Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes nearly 150 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies. Remote Sensing; Earth Science Informatics, Data Systems; Data Services; Metadat

The implementation of international geospatial standards for earth and space sciences

The Earth and Space Sciences Informatics division of European Geosciences Union (EGU) and the Open Geospatial Consortium jointly organised a special event entitled: 'Implementation of international geospatial standards for earth and space sciences event' - at the EGU General Assembly meeting held in Vienna, April 2009. The event objectives included: (a) to discuss the integration of information systems from different geosciences disciplines; (b) to promote and discuss the present process to scale from specific and monolithic systems towards independent and modular enabling infrastructures - forming an earth system science (ESS) infrastructure; and (c) to show some of the latest advances in implementing open standards. This manuscript introduces the event motivations and describes the abstract and holistic framework, which can be used to situate the topics and the developments presented by the event speakers. This manuscript introduces important, and relatively new technologies to build a multi-disciplinary geosciences information system: the System of Systems approach and the Model Driven Approach. To achieve that, three important information infrastructure categories are recognised: (a) ESS information infrastructure; (b) geospatial information infrastructure; and (c) distributed information infrastructure. Digital Earth should support the discussed framework to accelerate information transfer from theoretical discussions to applications, in all fields related to global climate change, natural disaster prevention and response, new energy-source development, agricultural and food security, and urban planning and management

Ontology For Europe's Space Situational Awareness Program

This paper presents an ontology architecture concept for the European Space Agency‘s (ESA) Space Situational Awareness (SSA) Program. It incorporates the author‘s domain ontology, The Space Situational Awareness Ontology and related ontology work. I summarize computational ontology, discuss the segments of ESA SSA, and introduce an option for a modular ontology framework reflecting the divisionsof the SSA program. Among other things, ontologies are used for data sharing and integration. By applying ontology to ESA data, the ESA may better achieve its integration and innovation goals, while simultaneously improving the state of peaceful SSA

The Orbital Space Environment and Space Situational Awareness Domain Ontology – Towards an International Information System for Space Data

The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding our knowledge of near-Earth space. To facilitate data-sharing interoperability among distinct orbital debris and space object catalogs, and SSA information systems, I proposed ontology in (Rovetto, 2015) and (Rovetto and Kelso, 2016). I continue this effort toward formal representations and models of the overall domain that may serve to improve peaceful SSA and increase our scientific knowledge. This paper explains the project concept introduced in those publications, summarizing efforts to date as well as the research field of ontology development and engineering. I describe concepts for an ontological framework for the orbital space environment, near-Earth space environment and SSA domain. An ontological framework is conceived as a part of a potential international information system. The purpose of such a system is to consolidate, analyze and reason over various sources and types of orbital and SSA data toward the mutually beneficial goals of safer space navigation and scientific research. Recent internationals findings on the limitations of orbital data, in addition to existing publications on collaborative SSA, demonstrate both the overlap with this project and the need for data-sharing and integration

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

Bridging the biodiversity data gaps: Recommendations to meet users’ data needs

A strong case has been made for freely available, high quality data on species occurrence, in order to track changes in biodiversity. However, one of the main issues surrounding the provision of such data is that sources vary in quality, scope, and accuracy. Therefore publishers of such data must face the challenge of maximizing quality, utility and breadth of data coverage, in order to make such data useful to users. Here, we report a number of recommendations that stem from a content need assessment survey conducted by the Global Biodiversity Information Facility (GBIF). Through this survey, we aimed to distil the main user needs regarding biodiversity data. We find a broad range of recommendations from the survey respondents, principally concerning issues such as data quality, bias, and coverage, and extending ease of access. We recommend a candidate set of actions for the GBIF that fall into three classes: 1) addressing data gaps, data volume, and data quality, 2) aggregating new kinds of data for new applications, and 3) promoting ease-of-use and providing incentives for wider use. Addressing the challenge of providing high quality primary biodiversity data can potentially serve the needs of many international biodiversity initiatives, including the new 2020 biodiversity targets of the Convention on Biological Diversity, the emerging global biodiversity observation network (GEO BON), and the new Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES)