Journal articles: 'Share data'

1

Duke, Clifford S. "Data: share and share alike." Frontiers in Ecology and the Environment 4, no. 8 (October 2006): 395. http://dx.doi.org/10.1890/1540-9295(2006)4[395:dsasa]2.0.co;2.

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Evans-Pughe, C. "Share and share alike [data sharing]." Engineering & Technology 1, no. 8 (November 1, 2006): 30–35. http://dx.doi.org/10.1049/et:20060801.

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JARVIS, LISA. "DRUGMAKERS SHARE DATA." Chemical & Engineering News 88, no. 25 (June 21, 2010): 6. http://dx.doi.org/10.1021/cen-v088n025.p006.

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Mitka, Mike. "Clinical Trial Data: Share and Share Alike?" JAMA 313, no. 9 (March 3, 2015): 881. http://dx.doi.org/10.1001/jama.2015.481.

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. "Optimal data use: share your data." TSG 88, no. 2 (February 2010): 50. http://dx.doi.org/10.1007/bf03089540.

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Sieber, Joan E. "Learning to Share Data." Contemporary Psychology: A Journal of Reviews 40, no. 5 (May 1995): 476–77. http://dx.doi.org/10.1037/003670.

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Karhulahti, Veli-Matti. "Want the games industry to share data? Share yours." Nature 592, no. 7852 (March 30, 2021): 26. http://dx.doi.org/10.1038/d41586-021-00860-z.

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Berman, Jules J. "Racing to Share Pathology Data." American Journal of Clinical Pathology 121, no. 2 (February 2004): 169–71. http://dx.doi.org/10.1309/f7b40jmq4f8vpdg6.

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Baker, Monya. "Quantitative data: learning to share." Nature Methods 9, no. 1 (December 28, 2011): 39–41. http://dx.doi.org/10.1038/nmeth.1815.

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Li, Xiaogang, Dawei Zhang, Zhiyong Liu, Zhong Li, Cuiwei Du, and Chaofang Dong. "Materials science: Share corrosion data." Nature 527, no. 7579 (November 2015): 441–42. http://dx.doi.org/10.1038/527441a.

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Melton, Gary B. "Must researchers share their data?" Law and Human Behavior 12, no. 2 (1988): 159–62. http://dx.doi.org/10.1007/bf01073123.

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Simms, Andrew. "How Useful Are Osteoarchaeological Methods in Supporting Current Interpretations for Violent Death? A Review of the Data from Iron Age Burial Contexts in England." SHARE: Studies In History, Archaeology, Religion And Conservation 4, no. 1 (July 9, 2020): 1. http://dx.doi.org/10.18573/share.11.

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ZABLOCKI, ELAINE. "Local Health Information Networks Share Data." Skin & Allergy News 36, no. 10 (October 2005): 62. http://dx.doi.org/10.1016/s0037-6337(05)70766-x.

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Nanda, Shreeya, and Maria K. Kowalczuk. "Unpublished genomic data–how to share?" BMC Genomics 15, no. 1 (2014): 5. http://dx.doi.org/10.1186/1471-2164-15-5.

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Ellis, Shannon E., and Jeffrey T. Leek. "How to Share Data for Collaboration." American Statistician 72, no. 1 (January 2, 2018): 53–57. http://dx.doi.org/10.1080/00031305.2017.1375987.

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ZABLOCKI, ELAINE. "Local Health Information Networks Share Data." Internal Medicine News 38, no. 20 (October 2005): 72. http://dx.doi.org/10.1016/s1097-8690(05)72210-1.

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Kusiak, Andrew. "Renewables: Share data on wind energy." Nature 529, no. 7584 (January 2016): 19–21. http://dx.doi.org/10.1038/529019a.

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ZABLOCKI, ELAINE. "Local Health Networks Share Electronic Data." Family Practice News 35, no. 18 (September 2005): 81. http://dx.doi.org/10.1016/s0300-7073(05)71805-3.

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Glauser, W. "International alliance to share genomic data." Canadian Medical Association Journal 185, no. 12 (July 15, 2013): E561—E562. http://dx.doi.org/10.1503/cmaj.109-4532.

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Capua, I. "Veterinary Virologists Share Avian Flu Data." Science 312, no. 5780 (June 16, 2006): 1597b. http://dx.doi.org/10.1126/science.312.5780.1597b.

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Rasool, Qaisar, Jianzhong Li, George S. Oreku, and Ehsan Ullah Munir. "Fair-Share Replication in Data Grid." Information Technology Journal 7, no. 5 (June 15, 2008): 776–82. http://dx.doi.org/10.3923/itj.2008.776.782.

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Levenson, Deborah. "When should pediatric biobanks share data?" American Journal of Medical Genetics Part A 152A, no. 3 (March 2010): fm vii—fm viii. http://dx.doi.org/10.1002/ajmg.a.33287.

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Butler, Declan. "Agencies join forces to share data." Nature 446, no. 7134 (March 2007): 354. http://dx.doi.org/10.1038/446354b.

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Scutt, Polly, Lisa J. Woodhouse, Alan A. Montgomery, and Philip M. Bath. "Data sharing: experience of accessing individual patient data from completed randomised controlled trials in vascular and cognitive medicine." BMJ Open 10, no. 9 (September 2020): e038765. http://dx.doi.org/10.1136/bmjopen-2020-038765.

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ObjectivesMeta-analysis based on individual patient data (IPD) from randomised trials is superior to using published summary data since it facilitates subgroup and multiple variable analyses. Guidelines and funders expect that researchers share IPD for bona fide analyses, but in practice, this is done variably. Here, we report the experience of obtaining IPD for two collaborative analysis studies.SettingTwo linked studies required IPD from published randomised trials. The leading researchers for eligible trials were approached and asked to share IPD including trial characteristics, patient demographics, baseline clinical data and outcome measures.ParticipantsParticipants in eligible randomised controlled trials included patients with or at risk of cognitive decline/vascular events.Primary and secondary outcome measuresNumbers (%) of trials where the leading researcher responded favourably/negatively or did not respond. If negative, reasons behind the response were collected. If positive, methods used to share IPD were recorded.ResultsAcross the two studies, 391 completed trials were identified. Email addresses for researchers were found for 313 (80%) of the trials. One hundred and forty-eight (47%) researchers did not respond despite being sent multiple emails. Following contact, positive initial responses were received from 92 researchers, resulting in IPD being shared for 78 trials. Eighty-seven (28%) researchers declined to share data; justifications were recorded. The median time from first request to accessing data in one study was 241 (IQR 383.3) days. IPD sources included: direct from researcher, via academic trial funders repository and a website requiring remote analysis of commercial data. Where data were shared, a variety of methods were used to transfer data.ConclusionSharing of IPD from trials is desirable and a requirement of many funding bodies. However, accessing IPD faces multiple challenges including refusals to share, delays in access to data and having to perform analyses on a remote website.Trial registrationNot applicable.

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Scarfe, William C. "Data, data everywhere but not a byte to share…?" Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 119, no. 4 (April 2015): 370–73. http://dx.doi.org/10.1016/j.oooo.2014.12.021.

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Fox, Jeffrey L. "Rice data release signals industry willingness to share data." Nature Biotechnology 20, no. 5 (May 2002): 417–18. http://dx.doi.org/10.1038/nbt0502-417.

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Tetko, Igor V., Ruben Abagyan, and Tudor I. Oprea. "Surrogate data – a secure way to share corporate data." Journal of Computer-Aided Molecular Design 19, no. 9-10 (September 2005): 749–64. http://dx.doi.org/10.1007/s10822-005-9013-3.

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Hauser, Ronald G., Ankur Bhargava, Ronald Talmage, Mihaela Aslan, and John Concato. "Data Object Exchange (DOEx) as a Method to Facilitate Intraorganizational Collaboration by Managed Data Sharing: Viewpoint." JMIR Medical Informatics 8, no. 10 (October 27, 2020): e19267. http://dx.doi.org/10.2196/19267.

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Background To help reduce expenses, shorten timelines, and improve the quality of final deliverables, the Veterans Health Administration (VA) and other health care systems promote sharing of expertise among informatics user groups. Traditional barriers to time-efficient sharing of expertise include difficulties in finding potential collaborators and availability of a mechanism to share expertise. Objective We aim to describe how the VA shares expertise among its informatics groups by describing a custom-built tool, the Data Object Exchange (DOEx), along with statistics on its usage. Methods A centrally managed web application was developed in the VA to share informatics expertise using database objects. Visitors to the site can view a catalog of objects published by other informatics user groups. Requests for subscription and publication made through the site are routed to database administrators, who then actualize the resource requests through modifications of database object permissions. Results As of April 2019, the DOEx enabled the publication of 707 database objects to 1202 VA subscribers from 758 workgroups. Overall, over 10,000 requests are made each year regarding permissions on these shared database objects, involving diverse information. Common “flavors” of shared data include disease-specific study populations (eg, patients with asthma), common data definitions (eg, hemoglobin laboratory results), and results of complex analyses (eg, models of anticipated resource utilization). Shared database objects also enable construction of community-built data pipelines. Conclusions To increase the efficiency of informatics user groups, a method was developed to facilitate intraorganizational collaboration by managed data sharing. The advantages of this system include (1) reduced duplication of work (thereby reducing expenses and shortening timelines) and (2) higher quality of work based on simplifying the adoption of specialized knowledge among groups.

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Graham, Sophie, Laura McDonald, Radek Wasiak, Michael Lees, and Sreeram Ramagopalan. "Time to really share real-world data?" F1000Research 7 (July 11, 2018): 1054. http://dx.doi.org/10.12688/f1000research.15517.1.

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Data other than that from clinical trials are important for healthcare decision making. However, unlike the vocal calls seen for more open access to trial data, there are limited efforts being made to ensure that agencies that collect real-world data (RWD) share this, despite its importance. There are many RWD sources across the world that could be readily exploited for research once shared. There are policy and privacy questions that need to be tackled, but opening up and sharing RWD offers remarkable potential for improvements in care for individuals and more effective use of limited healthcare resources. Open science should become the standard for RWD as well as clinical trials, especially those that have a high likelihood to influence practice.

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Dixon, Dennis O., and Stephen W. Lagakos. "Should Data and Safety Monitoring Boards Share Confidential Interim Data?" Controlled Clinical Trials 21, no. 1 (February 2000): 1–6. http://dx.doi.org/10.1016/s0197-2456(99)00042-2.

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31

Chawla, Dalmeet Singh. "Data sharing: Web widget nudges scientists to share their data." Nature 532, no. 7597 (April 7, 2016): 136. http://dx.doi.org/10.1038/532136a.

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32

Kovaříček, P., and J. Hůla. "Field capacity determination from GPS spatial data." Research in Agricultural Engineering 49, No. 3 (February 8, 2012): 75–79. http://dx.doi.org/10.17221/4955-rae.

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For agricultural machinery management the actually reached machines capacity has a considerable importance. The data recorded by GPS monitoring enable to correct machines work productivity under concrete operational conditions. Assessment of machine aggregates operation records has proved effect of the operational factors onto operational efficiency reached on particular plots. The theoretical efficiency given by exploitation characteristics of machines has decreased effect of higher share of non-productive travels within small and irregular plots almost by 25%. In this paper we are dealing with searching for correlation between field speed and travelled unit path and defined classes of size, length and plot shape. The resulting knowledge of field efficiency on plots properties will enable to make more accurate the machines planned operation.

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Alaimi, Ali, Malathi Govind, and Mohanad Halaweh. "Exploring Personal Data Sensitivity." International Journal of Cyber Research and Education 3, no. 1 (January 2021): 28–38. http://dx.doi.org/10.4018/ijcre.2021010103.

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The aim of this exploratory research is to investigate people's perception of data sensitivity and their willingness to share such data. There has been little research within the UAE that identified the public/ordinary people's perspective of what is considered sensitive data and what is not, and which data can/not be shared with others such as social media applications, e-commerce websites, and friends. To achieve the aim of this research, empirical data was collected using a survey designed to evaluate the sensitivity of five categories of data types (personal, contact, online life, financial, and secure identifiers). The research findings revealed that the respondents tended to feel relatively low sensitivity to personal data, but they tended to feel a higher degree of sensitivity to financial-related data, and they are also not willing to share it. However, some personal data items like medical history records were largely deemed as not sensitive according to participants. This paper presents and discusses new insights and research implications based on findings from the UAE context.

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34

Cartwright, Eva. "Share data to ensure objectives are achieved." Primary Teacher Update 2014, no. 35 (August 2, 2014): 45. http://dx.doi.org/10.12968/prtu.2014.1.35.45.

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35

George, Christopher H., Stephen P. H. Alexander, Giuseppe Cirino, James R. Docherty, Daniel Hoyer, Paul A. Insel, Angelo A. Izzo, et al. "The BJP expects authors to share data." British Journal of Pharmacology 176, no. 24 (December 2019): 4595–98. http://dx.doi.org/10.1111/bph.14907.

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36

Butler, Declan. "Drug firm to share raw trial data." Nature 490, no. 7420 (October 2012): 322. http://dx.doi.org/10.1038/490322a.

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Hope, Joan. "Rely on data to set, share strategy." Student Affairs Today 21, no. 8 (October 19, 2018): 12. http://dx.doi.org/10.1002/say.30541.

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Hope, Joan. "Rely on data to set, share strategy." Enrollment Management Report 22, no. 6 (August 22, 2018): 12. http://dx.doi.org/10.1002/emt.30460.

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Lo, Bernard, and David L. DeMets. "Incentives for Clinical Trialists to Share Data." New England Journal of Medicine 375, no. 12 (September 22, 2016): 1112–15. http://dx.doi.org/10.1056/nejmp1608351.

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Millar, AP, P. Fuhrmann, T. Mkrtchyan, G. Behrmann, C. Bernardt, Q. Buchholz, V. Guelzow, et al. "dCache, Sync-and-Share for Big Data." Journal of Physics: Conference Series 664, no. 4 (December 23, 2015): 042038. http://dx.doi.org/10.1088/1742-6596/664/4/042038.

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41

Kromhout, Hans. "Should we share ideas or measurement data?" Occupational and Environmental Medicine 69, no. 6 (April 12, 2012): 375–76. http://dx.doi.org/10.1136/oemed-2011-100582.

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42

Squazzoni, Flaminio, Francisco Grimaldo, and Ana Marušić. "Publishing: Journals could share peer-review data." Nature 546, no. 7658 (June 2017): 352. http://dx.doi.org/10.1038/546352a.

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Poon, Kok-Siong, and Evelyn Siew-Chuan Koay. "Diagnostic genomic laboratories should share their data." Nature 594, no. 7862 (June 8, 2021): 177. http://dx.doi.org/10.1038/d41586-021-01523-9.

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Bezuidenhout, Louise. "To share or not to share: Incentivizing data sharing in life science communities." Developing World Bioethics 19, no. 1 (January 22, 2018): 18–24. http://dx.doi.org/10.1111/dewb.12183.

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Sall, Ousmane, Moussa Lo, Fabien Gandon, Cheikh Niang, and Ibrahima Diop. "Using XML data integration and ontology reuse to share agricultural data." International Journal of Metadata, Semantics and Ontologies 4, no. 1/2 (2009): 93. http://dx.doi.org/10.1504/ijmso.2009.026258.

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46

Halling, Frank, Andreas Neff, and Thomas Ziebart. "Local Anesthetic Usage Among Dentists: German and International Data." Anesthesia Progress 68, no. 1 (March 1, 2021): 19–25. http://dx.doi.org/10.2344/anpr-67-03-12.

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The aim of this study was to analyze the use of dental local anesthetics in Germany compared with international data. The type and distribution of dental local anesthetics and added vasoconstrictors based on a representative sample of German dentists itemized over a period of 7 years (2011 to 2017) were evaluated and statistically analyzed. The results were compared with international dental local anesthetic consumption data published since 2005. With a consistent market share of nearly 98%, articaine was the first-line local dental anesthetic agent in Germany. During the investigation period, German dental local anesthetics with epinephrine 1:200,000 had ∼50% market shares, whereas formulations with epinephrine 1:100,000 had 40% to 45% market shares. Articaine, with market shares between 38% and 81%, was also the preferred anesthetic agent in various other countries, with the notable exceptions of the United Kingdom and the United States, where lidocaine was the preferred local anesthetic agent. Epinephrine was the preferred vasoconstrictor internationally, similar to Germany. The larger market share of higher concentrated epinephrine 1:100,000 was remarkable, considering the increasing number of medically compromised patients. Increased consideration for using agents with reduced dosages of epinephrine (1:200,000) is generally recommended.

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Song, Jin Ling. "Separate Mapping and Application in Data Share for Network Manufacturing." Advanced Materials Research 201-203 (February 2011): 667–71. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.667.

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EXPRESS-to-XML mapping is an indispensable foundation in manufacturing network data transmission and share. Put forward and construct a networked manufacturing system with synergy based on the whole life manufacture cycle of the products and the manufacturing information share. Stress is on the mapping mechanism from the standard description language of STEP_NC——EXPRESS to XML，presenting the separate-mapping method with which according to the function and feature of the information to be transmitted and shared, the physical file of STEP_NC is divided into general information structure elements, feature information structure, and operating information structure, realizing the optimally comprehensive mapping with the early binding and the late binding. Build up STEP_XML conversion system. Example is given for component with a hole in running the separate mapping method on the STEP - NC Machine simulation platform. It has been shown that the conversion system and the separate-mapping method are practical and efficient.

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48

Trainer, James F. "To share and share alike: The basic ground rules for inter-institutional data sharing." New Directions for Institutional Research 1996, no. 89 (1996): 5–13. http://dx.doi.org/10.1002/ir.37019968903.

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49

Newmark, Gregory. "Rail’s Share of Airport Access: Examining the Data." Transportation Research Record: Journal of the Transportation Research Board 1662, no. 1 (January 1999): 74–81. http://dx.doi.org/10.3141/1662-09.

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Kailasnath, Purushothaman, and Phillip Dickey. "ISUIA-II: the need to share more data." Surgical Neurology 62, no. 2 (August 2004): 95. http://dx.doi.org/10.1016/j.surneu.2004.05.002.

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Journal articles on the topic 'Share data'

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