Testing iPad in the field: use of a relational database in garbological research

Recording thousands of entries during field research poses a challenge to any field researcher. Contemporary handheld computers offer affordable solutions, which can resolve this challenge. In this paper, we test the iPad tablet computer and FileMaker Go database to conduct garbological research carried out in West Bohemia (Czech Republic). Garbological research based on the collection of data about human waste requires not only efficient tools for recording a vast number of individual garbage items on the spot but also integration of multiple analytical levels in a database. Our research was aimed at household waste to illuminate consumption patterns and mobility of humans and things in contemporary Central European settings. The iPad was used to collect textual and visual data and integrate these in a relational database. We describe our methodology and experience with this kind of technology. The iPad and FileMaker Go proved to be well suited to challenging field conditions in the landfill, data collection was efficient and reliable, the database was flexible because its basic features could be modified in the field, and one could even examine preliminary trends in the data using charts in FileMaker Go. The proposed hardware and software is less efficient for the collection of precise spatial data, preparation of accurate drawings, and for projects in remote areas without good access to an electrical grid

Development of a Grid Enabled Occupational Data Environment

The GEODE project is developing user-oriented Grid-based services, accessible via a portal, for social scientists who require and use 'occupational information' within their research. There are many complexities associated with social scientists’ use of data on individual occupations. These arise for example from the availability of numerous alternative occupational classifications, and the use of different occupational definitions across countries. This paper describes how the GEODE project is developing an online service which acts as a facility supporting access to numerous occupational information resources. This is achieved through an integrated Grid service which uses a Globus Toolkit 4 infrastructure and OGSA-DAI (Database Access and Integration) middleware to provide the necessary data indexing and matching services, accessed through a user-oriented front-end portal (using GridSphere). The paper discusses issues in the implementation and organization of these services

Towards data grids for microarray expression profiles

The UK DTI funded Biomedical Research Informatics Delivered by Grid Enabled Services (BRIDGES) project developed a Grid infrastructure through which research into the genetic causes of hypertension could be supported by scientists within the large Wellcome Trust funded Cardiovascular Functional Genomics project. The BRIDGES project had a focus on developing a compute Grid and a data Grid infrastructure with security at its heart. Building on the work within BRIDGES, the BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project plans to provide an enhanced data Grid infrastructure to support richer queries needed for the discovery and analysis of microarray data sets, also based upon a fine-grained security infrastructure. This paper outlines the experiences gained within BRIDGES and outlines the status of the GEMEPS project, the open challenges that remain and plans for the future

Data access and integration in the ISPIDER proteomics grid

Grid computing has great potential for supporting the integration of complex, fast changing biological data repositories to enable distributed data analysis. One scenario where Grid computing has such potential is provided by proteomics resources which are rapidly being developed with the emergence of affordable, reliable methods to study the proteome. The protein identifications arising from these methods derive from multiple repositories which need to be integrated to enable uniform access to them. A number of technologies exist which enable these resources to be accessed in a Grid environment, but the independent development of these resources means that significant data integration challenges, such as heterogeneity and schema evolution, have to be met. This paper presents an architecture which supports the combined use of Grid data access (OGSA-DAI), Grid distributed querying (OGSA-DQP) and data integration (AutoMed) software tools to support distributed data analysis. We discuss the application of this architecture for the integration of several autonomous proteomics data resources

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

1st INCF Workshop on Sustainability of Neuroscience Databases

The goal of the workshop was to discuss issues related to the sustainability of neuroscience databases, identify problems and propose solutions, and formulate recommendations to the INCF. The report summarizes the discussions of invited participants from the neuroinformatics community as well as from other disciplines where sustainability issues have already been approached. The recommendations for the INCF involve rating, ranking, and supporting database sustainability