To share or not to share: Publication and quality assurance of research data outputs. A report commissioned by the Research Information Network

A study on current practices with respect to data creation, use, sharing and publication in eight research disciplines (systems biology, genomics, astronomy, chemical crystallography, rural economy and land use, classics, climate science and social and public health science). The study looked at data creation and care, motivations for sharing data, discovery, access and usability of datasets and quality assurance of data in each discipline

Open access self-archiving: An author study

This, our second author international, cross-disciplinary study on open access had 1296 respondents. Its focus was on self-archiving. Almost half (49%) of the respondent population have self-archived at least one article during the last three years. Use of institutional repositories for this purpose has doubled and usage has increased by almost 60% for subject-based repositories. Self-archiving activity is greatest amongst those who publish the largest number of papers. There is still a substantial proportion of authors unaware of the possibility of providing open access to their work by self-archiving. Of the authors who have not yet self-archived any articles, 71% remain unaware of the option. With 49% of the author population having self-archived in some way, this means that 36% of the total author population (71% of the remaining 51%), has not yet been appraised of this way of providing open access. Authors have frequently expressed reluctance to self-archive because of the perceived time required and possible technical difficulties in carrying out this activity, yet findings here show that only 20% of authors found some degree of difficulty with the first act of depositing an article in a repository, and that this dropped to 9% for subsequent deposits. Another author worry is about infringing agreed copyright agreements with publishers, yet only 10% of authors currently know of the SHERPA/RoMEO list of publisher permissions policies with respect to self-archiving, where clear guidance as to what a publisher permits is provided. Where it is not known if permission is required, however, authors are not seeking it and are self-archiving without it. Communicating their results to peers remains the primary reason for scholars publishing their work; in other words, researchers publish to have an impact on their field. The vast majority of authors (81%) would willingly comply with a mandate from their employer or research funder to deposit copies of their articles in an institutional or subject-based repository. A further 13% would comply reluctantly; 5% would not comply with such a mandate

Authors and open access publishing

Surveys were carried out to learn more about authors and open access publishing. Awareness of open access journals among those who had not published in them was quite high; awareness of "self-archiving" wasless. For open access journal authors the most important reason for publishing in that way was the principle of free access; their main concerns were grants and impact. Authors who had not published in an open access journal attributed that to unfamiliarity with such journals. Forty per cent of authors have self-archived their traditional journal articles and almost twice as many say they would do so if required to

ISC/OSI Journal Authors Survey Report

On behalf of the Joint Information Systems Committee (JISC) and the Open Society Institute (OSI) a survey of journal authors has been carried out by Key Perspectives Ltd. The terms of reference were to poll a cohort of authors who had published on an open access basis and another cohort of authors who had published their work in conventional journals without making the article available on open access. The survey’s aims were to investigate the authors’ awareness of new open access possibilities, the ease of identification of and submission to open access outlets, their experiences of publishing their work in this way, their concerns about any implications open access publishing may have upon their careers, and the reasons why (or not) they chose to publish through an open access outlet

Pioneering Women\u27s Committee Struggles with Hard Times

[Excerpt] The Women\u27s Committee of IUE Local 201, established informally in 1976 and officially in 1978, is one of the oldest and longest-lived union women\u27s committees in the country. It took root and thrived within a large and overwhelmingly male General Electric manufacturing complex in the Greater Boston area and within one of the oldest, most democratic and most progressive union locals in the labor movement. For the past 11 years, the Committee has battled an extremely insensitive and recalcitrant GE management over a wide range of issues — winning substantial victories for training and entry of women into skilled jobs, for comparable worth wage adjustments in traditional jobs, and for pregnancy disability benefits and parental leave. Committee members have counseled hundreds of women and spearheaded fights for individual grievances on pregnancy disability, sexual harassment and discrimination. Within the local, the Committee\u27s activities have created a more positive climate for women to become stewards and committee members and to run for offices on the Policy Board. Most of the Committee leaders and many of the active members are a key part of the progressive wing within Local 201. But the local now faces massive layoffs triggered by GE\u27s transfer of work to other plants in the U.S. and abroad. The cuts began in June 1987 and are expected to reach 3,000 or 4,000 members by the middle of 1989. With its ranks being cut in half, Local 201 membership is understandably uneasy about its future, and many of the Women\u27s Committee\u27s past accomplishments are now in jeopardy. As preparations begin for the national GE contract, which expires in June, GE is pushing for major concessions as the price to pay for job security. The progressive movement is faced with the dual tasks of opposing concessions and pushing to save jobs. In this context, the Women\u27s Committee\u27s challenge is to push ahead with its agenda in a very difficult political climate. As 1988 begins, both Local 201 and its Women\u27s Committee are in rapid transition

Similarity-based virtual screening using 2D fingerprints

This paper summarises recent work at the University of Sheffield on virtual screening methods that use 2D fingerprint measures of structural similarity. A detailed comparison of a large number of similarity coefficients demonstrates that the well-known Tanimoto coefficient remains the method of choice for the computation of fingerprint-based similarity, despite possessing some inherent biases related to the sizes of the molecules that are being sought. Group fusion involves combining the results of similarity searches based on multiple reference structures and a single similarity measure. We demonstrate the effectiveness of this approach to screening, and also describe an approximate form of group fusion, turbo similarity searching, that can be used when just a single reference structure is available

Extracting Information from Weighted Contact Networks via Genetic Algorithms

Epidemic contact tracing examines the movement of infection through a population based upon links in a contact network, and weighted networks represent the potential of transfer of the contagion. Graph compression reduces the size of a network by merging groups of nodes into supernodes. This study considers the use of genetic algorithms to select the nodes to be merged, grouping together highly connected sections of the graphs. Examined is a dataset that is extracted from contacts that occurred during several days of the "Infectious: Stay Away" event. The incorporation of weights, to indicate the strength of interactions between individuals, is an important contribution of this work. The demonstrated outcomes are that by including weighted information on the edges, there is more effective detection of highly interacting subgroups when compared to the unweighted version of graphs. These methods not only compress the networks with a low rate of distortion, but also the identification of supernodes in the networks allows for better targeting of interventions by public health upon individuals in such groups. This is crucial because when one member becomes infected, all members of the group are exposed to the contagion

Developing a model for e-prints and open access journal content in UK further and higher education

A study carried out for the UK Joint Information Systems Committee examined models for the provision of access to material in institutional and subject-based archives and in open access journals. Their relative merits were considered, addressing not only technical concerns but also how e-print provision (by authors) can be achieved – an essential factor for an effective e-print delivery service (for users). A "harvesting" model is recommended, where the metadata of articles deposited in distributed archives are harvested, stored and enhanced by a national service. This model has major advantages over the alternatives of a national centralized service or a completely decentralized one. Options for the implementation of a service based on the harvesting model are presented

Descriptive Symbolic Models of Gaits from Parkinson's Disease Patients

Parkinson's disease (PD) is a degenerative disorder of the central nervous system that has many debilitating symptoms which affect the patient's motor system and can cause significant changes in their gait. By using genetic programming, we aim to develop descriptive symbolic nonlinear models of PD patient gait from time series data recorded from pressure sensors under subjects' feet. When compared to popular types of linear regression (OLS and LASSO), the nonlinear models fit their data better and generalize to unseen data significantly better. It was found that models developed for healthy control subjects generalized to other control subjects well, however the models trained on subjects with PD did not generalize well to other PD patients, which complicates the issue of being able to detect the progression of the disease. It is suspected that health care professionals can have difficulty classifying PD due to a lack of accurate data from patient reports; having individually trained models for active monitoring of patients would help in effectively diagnosing PD

Gait Model Analysis of Parkinson’s Disease Patients under Cognitive Load

Parkinson's disease is a neurodegenerative disease that affects close to 10 million with various symptoms including tremors and changes in gait. Observing differences or changes in an individual's manifestations of gait may provide a mechanism to identify Parkinson's disease and understand specific changes. In this study, timeseries data from both Control subjects and Parkinson's disease patients was modelled with symbolic regression and extreme gradient boosting. Model effectiveness was analyzed along with the differences in the models between modelling strategies, between Control subjects and Parkinson's disease patients, and between normal walking and walking while under a cognitive load. Both modelling strategies were found to effective. The symbolic regression models were more easily interpreted, while extreme gradient boosting had higher overall accuracy. Interpretation of the models identified certain characteristics that distinguished Control subjects from Parkinson's disease patients and normal walking conditions from walking while under a cognitive load