title: Information retrieval for ecological syntheses.
abstract: Research syntheses are increasingly being conducted within the fields of ecology and environmental management. Information retrieval is crucial in any synthesis in identifying data for inclusion whilst potentially reducing biases in the dataset gathered, yet the nature of ecological information provides several challenges when compared with medicine that should be considered when planning and undertaking searches. We present ten recommendations for anyone considering undertaking information retrieval for ecological research syntheses that highlight the main differences with medicine and, if adopted, may help reduce biases in the dataset retrieved, increase search efficiency and improve reporting standards. They are as follows: (1) plan for information retrieval at an early stage, (2) identify and use sources of help, (3) clearly define the question to be addressed, (4) ensure that provisions for managing, recording and reporting the search are in place, (5) select an appropriate search type, (6) identify sources to be used, (7) identify limitations of the sources, (8) ensure that the search vocabulary is appropriate, (9) identify limits and filters that can help direct the search, and (10) test the strategy to ensure that it is realistic and manageable. These recommendations may be of value for other disciplines where search infrastructures are not yet sufficiently well developed.
authors.affiliation: Department of Crop and Environment Sciences, Harper Adams University, Newport, Shropshire, TF10 8NB, UK.|Centre for Environmental Policy, Imperial College London, London, SW7 2AZ, UK.
authors.forename: Helen R
authors.initials: HR
authors.lastname: Bayliss
authors.affiliation: Institute of Health & Society, Newcastle University, Baddiley-Clark Building, Richardson Road, Newcastle upon Tyne, NE2 4AX, UK.
authors.forename: Fiona R
authors.initials: FR
authors.lastname: Beyer
mesh_terms: D000068598:Data Accuracy; D003627:Data Interpretation, Statistical; D057225:Data Mining / Q000379:methods*; D004463:Ecology / Q000379:methods*; D019317:Evidence-Based Medicine / Q000379:methods; D015201:Meta-Analysis as Topic; D012107:Research Design; D012196:Review Literature as Topic
keywords: data retrieval; ecology; literature review; literature search; systematic review