Best practices for sharing sensitive environmental geospatial data
Authors:   AMEC Earth & Environmental
Published: November 2017

With the advances in geomatics technologies (i.e. applications, data storage capacities and communication bandwidth), the extensive efforts expended in collecting geospatial data (field surveys, monitoring systems, imagery) and the pervasiveness of the Internet,
geomatics users expect easy access to an unprecedented variety of geospatial datasets. This expectation is mirrored in the basic principles of most government data management organizations which encourage the sharing of data for the greater societal good.
However, while access to data is increasing, there is also a growing recognition of the extent to which barriers exist in sharing or accessing of sensitive geospatial data. A 2006 Environics survey not only identified the barriers in sharing data (privacy and confidentiality issues, licensing and
ownership issues, and liability issues and broader data sensitivities) but found that removing such barriers to sharing data were felt to be the most important data issue to mitigate. In a 2006 workshop facilitated by GeoConnections, communities engaged in land management, environmental impact
assessments and sustainable development (collectively referred to as the Environmental and Sustainable Development (E&amp;SD) communities) identified several data sharing issues including the need to develop data-sharing agreements, facilitate open access, conduct further investigations and
provide guidance on how to share data of a sensitive nature.
To respond to these needs, GeoConnections contracted AMEC Earth and Environmental to conduct research and stakeholder consultation in supported of the development these Best Practices.
The purpose of these Best Practices is to educate Data Contributors, Owners, Custodians, Stewards and Consumers of the issues and concepts associated with protecting, sharing and utilizing sensitive geospatial data, with a focus on supporting programs, services, businesses and / or applications
related to the Environment and Sustainable Development (E&amp;SD) community. The intention is to provide practical guidance to those interested in developing their own sensitive environmental geospatial data sharing policies and protocols.
In reviewing the literature, surveying organizations and practitioners, and through consultation by workshops, it was determined that perspectives range widely on what might be considered sensitive environmental geospatial data. It was also found that there is no consistent mechanism for assessing
whether a dataset should be classified as sensitive or not. What was revealed was that the concept of sensitivity changes with context (time and recent events), an organization's regulatory environment (legislation, policy, competition, etc.), jurisdictions and the personal views of Data
Contributors/Owners/Custodians and in actuality, there is considerable intertwining of these elements. Anyone who is assessing a dataset to determine whether it should be considered sensitive or not should be aware of these elements and the potential impact on the credibility of their organization
if sensitive data is mistreated.
The first significant question to be answered is mp;lt;"What is sensitive geospatial data?mp;gt;" and how is it determined to be sensitive or not. What defines data as sensitive is related to legislation, regulations and policies governing an organization as well as standards adopted by the
organization.
With the focus on the E&amp;SD community, the emphasis is on sensitive mp;lt;"environmentalmp;gt;" geospatial data as a subcategory of sensitive geospatial data. The Guidelines consider environmental geospatial data to be thematic geospatial data that could be used for analysis in areas such as
environmental impact assessments, land use planning, land management, sustainable development, resource management, airshed management, etc.
Due to the diversity of what can make a dataset sensitive, these Guidelines propose a categorization of sensitivity to assist an assessor (typically the Data Custodian) in understanding which aspect of sensitivity may apply to the dataset they are reviewing. In addition, each organization has to
establish and publish its own criteria that allow the assessor to determine whether the dataset being reviewed is sensitive and justify why or why not. These criteria have to be established on an organization by organization basis due to the diversity of the data organizations handle and the
specifics of the regulatory environment under which each operates.
It is prudent that each organization develops these criteria independent of any specific dataset, establish them in advance of any dataset assessment, document the criteria and have it vetted by an authorized organizational representative (legal or policy). This step is critical in establishing not
only the process but provides a documented baseline for justifying the classifying of a dataset as sensitive if challenged at a later date.
Understanding these categories will also assist in defining the metrics for establishing what is to be considered sensitive data. Data can generally be categorized as sensitive geospatial data if it meets any of the following criteria:
1. Legislation/Policies/Permits - the data is identified by legislation as requiring safeguarding. The most prominent legislation in this regard is the federal Privacy Act - safeguarding the data is required if an individual can be identified, either directly by georeferenced information (such as
the geo-coordinates of an address) or indirectly through the amalgamation of geospatial data and related attributes;
2. Confidentiality - the data is considered confidential by an organization or its use can be economically detrimental to a commercial interest;
3. Natural Resource Protection - the use of the information can result in the degradation of an environmentally significant site or resource;
4. Cultural Protection - the use of the information can result in the degradation of an culturally significant site or resource; or
5. Safety and Security - the information can be used to endanger public health and safety.
Numerous articles have identified the need for organizations to establish frameworks for identifying and sharing sensitive data. This need is driven by:
The requirement to support open government by making data readily accessible unless there is a legitimate and documented reason not to;
Be consistent within an organization and across jurisdictions so that the mechanisms required to share the data are also applied consistently; and
Document criteria and processes so that users can search out that the data exists, be made aware of any decisions relating to the safeguarding of the data and know who to contact to request access to safeguarded data.
The Best Practices identify basic principles that can be applied to assessing sensitive environmental geospatial datasets in order to classify sensitivity consistently:
1. Unless the dataset is classified as sensitive it can be provided free of restrictions;
2. Information can not be considered sensitive if it is readily available through other sources or if it is not unique;
3. The Data Custodian of the information is the only agency that can determine whether an environmental geospatial dataset is to be classified as sensitive;
4. Data Consumers of sensitive environmental geospatial datasets must honour the restrictions accompanying the information in the form of an agreement, license and/or metadata; and
5. Organizations should document and openly publish their process, criteria and decisions.
These Best Practices also present an example decision framework for assessing whether an environmental geospatial dataset is to be classified as sensitive. This framework has been adapted from the US Federal Geographic Data Committee (FGDC) document Guidelines for Providing Appropriate Access to
Geospatial Data in Response to Security Concerns. As the FGDC guidelines are primarily concerned with Security and Public Safety, this framework has been modified to accommodate sensitive environmental geospatial data.
Once a dataset is defined as sensitive and the organization's regulatory environment is understood then the appropriate mechanisms for sharing become apparent. In most cases instruments such as agreements or licenses are sufficient, in other cases the sensitivity must be removed from the dataset
before it is shared and in other cases approval is given to a Data Consumer on a case by case basis. Regardless of the mechanism put in place, it essentially comes down to the Data Custodian trusting that the data will be adequately safeguarded by the Data Consumer and the mechanisms they have in
place sufficiently limit the risk of inappropriate treatment of the data. Furthermore, there are numerous examples of data collection programs where Data Contributors contribute sensitive data content on a regular basis to the Data Custodian and the Data Contributors trust that their contributions
are adequately safeguarded otherwise future contributions may be terminated.
At its core, the successful long term sharing of sensitive environmental geospatial information is about trust, risk management, the credibility of the participating organizations and their overriding desire to disseminate information.
Successful sharing of sensitive geospatial information lies within the mechanisms used to: present the underlying knowledge yet remove the sensitivity; the instrument that defines the conditions of use and protection; and, training of participants to ensure that they are cognizant of their roles and
responsibilities. Those sharing or accessing geospatial data may use a combination of mechanisms to ensure data is shared and used responsibly and that the credibility of the process is maintained.
It is intended that these Best Practices provide the reader with sufficient insight and links to resources in order to assist them in implementing a consistent and documented approach to managing and sharing sensitive environmental geospatial data within their organization. The document is intended
as a living document, and may be updated as related practices mature and the user-community needs evolve.