Frank A. Bisby

How global is the global biodiversity information facility

There is a concerted global effort to digitize biodiversity occurrence data from herbarium and museum collections that together offer an unparalleled archive of life on Earth over the past few centuries. The Global Biodiversity Information Facility provides the largest single gateway to these data. Since 2004 it has provided a single point of access to specimen data from databases of biological surveys and collections. Biologists now have rapid access to more than 120 million observations, for use in many biological analyses. We investigate the quality and coverage of data digitally available, from the perspective of a biologist seeking distribution data for spatial analysis on a global scale. We present an example of automatic verification of geographic data using distributions from the International Legume Database and Information Service to test empirically, issues of geographic coverage and accuracy. There are over 1/2 million records covering 31% of all Legume species, and 84% of these records pass geographic validation. These data are not yet a global biodiversity resource for all species, or all countries. A user will encounter many biases and gaps in these data which should be understood before data are used or analyzed. The data are notably deficient in many of the worlds biodiversity hotspots. The deficiencies in data coverage can be resolved by an increased application of resources to digitize and publish data throughout these most diverse regions. But in the push to provide ever more data online, we should not forget that consistent data quality is of paramount importance if the data are to be useful in capturing a meaningful picture of life on Earth.

Adapting integrity enforcement techniques for data reconciliation

Integration of data sources opens up possibilities for new and valuable applications of data that cannot be supported by the individual sources alone. Unfortunately, many data integration projects are hindered by the inherent heterogeneities in the sources to be integrated. In particular, differences in the way that real world data is encoded within sources can cause a range of difficulties, not least of which is that the conflicting semantics may not be recognised until the integration project is well under way. Once identified, semantic conflicts of this kind are typically dealt with by configuring a data transformation engine, that can convert incoming data into the form required by the integrated system. However, determination of a complete and consistent set of data transformations for any given integration task is far from trivial. In this paper, we explore the potential application of techniques for integrity enforcement in supporting this process. We describe the design of a data reconciliation tool (LITCHI) based on these techniques that aims to assist taxonomists in the integration of biodiversity data sets. Our experiences have highlighted several limitations of integrity enforcement when applied to this real world problem, and we describe how we have overcome these in the design of our system.

SPICE: A Flexible Architecture for Integrating Autonomous Databases to Comprise a Distributed Catalogue of Life

In the SPICE project we are building a distributed catalogue of life, which will eventually be formed from up to 200 autonomous taxonomic databases. We are faced with a number of challenges, which include the scalability of the system; the accommodation of partial or missing data; queries which are potentially very expensive computationally, where it is difficult to determine which databases will contain data matching the queries, and the effective integration of heterogeneous databases at the knowledge level. In this paper we present the architecture on which SPICE is being built, and we explain how, within our SPICE architecture, we will be able to explore and develop new techniques to enhance access to the SPICE distributed database.

Conflict detection for integration of taxonomic data sources

Over recent years, international initiatives such as the 1993 UN Convention on Biological Diversity have highlighted the need for information about species diversity on a global scale. However, attempts to build global information systems by integrating smaller, independently created biodiversity databases have been hampered by differences in the sets of species names used. Some databases use different names to refer to the same species, while in other cases the same name can be applied to differing definitions of a species, or even entirely different species. The LITCHI project aims to assist biologists in the integration of databases by searching for conflicts within taxonomic checklists (i.e. lists of the species names used in a database and the relationships between them). In order to detect such conflicts, we have created a formal model of taxonomic practice, which describes (amongst other things) what it means for a checklist to be consistent and well-specified. This model has been used as the basis for a prototype tool that uses Prolog to search for naming conflicts within a relational database of checklists. We describe the background to our formal model and show how it has been used to implement the LITCHI system. Our prototype tool is already proving its worth by detecting conflicts and errors within real taxonomic checklists.

Accessing biodiversity resources in computational environments from workflow applications

In the biodiversity world (BDW) project we have created a flexible and extensible Web services-based grid environment for biodiversity researchers to solve problems in biodiversity and analyse biodiversity patterns. In this environment, heterogeneous and globally distributed biodiversity-related resources such as data sets and analytical tools are made available to be accessed and assembled by users into workflows to perform complex scientific experiments. One such experiment is bioclimatic modelling of the geographical distribution of individual species using climate variables in order to predict past and future climate-related changes in species distribution. Data sources and analytical tools required for such analysis of species distribution are widely dispersed, available on heterogeneous platforms, present data in different formats and lack interoperability. The BDW system brings all these disparate units together so that the user can combine tools with little thought as to their availability, data formats and interoperability. The current Web Services-based grid environment enables execution of the BDW workflow tasks in remote nodes but with a limited scope. The next step in the evolution of the BDW architecture is to enable workflow tasks to utilise computational resources available within and outside the BDW domain. We describe the present BDW architecture and its transition to a new framework which provides a distributed computational environment for mapping and executing workflows in addition to bringing together heterogeneous resources and analytical tools.

LITCHI: knowledge integrity testing for taxonomic databases

Summary form only given. The LITCHI project (Logic-based Integration of Taxonomic Conflicts in Heterogeneous Information Systems) aims to develop software to enable the automated detection and, where possible, resolution of conflicts in taxonomic checklists. A taxonomic checklist is a list of the names of species (and other taxa) used within a particular biological database. Since species names are typically used to gain access to data within biological databases, checklists provide a concise representation of the data values that can act as keys when querying such databases. More importantly, species names are also typically used as the join attribute when integrating several biological databases. However, naming of species is a subjective activity, and different scientific communities will have different ideas about the names that should be used for particular species. These conflicts of opinion arise as a result of the subjective nature of the classification process and geographical or historical differences in background knowledge. Some communities may use different names for the same species, while other groups of scientists may use the same name to refer to different species. Often, there is no one right naming scheme, but some consistent set of names must be used if biological databases are to be integrated. Therefore, there is a real need for a tool which will assist biologists in the integration of checklists, prior to the integration of species databases, so that these differences of opinion can be resolved.

Supporting the construction of workflows for biodiversity problem-solving accessing secure, distributed resources

In the Biodiversity World (BDW) project we have created a flexible and extensible Web Services-based Grid environment for biodiversity researchers to solve problems in biodiversity and analyse biodiversity patterns. In this environment, heterogeneous and globally distributed biodiversity-related resources such as data sets and analytical tools are made available to be accessed and assembled by users into workflows to perform complex scientific experiments. One such experiment is bioclimatic modelling of the geographical distribution of individual species using climate variables in order to explain past and future climate-related changes in species distribution. Data sources and analytical tools required for such analysis of species distribution are widely dispersed, available on heterogeneous platforms, present data in different formats and lack inherent interoperability. The present BDW system brings all these disparate units together so that the user can combine tools with little thought as to their original availability, data formats and interoperability. The new prototype BDW system architecture not only brings together heterogeneous resources but also enables utilisation of computational resources and provides a secure access to BDW resources via a federated security model. We describe features of the new BDW system and its security model which enable user authentication from a workflow application as part of workflow execution.

Assisting the integration of taxonomic data: the LITCHI toolkit

We demonstrate a prototype toolkit that uses constraints and constraint violation repair techniques to enable the automated detection and, where possible, the automated resolution of conflicts in taxonomic databases.