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- Creator:
- Samuel, Sara M, Wilson, Diane L, and Fleming, Emily K
- Description:
- The International Committee of Medical Journal Editors (ICMJE) requires researchers to post individual participant data (IPD) plans for interventional clinical trials with registration in order to be eligible for publication in its member journals. This study looked at how researchers interpret the ICMJE requirements and the related prompts for information used by ClinicalTrials.gov. This data consists of the analyzed contents of the IPD plans that researchers at the University of Michigan (U-M) submitted with trial registrations for the first 27 months that the 2019 requirement was in effect.
- Keyword:
- research data sharing, research data policy, research data, clinical trials, ClinicalTrials.gov, individual participant data, IPD, data sharing plan, and compliance
- Citation to related publication:
- Samuel, S. M. & Wilson, D. L. & Fleming, E., (2023) “Evaluating individual participant data plans for ICMJE compliance: A case study at University of Michigan”, Journal of the Society for Clinical Data Management 3(4). doi: https://doi.org/10.47912/jscdm.257
- Discipline:
- Health Sciences, Social Sciences, and General Information Sources
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- Creator:
- Foltynek, Tomas, Ruas, Terry, Scharpf, Philipp , Meuschke, Norman, Schubotz, Moritz , Grosky, William , and Gipp, Bela
- Description:
- This data set is comprised of multiple folders. The corpus folder contains raw text used for training and testing in two splits, "document" and "paragraph". The Spun documents and paragraphs are generated using the SpinBot tool ( https://spinbot.com/API). The paragraph split is generated by only selecting paragraphs with 3 or more sentences in the document split. Each folder is divided in mg (i.e., machine generated through SpinBot) and og (i.e., original generated file), The human judgement folder contains the human evaluation between original and spun documents (sample). It also contains the answers (keys) and survey results. , The models folder contains the machine learning classifier models for each word embedding technique used (only for document split training). The models were exported using pickle (Python 3.6). The grid search for hyperparameter adjustments is described in the paper. , and The vector folders (train and test) contains the average of all word vectors for each document and paragraph. Each line has the number of dimensions of the word embeddings technique used (see paper for more details) followed by its respective class (i.e, label mg or og). Each file belong to one class, either "mg" or "og". The values are comma-separated (.csv). The extension is .arff can be read as a normal .txt file.
- Keyword:
- paraphrase detection, plagiarism detection, document classification, and word embeddings
- Citation to related publication:
- Foltýnek, T. & Ruas, T. & Scharpf, P. & Meuschke, N. & Schubotz, M. & Grosky, W. & Gipp, B., “Detecting Machine-obfuscated Plagiarism,” in Sustainable Digital Communities, vol. 12051 LNCS, Springer, 2020, pp. 816–827. https://doi.org/10.1007/978-3-030-43687-2_68
- Discipline:
- General Information Sources
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- Creator:
- Mirshams Shahshahani, Payam
- Description:
- Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal. The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
- Keyword:
- minimum reaction time, sprinter, Olympics, Athletics, sex difference, starting block, and false start
- Citation to related publication:
- Mirshams Shahshahani P, Lipps DB, Galecki AT, Ashton-Miller JA (2018) On the apparent decrease in Olympic sprinter reaction times. PLoS ONE 13(6): e0198633. https://doi.org/10.1371/journal.pone.0198633
- Discipline:
- Engineering, Health Sciences, Science, Other, and General Information Sources
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- Creator:
- Xu, Xuecong, Yan, Xiang , and Dillahunt, Tawanna R.
- Description:
- We compared the response rates, cost, and the average income of participants pertaining to 6 different survey distribution methods used in an initial study about mobility-on-demand services. We used the data to identify survey and recruitment methods that are more effective in reaching hard-to-reach populations. All the raw data used for calculations and the calculations themselves can be found in the attached spreadsheets. and Initial analyses have identified in-person onsite recruitment as one of the better methods of reaching hard-to-reach populations, and is calling for continued work in improving research methods in the field of HCI.
- Keyword:
- survey
- Citation to related publication:
- Yan, X., Zhao, X., Han, Y., and Hentenryck, P. V. (2019). Mobility-on-demand versus fixed-route transit systems: an evaluation of traveler preferences in low-income communities. https://poverty.umich.edu/files/2019/02/Yan_et_al_WorkingPaper_Preference_for_mobility_on_demand.pdf , Atkinson, R., and Flint, J. Accessing Hidden and Hard-to-Reach Populations: Snowball Research Strategies. "Social Research Update" 33 (Jan 2001)., Buranyi, S. Rise of the racist robots: how ai is learning all our worst impulses, Aug 2017. Retrieved June 11, 2019 from https://www.theguardian.com/inequality/2017/aug/08/rise-of-the-racist-robots-how-ai-is-learning-all-our-worst-impulses., Dillahunt, T. R., Erete, S., Galusca, R., Israni, A., Nacu, D., and Sengers, P. Reflections on design methods for underserved communities. In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (New York, NY, USA, 2017), CSCW ’17 Companion, ACM, pp. 409–413., Erete, S., Israni, A., and Dillahunt, T. An intersectional approach to designing in the margins. Interactions 25, 3 (Apr. 2018), 66–69., Foster, A. Concerning issue with driverless cars, Mar 2019. Retrieved June 11, 2019 from https://www.news.com.au/technology/innovation/motoring/on-the-road/driverless-cars-may-be-more-likely-to-hit-darkskinned-people-study-finds/news-story/b19959d01ef865f15bb336275b8903e8., Johnston, L. G., and Sabin, K. Sampling hard-to-reach populations with respondent driven sampling. Methodological Innovations Online 5, 2 (aug 2010), 38.1–48., Macaulay, A. C., Commanda, L. E., Freeman, W. L., Gibson, N., McCabe, M. L., Robbins, C. M., and Twohig, P. L. Participatory research maximises community and lay involvement. BMJ 319, 7212 (sep 1999), 774–778., Maestre, J. F., Eikey, E. V., Warner, M., Yarosh, S., Pater, J., Jacobs, M., Marcu, G., and Shih, P. C. Conducting research with stigmatized populations: Practices, challenges, and lessons learned. In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing (2018), ACM, pp. 385–392., Paterson, J. M., and Maker, Y. Why does artificial intelligence discriminate?, Jun 2019. Retrieved June 11, 2019 from https://pursuit.unimelb.edu.au/articles/why-does-artificial-intelligence-discriminate., Strohmayer, A., Laing, M., and Comber, R. Technologies and social justice outcomes in sex work charities: fighting stigma, saving lives. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017), ACM, pp. 3352–3364., and Sydor, A. Conducting research into hidden or hard-to-reach populations. Nurse researcher 20, 3 (2013).
- Discipline:
- General Information Sources