A National Environmental Information Infrastructure

Climate change and human activities have a strong impact on lakes and their catchments, so to understand ongoing processes it is fundamental to monitor environmental variables with a spatially well-distributed and high frequency network and efficiently share data. An effective sharing and interoperability of environmental information between technician and end-user fosters an in-depth knowledge of the territory and its critical environmental issues. In this paper, we present the approaches and the results obtained during the PITAGORA project (Interoperable Technological Platform for Acquisition, Management and Organization of Environmental data, related to the lake basin). PITAGORA was aimed at developing both instruments and data management, including pre-processing and quality control of raw data to ensure that data are findable, accessible, interoperable, and reusable (FAIR principles). The main results show that the developed instrumentation is low-cost, easily implementable and reliable, and can be applied to the measurement of diverse environmental parameters such as meteorological, hydrological, physico-chemical, and geological. The flexibility of the solutions proposed make our system adaptable to different monitoring purposes, research, management, and civil protection. The real time access to environmental information can improve management of a territory and ecosystems, safety of the population, and sustainable socio-economic development.

Environmental information and data underpin achievement of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) mission at the Hanford Site. The Hanford Environmental Data Management (HEDM) Program is the DOE Richland Operations Office (RL) approach to develop and implement a formal program for managing environmental data and the associated records, materials, and systems at the Hanford Site. The current project, contract, organization, and contractor-specific efforts at managing environmental data sets are insufficient to provide orderly, long-term, site-wide access. A vital element to be created within the HEDM program plan is a catalog of data sources, called the Hanford Environmental Information and Data Index (HEIDI), that will enable long-term access and retrievability for the multiple independent sources of data that might otherwise be difficult to discover. This report compares leading open source and commercial data catalog platforms using criteria to assess the functionality needed to develop the HEIDI catalog of Hanford data sources that connects and exchanges data with established Hanford Local Area Network (HLAN) enterprise information technology systems. Proprietary platforms evaluated included ArcGIS Enterprise Sites, Junar, OpenDataSoft, and Socrata, and non-proprietary platforms included Energy Data eXchange (EDX), Comprehensive Knowledge Archive Network (CKAN), and DKAN (a Drupal-based open data portal based on CKAN). Capabilities supporting data discoverability, retrieval, and archival, as well as metadata standard requirements and integration into the HLAN were rated as either failing to meet requirements (F), meeting requirements (M), or exceeding requirements by delivering additional desired features (E). The lowest rating for any capability area was assigned as the overall rating for the platform. These findings enable DOE-RL and the contractors implementing the HEDM plan to focus on candidate tools likely to meet the requirements for implementing HEIDI. All of the platforms receiving an overall rating of ‘F’ were unable to be deployed on Hanford infrastructure or within dedicated cloud resources. A propriety software-as-a-service (SaaS) model of delivering a data catalog (e.g., found in software such as Junar and OpenDataSoft) favors consistency across customers at the expense of customization and configurable roles that are needed for Hanford work. Hosting data on a shared commercial platform places limits on dataset size (maximum of 240 Mb for OpenDataSoft), a significant limitation for HEIDI implementation. EDX, a government data catalog based on CKAN, received the ‘F’ rating due to an inability to incorporate authentication from HLAN into the system. Among platforms rated ‘M’ or ‘E’, only the Socrata platform had a SaaS delivery model. In contrast to other SaaS platforms, Socrata provided custom roles and gateways that allow local datasets to be incorporated into an online catalog. Socrata also complies with the Federal Risk and Authorization Management Program, a significant benefit for cloud-based management of Hanford data. The other platforms rated ‘M’ or ‘E’, ArcGIS Enterprise Sites, CKAN, and DKAN, provide fully self-hosted options, allowing for greater control and flexibility with the HEIDI catalog. These widely used tools have supportive communities of practice, extensive customization options, and demonstrated deployments that provide evidence that they can meet requirements, often deliver additional desired features, and work well with federal government systems. Completely customized alternatives built on a collection of applications were not evaluated because achieving similar performance to CKAN or DKAN requires substantial resources, especially in the absence of the active communities that have grown to support these tools. ArcGIS Enterprise Sites, Socrata, CKAN, and DKAN were evaluated as strong candidates for successful implementation with HEIDI.

ABSTRACTThe increasing amount of spatial data demands effective and efficient methods for managing them in spatial data infrastructures (SDIs). Metadata standards have been developed in response to the needs of data custodians who manage these ever-growing resources and in recognition of the end users’ need for easy access and discovery of spatial data. Data custodians prepare metadata records and allow SDIs to harvest them. The harvesting can be undertaken through metadata standards or data service standards. The metadata updating processes are not efficient and, therefore, create a disjoint between the data and its metadata. As a result, end users cannot realize the full potential of metadata records. In addressing this issue, the paper presents an automatic spatial metadata system with a suite of functions including metadata monitoring, enrichment, and maintenance to enable the data custodians to manage the integrity of their metadata records in SDIs. These functions have been demonstrated and reviewed through a case study in the Australian Urban Infrastructure Network (AURIN). Using these functions, AURIN’s data custodians have been able to offer over 1200 coherent and consistent spatial metadata records to end users.

Commonalities and differences between MDSplus and HDF5 data systems

The 2015 New York City Legionnaires' Disease Outbreak: A Case Study on a History-Making Outbreak.

With the advancement of GIS technology since its inception in 1960’s, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990’s and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration.

The knowledge of the submerged cultural heritage in the North Sea is rather limited. The Belgian North Sea is being used for a lot of different purposes, such as fishing, aggregate extraction, wind farms, dredging, etc. Due to these increasing economic activities, the underwater archive is in danger. In the context of the UNESCO Convention on the Protection of the Underwater Cultural Heritage of 2001, gathering more information about the submerged cultural heritage in the intertidal zones of the North Sea is one of the main objectives of the Belgian scientific project ‘SeArch’. It will give a clearer picture of the broader cultural and archaeological heritage in the region and it can be used as a basis for a sustainable management by government agencies. The Department of Geography (Ghent University, Belgium) contributes to the SeArch project in two ways. First, an innovative survey methodology has been developed which allows an accurate and cost-efficient evaluation of the archaeological potential in the intertidal zones of the Belgian beaches. Secondly, the Department of Geography is developing an interactive webGIS platform, which makes it possible to share, integrate and visualize the gathered archaeological and environmental data and information in a user-friendly way. Hereby, the total potential of this project is fully exploited in a time-efficient manner. To create an interactive webGIS platform, a good structured spatial database is needed. It enables manipulation of a wide variety of georeferenced information in both raster and vector formats. This paper provides more information about the configuration and application of the spatial database. Moreover, it focusses on the development of a fully functional Spatial Data Infrastructure (SDI) using the most reliable, powerful and state-of-the-art technological components. Besides, a new way of collecting geomatic data in a fast and accurate manner will be discussed. Some processing results will show the possibilities for detecting and visualizing underground structures and archaeological objects.

In order to implement the State Council and the MEE’s requirements on strengthening the integration and sharing of government information resources, this paper is to explore a unified management method of multi-source environmental information based on GeoSOT geographic grid. Since more than 90% of the environmental information has spatial attributes, based on the spatial position identification, it can realize the unified data management, relevant retrieval and spatial correlation analysis inside environmental protection department and around relevant ministries. Multi-scale spatial grid identification can also meet the requirements of different levels of management from macro to fine. The unified identity and management scheme of multi-source environmental data is expected to provide basic technical support for the integration of environmental protection information.

Increasing stress on global groundwater resources is leading to new approaches to the management and delivery of groundwater data. These approaches include the deployment of a Spatial Data Infrastructure (SDI) to enable online data interoperability amongst numerous and heterogeneous data sources. Often an important component of an SDI is a global domain schema, which serves as a central structure for the query and transport of data, but at present there does not exist a schema for groundwater data that is strongly compliant with SDI concepts, standards, and technologies. In this paper we present GroundWater Markup Language (GWML), a groundwater application of the Geography Markup Language (GML). GWML can be used in conjunction with a variety of web services to facilitate data interoperability in a SDI. We describe three common usage scenarios that motivate the design of GWML and a three-stage design methodology involving conceptual, logical and physical schemas. The resultant GWML has broad scope as demonstrated by its implementation in the Canadian Groundwater Information Network. Example uses include decision support in resource management, a scientific application for aquifer mapping, and a commercial application for drill site selection. These demonstrated uses suggest GWML can play a key role in emerging groundwater SDI.

Environmental monitoring and evaluation (M&E) systems are indispensable tools for sustainable land management, especially in dry and fragile ecosystems. The reporting and dissemination of its products and indicators are the key roles to perform their missions. Furthermore, the overall success of such multilateral projects and networks depends on well-organized infrastructures for spatial data management. A spatial data infrastructure (SDI) is an efficient framework to centralize the management of spatial data and information related to multilateral projects for the best sharing and exchange between partners and stakeholders in order to ensure that they are interactively connected to use the data efficiently and in a flexible manner. This paper outlines the work undertaken in partnership between the Geography and GIS Department of the Faculty of Arts, King Abdulaziz University, Saudi Arabia Kingdom, the Geomatics, Earth and Land Settlement Branch of the Department of Geology, Faculty of Sciences of Tunis, Tunis El Manar University, Tunisia, and the Sahara and Sahel Observatory OSS which is an intergovernmental organization, in order to build a Spatial Data Infrastructure (SDI) for the ROSELT/OSS program (Long-Term Environmental Monitoring Observatories Network in the Circum-Sahara of the Sahara and Sahel Observatory). This SDI is entirely developed using Open Source technologies and the extensive suite of OGC (Open Geospatial Consortium) standards and specifications, to enable interoperability among and between its different components.

Focused on the mechanics of managing environmental data, this book provides guidelines on how to evaluate data requirements, assess tools and techniques, and implement an effective system. Moving beyond the hypothetical, Gerald Burnette illustrates the decision-making processes and the compromises required when applying environmental principles and practices to actual data. Managing Environmental Data explains the basic principles of relational databases, discusses database design, explores user interface options, and examines the process of implementation. Best practices are identified during each portion of the process. The discussion is summarized via the development of a hypothetical environmental data management system. Details of the design help establish a common framework that bridges the gap between data managers, users, and software developers. It is an ideal text for environmental professionals and students. The growth in both volume and complexity of environmental data presents challenges to environmental professionals. Developing better data management skills offers an excellent opportunity to meet these challenges. Gaining knowledge of and experience with data management best practices complements students’ more traditional science education, providing them with the skills required to address complex data requirements.

The National Ocean Service, which I've headed since December 1983, is one of the major line components of the National Oceanic and Atmospheric Administration (NOAA). NOAA, in turn, is part of the Department of Commerce and is the leading federal agency in the oceanic and atmospheric sciences. Other agencies are involved in the earth sciences, such as the Department of the Interior's Geological Survey, or are in the business of environmental regulations, like the U.S. Environmental Protection Agency, but NOAA is the one federal agency charged specifically with analyzing and predicting oceanic and atmospheric components of the earth's environment as a whole. The importance of this global, integrated air‐sea approach is reflected in the five NOAA line offices.This past December, NOAA line offices were reorganized to consolidate programs as part of the Reagan Administration's general government‐wide belt tightening (see Figure 1). The idea was for NOAA to grow leaner but stronger. The main thrust of the work of the Weather Service and the Marine Fisheries Service remained the same. The Office of Oceanic and Atmospheric Research continued to provide research support to the other NOAA components. A trimmed down Environmental Data and Information Service merged with the National Environmental Satellite Service to become today's National Environmental Satellite, Data, and Information Service. Also, this past December the NOAA Office of Coastal Zone Management joined forces with the National Ocean Survey to become the National Ocean Service.

Considerable attention has been directed towards techniques and procedures which facilitate the high quality of field-collected ambient environmental data. This study addresses the quality control methods used to assure data quality after the data have been recorded. The two major elements associated with the validation of much of Tennessee Valley Authority's (TVA's) environmental data are: (1) initial computer flagging of physically/chemically questionable and outlying data and (2) analyst review and feedback to field technicians to implement corrective actions. Examples of these procedures as applied to aerometric data will be discussed. The benefits of this approach include timely feedback to the field technicians to resolve potential problems with a monitoring system and assignment of quality code ratings and precision and accuracy to all archived and reported data.

This paper aims at reevaluating the role of Spatial Data Infrastructure (SDI) as an initiative which can facilitate disaster management by providing a better way for managing spatial data. SDI contains technological and non-technological aspects for sharing and exploiting geo-information resources. The results of the research have shown that a prototype emergency spatial data sharing system using an SDI framework can assist the disaster management in such a way that they can improve the efficiency and quality of data for the decision making and increase the effectiveness in data collection and sharing activities during the management of emergency spatial data.

The need for spatially explicit thematic data is currently increasing in parallel to the development of observing, storing and processing capabilities. This requires an integrated data management structure in which human and institutional aspects play a key role as part of a Spatial Data Infrastructure (SDI). We focus in this study on the African continent to evaluate the status of its SDI implementation. Because assessing SDI at a continental scale in a traditional way (i.e. following methods developed for national assessments) requires financial resources and mechanisms only affordable to developed countries (e.g. European Union), alternative ways have been explored based on fourteen key SDI indicators that were validated by SDI experts in a previous study. Data was collected for each African country through the African leading SDI institution (UN Economic Commission for Africa) and through Internet searches. We found relatively weak scores of the fourteen SDI indicators for African countries compared to the rest of the World, but with notable differences within Africa. We discuss the implication of the lack of information available on the Internet to assess SDI status in Africa. We conclude that it is necessary to improve statistical information in most African countries. This requires an agreed-on geospatial data structure and organization between concerned institutions that is only achievable through a shared global vision on geospatial data governance. To this end, we suggest a few quick wins and several new mechanisms that would enhance the flow of SDI statistical information and improve data management structure in Africa.