Where and how to find data on safety: what do systematic reviews of complementary therapies tell us?

Background: Successfully identifying relevant data for systematic reviews with a focus on safety may require retrieving information from a wider range of sources than for ‘effectiveness’ systematic reviews. Searching for safety data continues to prove a major challenge. Objectives: To examine search methods used in systematic reviews of safety and to investigate indexing. Methods: Systematic reviews focusing on safety of complementary therapies and related interventions were retrieved from comprehensive searches of major databases. Data was extracted on search strategies, sources used and indexing in major databases. Safety related search terms were compared against index terms available on major databases. Data extraction by one researcher using a pre-prepared template was checked for accuracy by a second researcher. Results: Screening of 2563 records resulted in 88 systematic reviews being identified. Information sources used varied with the type of intervention being addressed. Comparison of search terms with available index terms revealed additional potentially relevant terms that could be used in constructing search strategies. Seventy-nine reviews were indexed on PubMed, 84 on EMBASE, 21 on CINAHL, 15 on AMED, 6 on PsycINFO, 2 on BNI and HMIC. The mean number of generic safety-related indexing terms on PubMed records was 2.6. For EMBASE the mean number was 4.8 with at least 61 unique terms being employed. Most frequently used indexing terms and subheadings were adverse effects, side effects, drug interactions and herb-drug interactions. Use of terms specifically referring to safety varied across databases. Conclusions: Investigation of search methods revealed the range of information sources used, a list of which may prove a valuable resource for those planning to conduct systematic reviews of safety. The findings also indicated that there is potential to improve safety-related search strategies. Finally, an insight is provided into indexing of and most effective terms for finding safety studies on major databases.

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.