directorate needs to allocate additional resources for DIS stewardship, maintenance, checking keyword hits, visualization tools, developing the interface with the DIS Working Group, etc.

Opportunities, impediments, and availability of data in developing countries

Recommendation: Write a white paper based on the lines of this report for decision-makers at the country level. The paper should address data management and policy, representing a wider vision, and indicating lines of action adapted to local, country and regional conditions. Issues that need to be addressed include but may not be limited to:

* Evaluation of potential economic impacts of open data policies (documenting successful examples).
* Specific workshops/meetings with policy makers to support open access.
* Identify opportunities for partnerships among projects and institutions to strengthen open access.

Integration of socio-economic and physical data in a geographic context

Recommendation: Form an IAI DIS Working Group composed of data and data policy experts, IAI investigators, data managers, active data users, metadata standards specialists, the IAI DIS manager and the IAI Director, with a total of 8 to 12 participants. The responsibilities of this working group are:
* Improve integration and data discovery.
* Improve data management and interconnectivity.
* Start data sharing within and among IAI-funded projects as a first step to universal public metadata access via the DIS.
* Implement metadata result display and visualization tools (with ORNL Mercury).
* Explore interdisciplinary thesaurus.
* Document best-practices at IAI level for data and metadata sharing.
* Implement multi-lingual training (including needs identification) and documents, although metadata will remain exclusively in English.
* Suggest directions and actions for the DIS.
* Consider data policy criteria and check what can be applied to the IAI.

Recommendation: Spatio-temporal data should be organized in a spatial referencing framework, with exceptions for socio-economic data that may not be spatial in nature.

Recommendation: the IAI should continue using FGDC (Federal Geographic Data Committee) metadata standards.

Recommendation: Identify metadata standards for qualitative data.

Fact: Need utilities to map metadata across different standards.

Recommendation: the IAI must evaluate whether the IAI DIS manager has time to coordinate these activities across all funded projects.

Intellectual Property

Recommendation: Projects that produce an integrated database should be encouraged to upload on the IAI DIS both the entire database (preferably in non-proprietary format) and the component data, preserving third party rights.

Facts: Scientific products from IAI-funded projects could benefit from Creative Commons licensing.

Fact: The PIs may not own the rights to products, for example, giving the IAI a pdf of a paper could be an infringement of copyright law where no “fair use” clauses apply.

User’s Manual for IAI Science

Recommendation: The IAI in conjunction with the grantee needs to be more explicit in defining the “information”, “work”, “data”, and “product” (see preliminary list of definitions in the appendix, below) that must be made available to constitute contractual compliance.

Recommendation: For each project’s annual report to be approved, data and products (including publications) listed must have metadata uploaded and searchable on the IAI DIS even if the data and products are not yet available.

Fact: PI has responsibility to ensure data are made available at the end of the project, including negotiating with partners not funded by IAI.

Recommendation: IAI and PIs must agree on where data will be stored and when.

Recommendation: IAI will assess the quality and reliability of data repositories, and suggest a list of alternatives to project PIs (including ORNL DAAC and CIESIN). LBA has kindly offered to serve as a temporary repository until a final determination is made.

Recommendation: PIs must include relevant links to metadata and/or data in the policy and practice briefs produced as part of the IAI’s overall communications strategy.

Appendix – Definitions

Note: The following may not be 100% legally accurate; after all, I am not a lawyer. They are my understanding of the terms. Please read a more detailed description, but, consult your lawyer to really be on the safe side.

Data: At its raw-est, data straight out of instruments, or raw data as collected via surveys and questionnaires. It is difficult to always correctly distinguish between raw data and processed data, and what is processed data for one may be raw data for someone else. As such, decision on what is raw data has to be made on a case-by-case basis by the researcher.

Metadata: Literally, data about data, metadata allows a potential user of data to learn more about the data before using it. At its most minimal, metadata would include information on where, how, by whom, in what format, and for what reason were the data collected, and information on if the data are available, under what kind of terms and conditions of use, and how to get them.

Information: Processed data implying some level of usefulness. The processing can be minimal and routine to complicated and proprietary. Information almost always has copyright restrictions attached to it. Information at one level can be data at another level. Distinction between information and data has to be made on a case-by-case basis (see “Data” above).

License: A license specifies the terms and conditions under which something can be used. A license does not require any reciprocal action on the part of the licensee.

Contract: A contract is like a license, but involves a reciprocal action required on the part of the user.

Protocol: A protocol is a suggestion for a way of doing things. It is not legally binding, but is usually adopted and propagated through norms. For example, the protocol in science is to always credit the source. The social penalties for not crediting are usually enough deterrent.