| Data Management |
The development of a SDI may be based on a spatial information management framework. Such framework is in use for example in the state of Victoria, Australia, where it aims to provide a consistent approach to the management of spatial information by data custodians (Victorian Spatial Council, 2013) (see section 4.1.4). A spatial information management framework establishes a core set of best practices: requirements, standards and policies, for managing spatial information. The underlying principles are that the information managed within the spatial information management framework will: Represent the definitive and authoritative source of the data it contains; Be managed by designated custodians; Be accessible and available to all members of the community, except where confidentiality and sensitivity restrictions apply; and Have the potential to be combined with other spatial information products for analysis and decision making purposes. A spatial information management framework should address four main elements (Victorian Spatial Council, 2010): Institutional arrangements for developing spatial information: governance, custodianship. Requirements for creating and maintaining spatial data: framework and business data, data quality. Mechanisms for making spatial data accessible and available: metadata, awareness, access, pricing and licensing, and privacy. Strategic development of technology and applications. Good practices: A good practice regarding data quality and risk management is to follow the Complete Cycle of Geospatial Data Quality for a Spatially-Enabled Society (GeoConnections and Intelli3 Inc., 2015) which suggests evaluating data quality using ISO 19157, managing risks of inappropriate data usage using ISO 31000, and communicating properly with all players, especially non-expert users using ISO 3864-2 (International Organization for Standardization, 2004). A good practice regarding data is to apply master data management principles (The Master Data Management Institute, 2015), for the SDI but also at the source (e.g., the national mapping agencies feeding data to the SDI). Another good practice is to evaluate the data being fed to the SDI using data maturity models (e.g., Data Management Maturity Model (CMMI Institute, 2016) or the Open Data Maturity Model (The Open Data Institute, 2016). |
| Data Policy |
A good practice is to develop a profile of the ISO standard for example the North American Profile of ISO 19115:2003 Geographic information – Metadata (NAP – Metadata) (National Standards of Canada, 2003), developed jointly by Canada and the US. Another example is the INSPIRE profile of ISO 19115 (Metadata Implementing Rules: Technical Guidelines based on EN ISO 19115 and EN ISO 19119) developed by the Drafting Team Metadata and European Joint Research Centre (INSPIRE, 2013). Metadata is useful during the whole data lifecycle: Creation of the dataset; For maintenance; For distribution; and For use; The use of appropriate metadata (e.g., the core of ISO 19115 or as specified in a metadata profile) should be a prerequisite for the distribution of data through the Arctic SDI. For managing metadata, it is a good practice to use a dedicated metadata management tool (e.g., GeoNetwork (Open Source Geospatial Foundation, 2015)). “A data specification contains the data model and other relevant provisions concerning the data, such as rules for data capture, encoding, and delivery, as well as data quality requirements, metadata for evaluation and use, data consistency, etc. Data modelling and data specifications are linked, in the first place, to data collection and data product delivery. Since an SDI is usually composed of many data themes where cross-theme interoperability may be required, a robust framework should be established that drives the development process of the data component in a coherent way. In the European Union, INSPIRE has adopted a conceptual framework that consists of two main sections: The Generic Conceptual Model (GCM) defines 25 aspects or elements relevant to achieving data interoperability in an SDI, and proposes methods and tools to address them. These include, for example, registries, coordinate reference systems, identifier management, metadata and maintenance, to name just a few. The description of the methodology for developing data specifications for interoperability includes a detailed discussion of the relevant actors, steps and the overall workflow from collecting user requirements to documenting and testing the specifications that emerge from this process.” (European Commission, Joint Research Centre, 2012). To achieve interoperability between systems and system components, a SDI must follow international standards of the OGC, ISO, W3C and domain-specific thesauri or ontologies. Interoperability can be addressed at various levels: Technical interoperability: deals with purely technical aspects of interoperability such as transmission protocols, and data exchange formats, standard interface specifications, data transport. Semantic interoperability: means that applications can interpret data consistently in the same manner in order to provide the intended representation of the data. Geosemantic interoperability: ability of systems using spatial data and services to cooperate (inter-operate) at the semantic and geometric levels (e.g., definitions of shapes, criteria to define boundaries and position). Organisational interoperability: “coordinated processes in which different organisations achieve a previously agreed and mutually beneficial goal” (Interoperability Solutions for European Public Administrations, 2010). Legal interoperability: the legal rights, terms, and conditions of data from two or more sources are compatible and the data may be combined by any user without compromising the legal rights of any of the data sources used. In a vision of optimal collaboration between the Arctic Council and its groups, national mapping agencies of the Arctic countries and other data providers, the Arctic SDI should focus on technical interoperability first in order to allow for the discovery of, and access to, relevant datasets that exist elsewhere (e.g., other SDIs) (concept of “inward” interoperability, i.e. discover sources and access them through the Arctic SDI). Semantic, geosemantic and organisational interoperability should come after in order to allow for visualizing, assessing and combining the available datasets coming from a number of sources. Finally, even though many of the Arctic SDI sources of data will be open, access to some sources will be restricted and the notion of legal interoperability will need to be addressed to protect these sources. |
| Data Sharing Principle |
This Arctic SDI Geoportal is intended to provide free and open access for any user. Some data available through this Geoportal may have usage restrictions. Using some features of the Geoportal may require registering and signing in as an authenticated user. The Arctic SDI incorporates data from multiple, distributed providers and each data set has a specific license. Arctic SDI's Geoportal Metadata Catalogue links to these data licenses as supplied by the respective data providers and it is the responsibility of the user to comply with these licenses, disclaimers, and/or copyright notices. The Arctic SDI Geoportal offers no warranty, expressed or implied, as to the accuracy, reliability or completeness of the information it contains. The Arctic SDI Geoportal strives to maintain high service availability, but does not guarantee uninterrupted access to the Arctic SDI Geoportal or the data services provided therein. |
