Found 2 publication(s)
Bendix, J.; Nieschulze, J. & Michener, W.K. (2012): Data platforms in integrative biodiversity research. Ecological Informatics 11, 1-4.
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- DOI: 10.1016/j.ecoinf.2012.04.001
- Abstract: It is widely recognized ...
- Keywords: | Biodiversity | Metadata | Multidisciplinary | Data | Ontology | Repository |
Abstract:It is widely recognized that biodiversity and ecosystem services are globally threatened by environmental change and that the goal to halt the loss of species richness by 2010 has failed (Butchart et al., 2010). Despite the apparent interrelationships between biodiversity and abiotic (e.g. in case of climate change) and anthropogenic factors (e.g. in case of land use change), much remains to be understood about the causative mechanisms of biodiversity change and their interactions (Fischer et al., 2010 and Sala et al., 2000). This lack of understanding points to a clear need for more integrative biodiversity research that engages biologists and scientists from diverse disciplines, ranging from geosciences to socioeconomics. Such comprehensive research approaches are underpinned by the development of new monitoring systems of biodiversity and ecosystem services as indicated by the new international body IPBES (Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services; Marris, 2010). Knowledge of past biodiversity changes and accurate forecasts of future changes (c.f. La Sorte and Jetz, 2010; Pereira et al., 2010; Sala et al., 2000) depend upon diverse data and data types from innumerable sources over long time scales. Such data requirements are challenged by the scarcity of relevant biodiversity data from the last century due to the absence of comprehensive data stewardship practices and long-lived digital repositories, particularly for short-term research projects (see “fate of research data” in Easterbrook and Matthews, 1992; and “data entropy” in Michener et al., 1997). Although there is increasing awareness of the importance of data stewardship and preservation, the research community is now facing the challenge of exponentially growing data volumes in all disciplines that could contribute to more integrative biodiversity research (e.g. species data: Soberón and Peterson, 2009; genomic data: Kahn, 2011; climate data: Overpeck et al., 2011). Furthermore, globally available data are characterized by many problems including: incomplete taxonomic and spatial coverage, incompatibility among data sets, and inherent difficulties in integrating data across different scales (Pereira and Cooper, 2006). Most existing data repositories provide limited support for managing, integrating and visualizing relevant data (Guralnick et al., 2007 and Torres et al., 2006) and are not well positioned for dealing with upcoming biodiversity-related science challenges (Reichman et al., 2011). Some positive changes are underway. For instance, during the last decade of the preceding century, most data were managed by individuals in small, independent, institution-specific databases (Frawley et al., 1992). Increasingly, however, data are being deposited in community-based data repositories. As an example, the Directory of Open Access Repositories (OpenDOAR, http://www.opendoar.org/about.html, access: 5 Mar 2011) encompasses 1873 repositories, although just 2% are specifically focused on biodiversity and ecological data. To cope with the growing volume of taxonomic data, Bisby (2000) estimated a global demand for approximately 150 species databases, each covering 10,000 to 25,000 or more species. Arzberger et al. (2004) highlighted three actions that would lead to more open global data access. First, from the technical perspective, data and metadata standardization, data interoperability and user-friendly interfaces are priority needs. Second, sustainable technical, institutional and funding strategies are required. Third, technical and administrative solutions will largely be shaped through consideration of property rights and user behavior. These three principal challenges will be discussed in the current special issue by information technology experts from the biodiversity and environmental sciences. Some of the specific challenges addressed in this special issue are briefly introduced in the following sections.
Lotz, T.; Nieschulze, J.; Bendix, J.; Dobbermann, M. & König-Ries, B. (2012): Diverse or uniform - Intercomparison of two major German projectdatabases for interdisciplinary collaborative functional biodiversity research. Ecological Informatics 8, 10-19.
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- DOI: 10.1016/j.ecoinf.2011.11.004
- Abstract: Research on biodiversity...
- Keywords: | Information management system | Collaborative research project | Metadata | Data acquisition | Data exploration | Data curation |
Abstract:Research on biodiversity, its relation to ecosystem functioning and services, and the assessment of the impacts of environmental change on biodiversity needs an interdisciplinary perspective. This implies a great diversity of data and data formats gathered mostly in short- to mid-term collaborative research projects. It has been common practice that projects develop specific data management and communication solutions. We compare solutions of two major German collaborative research programs in functional biodiversity research to derive functional commonalities. This in-depth analysis follows five categories of the data life cycle: (i) data acquisition, (ii) metadata management, (iii) database, (iv) exploration, analysis and visualization, and (v) data curation and preservation. The results show that even though both systems were developed completely independently, they reveal comparable overall features and a similar state of implementation. Major focus areas lie in the implementation of comparable metadata schemas and their importance for storage and access strategies for tabular data on the value level. Basic analysis tools and similar management functions are considered. Intensive communication with the users and the orientation of ongoing developments based on user requirements is also important. Both systems are different mostly in specific details which, however, do not influence the overall comparable performance. It should be also emphasized that the same functionality is achieved with completely different software. The choice of software is based on the evaluation of available technologies. Thereby it might be influenced by individual experiences of the developers, but is mainly determined by the data diversity, which forces the usage of flexible technologies to develop adaptable systems. It is concluded that overall features for project databases of collaborative research projects must be supplemented by sophisticated data description, storage, and analysis structures to serve the requirements of integrative functional biodiversity research.