Elsevier

Ecological Informatics

Volume 8, March 2012, Pages 10-19
Ecological Informatics

Diverse or uniform? — Intercomparison of two major German project databases for interdisciplinary collaborative functional biodiversity research

https://doi.org/10.1016/j.ecoinf.2011.11.004Get rights and content

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.

Introduction

Functional biodiversity research explores the current state of biodiversity and relations to ecosystem functioning and services, as well as drivers and functional consequences of biodiversity changes (Bendix and Beck, 2009, Fischer et al., 2010). Since the Millennium Ecosystem Assessment (2005) it is widely accepted in science and society that biodiversity is being destroyed at alarming rates. At the same time, awareness has risen that the loss in the number of species might negatively affect the ability of ecosystems to function (Purvis and Hector, 2000). The nature of interactions among the causes of biodiversity change is poorly understood (Sala et al., 2000). Additional uncertainties remain about the relationships among different levels of biodiversity at multiple trophic levels and environmental conditions and processes, requiring long-term experiments to account for temporal fluctuations (Hooper et al., 2005). In summary, the main challenge is to analyze biodiversity as the focal issue in the context of ecosystem and functional aspects, while considering the biotic, abiotic, and anthropogenic spheres and ranging from genetic to landscape scales. This is currently the main approach of major German interdisciplinary collaborative research programs in functional biodiversity research, as funded e.g. by the German Research Foundation DFG (refer to DFG, 2009). This approach necessitates the integration of data and results across multiple sub-disciplines and scales, which results in high data heterogeneity (Reichman et al., 2011).

Consequently, each of the mentioned research programs must be supported by an Internet accessible working database. As the main synthesizing research infrastructure, the databases should particularly be designed for data storage, exchange, integration and basic data analyses (Michener and Brunt, 2000, Purvis and Hector, 2000). The challenge for functional diversity research is to deal with its great data diversity, which must be mapped appropriately by the database system (Bowker, 2000). Database architectures for research projects devoted to functional biodiversity must therefore support more functionalities of “wide” rather than “deep” databases, which are suitable for purely taxonomic datasets (Porter, 2000). Also, terminology varies across disciplines, which complicates data interpretation and re-use.

It should be stressed that project databases of collaborative research endeavors in general have a limited life time, as financial support is restricted to the funding period of the research program. Thus, they cannot be compared with repositories with dedicated and sustained funding. Project databases are also used as a marketplace for data presentation, browsing and exchange within the research consortium. Because data must be provided to other groups for interdisciplinary analyses as soon as possible, incomplete work-in-progress or ongoing datasets (e.g., time-series) need to be uploaded, which are then continuously complemented during the duration of the collaborative research project. Because the database must serve the specific demands of the respective collaborative project in merging different plot-based and spatial datasets, every project normally develops its own prototype system (e.g., Stoner et al., 2001). However, each of these prototype databases might contain information for a blueprint of a generic and comprehensive database system applicable to other collaborative projects dealing with functional biodiversity.

In the current paper, two different project database solutions of major German collaborative research programs in functional biodiversity research are comparatively analyzed. The authors elaborating this comparison are developers, data managers, and principal investigators of the systems and simultaneously researchers in the majority of German collaborative projects on functional biodiversity. Precursors of the compared systems started as early as 10 years ago. They have undergone several re-construction phases and adaptation to evolving research environments. At present, four out of five DFG funded collaborative functional biodiversity research projects run one of the presented solutions, and additional projects and administrations have indicated their interest.

Because the two systems have been developed completely independently but for a comparable purpose, the main aim is to establish whether the result of the development points to common design features, which then might be considered as mandatory for project databases. At the same time, differences in the database design, as well as the pursued administrative and technical solutions, should be analyzed to assess generic functionality versus project specific customization necessary to adapt working databases to individual research programs. In summary, the analysis should help to facilitate the decision making for future collaborative programs regarding the development of working databases.

Section snippets

Investigated projects

The first data base system, the Biodiversities Exploratories Information System (hereafter BExIS) serves the German Research Foundation (DFG) funded priority program SPP 1374, Biodiversity Exploratories, as work-in-progress storage (Green et al., 2009) and virtual research environment. The Biodiversity Exploratories (BE) are a long-term open research platform investigating the relationship between biodiversity of different taxa and levels, the role of land-use for biodiversity of different taxa

Fundamental system requirements

From 2007 on, both collaborative research projects developed data and information systems independently that were fitted to their respective project specifications. The development teams had previously employed LAMP (Linux, Apache, MySQL, PHP/Perl) based document management systems for data handling. At the beginning of the running research programs, they decided not to store tabular data in flat files. Instead, such files are parsed and the values are type checked and transferred into a

Conclusion

An in-depth analysis of the two database systems of collaborative research programs reveal many common features, especially in view of the fact that they were developed independently from each other. Both projects were started in order to enable good data communication in an interdisciplinary program devoted to functional/ecological biodiversity research and initially followed the same chronology of development. To date, they have nearly reached a comparable state of implementation.

Even if both

Acknowledgments

The authors are indebted to the German Research Foundation (DFG) for funding the development of the project databases in the scope of the Research Unit 816 (“Biodiversity and Sustainable Management of a Megadiverse Mountain Ecosystem in South Ecuador”; subproject Z1 Centra Data Services, BE-1780/21–2) and the DFG Priority Program 1374 (“Biodiversity Exploratories”, KO-2209/12–1). The work on the current article was also fostered by the Working Group data of the DFG Senate Commission on

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