Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval

Enriching ontological user profiles with tagging history for multi-domain recommendations

Many advanced recommendation frameworks employ ontologies of various complexities to model individuals and items, providing a mechanism for the expression of user interests and the representation of item attributes. As a result, complex matching techniques can be applied to support individuals in the discovery of items according to explicit and implicit user preferences. Recently, the rapid adoption of Web2.0, and the proliferation of social networking sites, has resulted in more and more users providing an increasing amount of information about themselves that could be exploited for recommendation purposes. However, the unification of personal information with ontologies using the contemporary knowledge representation methods often associated with Web2.0 applications, such as community tagging, is a non-trivial task. In this paper, we propose a method for the unification of tags with ontologies by grounding tags to a shared representation in the form of Wordnet and Wikipedia. We incorporate individuals' tagging history into their ontological profiles by matching tags with ontology concepts. This approach is preliminary evaluated by extending an existing news recommendation system with user tagging histories harvested from popular social networking sites

A comparative analysis of 21 literature search engines

With increasing number of bibliographic software, scientists and health professionals either make a subjective choice of tool(s) that could suit their needs or face a challenge of analyzing multiple features of a plethora of search programs. There is an urgent need for a thorough comparative analysis of the available bio-literature scanning tools, from the user’s perspective. We report results of the first time semi-quantitative comparison of 21 programs, which can search published (partial or full text) documents in life science areas. The observations can assist life science researchers and medical professionals to make an informed selection among the programs, depending on their search objectives. 
Some of the important findings are: 
1. Most of the hits obtained from Scopus, ReleMed, EBImed, CiteXplore, and HighWire Press were usually relevant (i.e. these tools show a better precision than other tools). 
2. But a very high number of relevant citations were retrieved by HighWire Press, Google Scholar, CiteXplore and Pubmed Central (they had better recall). 
3. HWP and CiteXplore seemed to have a good balance of precision and recall efficiencies. 
4. PubMed Central, PubMed and Scopus provided the most useful query systems. 
5. GoPubMed, BioAsk, EBIMed, ClusterMed could be more useful among the tools that can automatically process the retrieved citations for further scanning of bio-entities such as proteins, diseases, tissues, molecular interactions, etc. 
The authors suggest the use of PubMed, Scopus, Google Scholar and HighWire Press - for better coverage, and GoPubMed - to view the hits categorized based on the MeSH and gene ontology terms. The article is relavant to all life science subjects.
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Choosing and using methodological search filters : searchers' views

© 2014 The authors. Health Information and Libraries Journal © 2014 Health Libraries Group.Peer reviewedPostprin

Improving average ranking precision in user searches for biomedical research datasets

Availability of research datasets is keystone for health and life science study reproducibility and scientific progress. Due to the heterogeneity and complexity of these data, a main challenge to be overcome by research data management systems is to provide users with the best answers for their search queries. In the context of the 2016 bioCADDIE Dataset Retrieval Challenge, we investigate a novel ranking pipeline to improve the search of datasets used in biomedical experiments. Our system comprises a query expansion model based on word embeddings, a similarity measure algorithm that takes into consideration the relevance of the query terms, and a dataset categorisation method that boosts the rank of datasets matching query constraints. The system was evaluated using a corpus with 800k datasets and 21 annotated user queries. Our system provides competitive results when compared to the other challenge participants. In the official run, it achieved the highest infAP among the participants, being +22.3% higher than the median infAP of the participant's best submissions. Overall, it is ranked at top 2 if an aggregated metric using the best official measures per participant is considered. The query expansion method showed positive impact on the system's performance increasing our baseline up to +5.0% and +3.4% for the infAP and infNDCG metrics, respectively. Our similarity measure algorithm seems to be robust, in particular compared to Divergence From Randomness framework, having smaller performance variations under different training conditions. Finally, the result categorization did not have significant impact on the system's performance. We believe that our solution could be used to enhance biomedical dataset management systems. In particular, the use of data driven query expansion methods could be an alternative to the complexity of biomedical terminologies

Information seeking retrieval, reading and storing behaviour of library users

In the interest of digital libraries, it is advisable that designers be aware of the potential behaviour of the users of such a system. There are two distinct parts under investigation, the interaction between traditional libraries involving the seeking and retrieval of relevant material, and the reading and storage behaviours ensuing. Through this analysis, the findings could be incorporated into digital library facilities. There has been copious amounts of research on information seeking leading to the development of behavioural models to describe the process. Often research on the information seeking practices of individuals is based on the task and field of study. The information seeking model, presented by Ellis et al. (1993), characterises the format of this study where it is used to compare various research on the information seeking practices of groups of people (from academics to professionals). It is found that, although researchers do make use of library facilities, they tend to rely heavily on their own collections and primarily use the library as a source for previously identified information, browsing and interloan. It was found that there are significant differences in user behaviour between the groups analysed. When looking at the reading and storage of material it was hard to draw conclusions, due to the lack of substantial research and information on the topic. However, through the use of reading strategies, a general idea on how readers behave can be developed. Designers of digital libraries can benefit from the guidelines presented here to better understand their audience

Identifying studies for systematic reviews - An example from medical imaging

Objectives: To determine if published figures on the proportion of articles included in systematic reviews and identified in electronic databases are applicable to an example from medical imaging. Methods: A systematic review was performed. Additionally, sensitivity and precision of a MEDLINE search were compared with values from three published searches, each customized for a specific field. Results: All articles included in the systematic review were in electronic databases. The MEDLINE search had low precision compared with searches in other fields. Conclusions: in a specific area of medical imaging, electronic databases, including MEDLINE, are reliable sources of articles

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

Tailored retrieval of health information from the web for facilitating communication and empowerment of elderly people

A patient, nowadays, acquires health information from the Web mainly through a “human-to-machine” communication process with a generic search engine. This, in turn, affects, positively or negatively, his/her empowerment level and the “human-to-human” communication process that occurs between a patient and a healthcare professional such as a doctor. A generic communication process can be modelled by considering its syntactic-technical, semantic-meaning, and pragmatic-effectiveness levels and an efficacious communication occurs when all the communication levels are fully addressed. In the case of retrieval of health information from the Web, although a generic search engine is able to work at the syntactic-technical level, the semantic and pragmatic aspects are left to the user and this can be challenging, especially for elderly people. This work presents a custom search engine, FACILE, that works at the three communication levels and allows to overcome the challenges confronted during the search process. A patient can specify his/her information requirements in a simple way and FACILE will retrieve the “right” amount of Web content in a language that he/she can easily understand. This facilitates the comprehension of the found information and positively affects the empowerment process and communication with healthcare professionals