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Journal articles on the topic 'Data with gaps'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

D, Mariette. "Unhealthful Data Gaps." Scientific American 320, no. 5 (2019): 4. http://dx.doi.org/10.1038/scientificamerican0519-4.

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2

Aldhous, Peter. "Gaps loom in satellite data." Nature 355, no. 6362 (1992): 662. http://dx.doi.org/10.1038/355662a0.

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3

Zielinski, Sarah. "Filling gaps in ecosystem data." Eos, Transactions American Geophysical Union 87, no. 26 (2006): 254. http://dx.doi.org/10.1029/2006eo260004.

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4

Pearman, Francis A., F. Chris Curran, Benjamin Fisher, and Joseph Gardella. "Are Achievement Gaps Related to Discipline Gaps? Evidence From National Data." AERA Open 5, no. 4 (2019): 233285841987544. http://dx.doi.org/10.1177/2332858419875440.

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There is growing interest in the relation between the racial achievement gap and the racial discipline gap. However, few studies have examined this relation at the national level. This study combines data from the Stanford Education Data Archive and the Civil Rights Data Collection and employs a district fixed effects analysis to examine whether and the extent to which racial discipline gaps are related to racial achievement gaps in Grades 3 through 8 in districts across the United States. In bivariate models, we find evidence that districts with larger racial discipline gaps have larger racia

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5

Marqués, José Manuel, Fernando Ávila, Anahí Rodríguez-Martínez, et al. "Policy report on FinTech data gaps." Latin American Journal of Central Banking 2, no. 3 (2021): 100037. http://dx.doi.org/10.1016/j.latcb.2021.100037.

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6

Shroff, Sangeeta. "Data Gaps in Agricultural Statistics:Some Issues." Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics 58, no. 3 (2016): 228. http://dx.doi.org/10.21648/arthavij/2016/v58/i3/147827.

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7

Cameron, Erin K., Inês S. Martins, Patrick Lavelle, et al. "Global gaps in soil biodiversity data." Nature Ecology & Evolution 2, no. 7 (2018): 1042–43. http://dx.doi.org/10.1038/s41559-018-0573-8.

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8

SCHNEIDER, MARY ELLEN. "Decoding Care Transitions Despite Data Gaps." Hospitalist News 5, no. 4 (2012): 3. http://dx.doi.org/10.1016/s1875-9122(12)70080-9.

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9

Gilbert, Natasha. "Data gaps threaten chemical safety law." Nature 475, no. 7355 (2011): 150–51. http://dx.doi.org/10.1038/475150a.

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10

Golbus, Jessica R., W. Nicholson Price, and Brahmajee K. Nallamothu. "Privacy Gaps for Digital Cardiology Data." Circulation 141, no. 8 (2020): 613–15. http://dx.doi.org/10.1161/circulationaha.119.044966.

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11

Patel, Paraskumar. "Overcoming Data Gaps in Sales Analysis." Journal of Marketing & Supply Chain Management 1, no. 3 (2022): 1–5. http://dx.doi.org/10.47363/jmscm/2022(1)139.

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In the rapidly evolving global marketplace, businesses face the critical challenge of navigating through extensive sales data to derive actionable insights. This paper explores the complexities of aligning and analyzing sales data from various third-party vendors across different geographies, highlighting the significant impact of data misalignment and gaps on strategic decision-making.

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12

Waller, John. "Finding Data Gaps in the GBIF Backbone Taxonomy." Biodiversity Information Science and Standards 6 (August 23, 2022): e91312. https://doi.org/10.3897/biss.6.91312.

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When publishers supply GBIF (Global Biodiversity Information Facility) with a dwc:scientificName, this name is sometimes <em>not</em> found in the GBIF taxonomic backbone. The backbone is needed to organize occurrences on GBIF. In these cases, the occurrence records get a data quality flag called taxon match higher rank. This means that GBIF was only able to match the name to a higher rank. Matching is a process whereby a name supplied by the publisher is compared to a name in the already existing in the GBIF backbone taxonomy. At GBIF, we would always like to match the name supplied by the pu

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13

Ariño, Arturo H. "On the Long Tails of Specimen Data." Biodiversity Information Science and Standards 7 (September 7, 2023): e112151. https://doi.org/10.3897/biss.7.112151.

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A recent article by K.R. Johnson and I.F.P. Owens in Science (Johnson and Owens 2023) suggested that the 73 main natural history museums around the world collectively hold over 1 billion records of accessioned "specimens" (taken as collection units), a result remarkably close to, but obtained through a completely different method from, research published a decade earlier by A.H. Ariño in Biodiversity Informatics (Ariño 2010). Both sets of approaches have benefitted from information available at the Global Biodiversity Information Facility (GBIF), which in the intervening years has grown by an

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14

Hoh, Daphne, Jun-Yi Wu, and Mao-Ning Tuanmu. "Utilizing a Dashboard for Efficient Biodiversity Data Overview and Gap-Filling Effort." Biodiversity Information Science and Standards 8 (August 26, 2024): e135531. https://doi.org/10.3897/biss.8.135531.

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Taiwan Biodiversity Information Facility has been leading the effort to integrate and mobilize biodiversity data nationally. We recently accomplished the integration of local databases and successfully developed a data portal that efficiently links to the most comprehensive biodiversity database in Taiwan: the Taiwan Biodiversity Information Alliance Data Portal. However, we identified an emerging challenge following this development. Preliminary analyses have revealed several gaps in the current dataset, impeding robust data use. For instance, land data dominates over sea data, and bird recor

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15

Hendrickson, Ole. "Old-growth forests: Data gaps and challenges." Forestry Chronicle 79, no. 3 (2003): 645–51. http://dx.doi.org/10.5558/tfc79645-3.

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How much old growth is there? How much was there? Is remaining old growth disappearing? If so, how fast and why? Is any more old growth being created? How fragmented are old-growth forests? What other forest types and land uses surround them? Scientists see these as challenging questions, never to be fully resolved. Policy makers see information gaps and want answers. They assume that because the public values old-growth forests, their continuing availability must be assured. Forest managers need to be convinced that old-growth forests provide unique values before taking costly measures to con

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16

Chiarello, Filippo, Elena Coli, Vito Giordano, Gualtiero Fantoni, and Andrea Bonaccorsi. "DATA FOR ENGINEERING DESIGN: MAPS AND GAPS." Proceedings of the Design Society 1 (July 27, 2021): 821–30. http://dx.doi.org/10.1017/pds.2021.82.

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AbstractData, information and knowledge are strongly involved in Engineering Design (ED) process. Despite the crucial role played by data in the design process, there is a lack of studies about how different data are used and generated by the various phases of the ED process. This study is a first attempt to fill this gap by mapping which data types are involved in the different ED phases from a research perspective.In order to achieve this objective, we used a methodology based on Text Mining. Firstly, we retrieve a corpus of scientific papers related to ED; then, we build two lexicons to rec

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17

Dou, Zhengxiong, and Xiaonan Wang. "Data delivery in VANET with network gaps." Journal of High Speed Networks 26, no. 2 (2020): 111–24. http://dx.doi.org/10.3233/jhs-200633.

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18

Miglani, Varun. "Data Gaps on Contract Farming in India." Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics 58, no. 3 (2016): 261. http://dx.doi.org/10.21648/arthavij/2016/v58/i3/147832.

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19

Cooksey, Catherine, and Raju Datla. "Workshop on Bridging Satellite Climate Data Gaps." Journal of Research of the National Institute of Standards and Technology 116, no. 1 (2011): 505. http://dx.doi.org/10.6028/jres.116.002.

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20

McDonald, Judith A., and Robert J. Thornton. "Estimating gender wage gaps: A data update." Journal of Economic Education 47, no. 2 (2016): 140–41. http://dx.doi.org/10.1080/00220485.2016.1146100.

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21

&NA;, &NA;. "ANA, NCSDN MOVE TO MEND DATA GAPS." AJN, American Journal of Nursing 93, no. 3 (1993): 97. http://dx.doi.org/10.1097/00000446-199303000-00032.

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22

Gupta, Shruti, Radha Malani, and Anoop Singh. "Subsidies in India: Bridging the Data Gaps." Indian Public Policy Review 5, no. 5 (Sep-Oct) (2024): 1–50. http://dx.doi.org/10.55763/ippr.2024.05.05.001.

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This paper looks at reported subsidy spending in India, in light of ongoing central initiatives to build transparency and accessibility of information related to financial operations and decisions of public expenditure. Subsidies have become a prominent policy tool for public resource allocation in India. However, without a clear definition and reporting of ‘subsidy’, the term tends to be loosely used to encompass many schemes and programs of the Union and state governments, including the recent rise in ‘freebies’, which need to be clearly differentiated. Moreover, many forms of financing thro

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23

Betts, Kellyn S. "First U.S. ecosystems analysis reveals data gaps." Environmental Science & Technology 36, no. 21 (2002): 404A. http://dx.doi.org/10.1021/es022451k.

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24

Cooney, Catherine M. "Data gaps limit success of national indicators." Environmental Science & Technology 37, no. 21 (2003): 382A—383A. http://dx.doi.org/10.1021/es0326219.

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25

Peebles, Laura, and Beverley Norris. "Filling ‘gaps’ in strength data for design." Applied Ergonomics 34, no. 1 (2003): 73–88. http://dx.doi.org/10.1016/s0003-6870(02)00073-x.

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26

de Sousa, Rita, Chantal Reusken, and Marion Koopmans. "MERS coronavirus: Data gaps for laboratory preparedness." Journal of Clinical Virology 59, no. 1 (2014): 4–11. http://dx.doi.org/10.1016/j.jcv.2013.10.030.

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27

Micha, Renata, Jennifer Coates, Catherine Leclercq, U. Ruth Charrondiere, and Dariush Mozaffarian. "Global Dietary Surveillance: Data Gaps and Challenges." Food and Nutrition Bulletin 39, no. 2 (2018): 175–205. http://dx.doi.org/10.1177/0379572117752986.

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Background: Detailed information on global individual-level consumption patterns is imperative for informed policy making. However, such data are dispersed and incomplete. Objective: To review and discuss the methodologies, observed data availability, challenges, and opportunities pertaining to global dietary surveillance. Methods: This investigation provides an extensive review of global dietary assessment methodologies and challenges, including at the survey level, the dietary collection and assessment level, and the dietary data processing and analysis level. The focus is on nationally repr

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28

Barbedo, Jayme Garcia Arnal. "Data Fusion in Agriculture: Resolving Ambiguities and Closing Data Gaps." Sensors 22, no. 6 (2022): 2285. http://dx.doi.org/10.3390/s22062285.

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Acquiring useful data from agricultural areas has always been somewhat of a challenge, as these are often expansive, remote, and vulnerable to weather events. Despite these challenges, as technologies evolve and prices drop, a surge of new data are being collected. Although a wealth of data are being collected at different scales (i.e., proximal, aerial, satellite, ancillary data), this has been geographically unequal, causing certain areas to be virtually devoid of useful data to help face their specific challenges. However, even in areas with available resources and good infrastructure, data

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29

Giest, Sarah, and Annemarie Samuels. "‘For good measure’: data gaps in a big data world." Policy Sciences 53, no. 3 (2020): 559–69. http://dx.doi.org/10.1007/s11077-020-09384-1.

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30

Recker, Jonas, and Anja Perry. "Data on the Margins – Data from LGBTIQ+ Populations in European Social Science Data Archives." Data Science Journal 23 (July 23, 2024): 39. http://dx.doi.org/10.5334/dsj-2024-039.

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Data gaps are a significant lack of data about marginalized groups existing due to unequal power relations (D’Ignazio and Klein, 2020). They both perpetuate and result in a dominance of male, white, hetero, and cis perspectives in how we make sense of and interact with the world. The most prominent data gap is the gender data gap notably described by Criado-Perez (2020). However, not only women, but all marginalized groups are affected by such gaps, as data about them are frequently not collected due to a disregard on behalf of those in power of the need to do so. LGBTIQ+ people, considered a

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31

See, Craig R., Mark B. Green, Ruth D. Yanai, Amey S. Bailey, John L. Campbell, and Jeremy Hayward. "Quantifying uncertainty in annual runoff due to missing data." PeerJ 8 (July 21, 2020): e9531. http://dx.doi.org/10.7717/peerj.9531.

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Long-term streamflow datasets inevitably include gaps, which must be filled to allow estimates of runoff and ultimately catchment water budgets. Uncertainty introduced by filling gaps in discharge records is rarely, if ever, reported. We characterized the uncertainty due to streamflow gaps in a reference watershed at the Hubbard Brook Experimental Forest (HBEF) from 1996 to 2009 by simulating artificial gaps of varying duration and flow rate, with the objective of quantifying their contribution to uncertainty in annual streamflow. Gaps were filled using an ensemble of regressions relating disc

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32

Canhos, Dora Ann Lange. "Data Management Plan: Brazil's Virtual Herbarium." Research Ideas and Outcomes 3 (June 27, 2017): e14675. https://doi.org/10.3897/rio.3.e14675.

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The goal of the Brazil Virtual Herbarium is to facilitate the identification of taxonomic and geographic information gaps of plants and fungi of Brazil. The system displays the status of online data for all valid species in the List of Species of the Brazilian Flora, including those without any record. The system also compares the Brazilian states where specialists indicate that the species occurs with the states that have occurrence points in Brazil's Virtual Herbarium, highlighting the gaps. This data management plan was prepared as part of a pilot project run on behalf of the International

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33

Durkin, Allison, Brandon Willmore, Caroline Nobo Sarnoff, and David Hemenway. "The Firearms Data Gap." Journal of Law, Medicine & Ethics 48, S4 (2020): 32–38. http://dx.doi.org/10.1177/1073110520979399.

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The firearms data infrastructure in the United States is severely limited in scope and fragmented in nature. Improved data systems are needed in order to address gun violence and promote productive conversation about gun policy. In the absence of federal leadership in firearms data systems improvement, motivated states may take proactive steps to stitch gaps in data systems. We propose that states evaluate the gaps in their systems, expand data collection, and improve data presentation and availability.

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34

Shovin, V. A. "Factor analysis for restoring data gaps of hypertension." Mathematical structures and modeling, no. 1 (2019): 65–72. http://dx.doi.org/10.24147/2222-8772.2019.1.65-72.

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An algorithm for filling data gaps on the basis of restoring the vector of object indices from the factorial data structure, calculated with penalty method, is developed. Data gaps and the corresponding factor model equations for individual objects were not taken into account in the optimization criterion for residuals of the factor model equations. That allows to reliably estimate the values of data gaps. A numerical experiment confirming the operability of the algorithm is carried out and a program with an interface that allows the user to upload new data is created.

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35

Kang, Minseok, Kazuhito Ichii, Joon Kim, et al. "New Gap-Filling Strategies for Long-Period Flux Data Gaps Using a Data-Driven Approach." Atmosphere 10, no. 10 (2019): 568. http://dx.doi.org/10.3390/atmos10100568.

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In the Korea Flux Monitoring Network, Haenam Farmland has the longest record of carbon/water/energy flux measurements produced using the eddy covariance (EC) technique. Unfortunately, there are long gaps (i.e., gaps longer than 30 days), particularly in 2007 and 2014, which hinder attempts to analyze these decade-long time-series data. The open source and standardized gap-filling methods are impractical for such long gaps. The data-driven approach using machine learning and remote-sensing or reanalysis data (i.e., interpolating/extrapolating EC measurements via available networks temporally/sp

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36

Ahn, Hyerim. "The Effect of Data Gap on the Organizational Learning based on Data: Focusing on the Exploration and Exploitation Process." Korean Academy of Management 33, no. 1 (2025): 55–81. https://doi.org/10.26856/kjom.2025.33.1.55.

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In the age of datafication, organizations have access to more information than ever before and increasingly rely on data to make decisions. However, few approaches analyze the impact of data gaps on organizational performance, specifically focusing on the data gaps that may arise due to differences of connectivity among organizations and individuals. In this study, I modeled data gaps -instances where a dataset is missing a specific element or social group- in two ways: (1) when an organization's ability to provide connectivity is limited, resulting in missing data needed to measure the intend

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37

Al-Allaf, Muhammad Youns, Muzahim Saeed Al-Bek, and Muhannad Abdel-Qader. "Determine Canopy Gaps for Atrush Forest using Remote Sensing Data." IOP Conference Series: Earth and Environmental Science 1213, no. 1 (2023): 012114. http://dx.doi.org/10.1088/1755-1315/1213/1/012114.

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Abstract It is known that the gaps in the forests have a significant impact on the natural regeneration of the forest, so these gaps were studied by relying on remote sensitivity data (Quick Bird) with a precision of discrimination (2.44 m) spectral and (0.61 m) panoramic The statement was classified non-directed by the computer program (Erdas 9.2) for its suitability for the study area of a mountain nature, the study area was classified into (empty spaces (gaps), roads, forest lands), the study area reached (126.182) hectares, the area of the gaps inside the forest (68%), while the roads were

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38

Machado, Alexandre M. S., Eduardo L. Hettwer Giehl, Luiza Pacheco Fernandes, Simon N. Ingram, and Fábio G. Daura-Jorge. "Alternative data sources can fill the gaps in data-poor fisheries." ICES Journal of Marine Science 78, no. 5 (2021): 1663–71. http://dx.doi.org/10.1093/icesjms/fsab074.

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Abstract Assessing fish stocks harvested by small-scale fisheries is challenging. The lack of official fisheries data constrains the proper management of such fisheries. Thus, alternative sources of information are crucial to enrich data-poor fisheries. Here, we evaluated different sources of data for the mullet (Mugil liza) fishery, one of the most important but overexploited fisheries in Brazil. We gathered three alternative sources of catch data by artisanal fisheries: 14 years of self-reported catches by artisanal fishers across 24 municipalities; 16 years of catches by traditional beach s

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39

Lompar, Miloš, Branislava Lalić, Ljiljana Dekić, and Mina Petrić. "Filling Gaps in Hourly Air Temperature Data Using Debiased ERA5 Data." Atmosphere 10, no. 1 (2019): 13. http://dx.doi.org/10.3390/atmos10010013.

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Missing data in hourly and daily temperature data series is a common problem in long-term data series and many observational networks. Agricultural and environmental models and climate-related tools can be used only if weather data series are complete. To support user communities, a technique for gap filling is developed based on the debiasing of ERA5 reanalysis data, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of the global climate. The debiasing procedure includes in situ measured temperature. The methodology is tested for dif

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40

Popper, Arthur N. "Man-made noise and aquatic Life: data, data gaps, and speculation." Journal of the Acoustical Society of America 137, no. 4 (2015): 2245. http://dx.doi.org/10.1121/1.4920191.

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41

Galea, Sandro, and Salma M. Abdalla. "Data to Improve Global Health Equity—Key Challenges." JAMA Health Forum 4, no. 11 (2023): e234433. http://dx.doi.org/10.1001/jamahealthforum.2023.4433.

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42

Candelas, G., L. Silva-Fernández, M. Montoro, et al. "FRI0071 ANALYSIS OF DATA GAPS IN RHEUMATOID ARTHRITIS." Annals of the Rheumatic Diseases 79, Suppl 1 (2020): 612.2–612. http://dx.doi.org/10.1136/annrheumdis-2020-eular.6574.

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Background:Although ideally Recommendations for the management of rheumatoid arthritis (RA) should be supported by the highest level of evidence, many of which are based on “expert opinion”. This means that there are knowledge gaps to which a part of the research efforts in this disease should be directed.Objectives:1.- Analyze the causes of the low level of evidence in some of the recommendations on diagnosis and management of RA in the main published documents2.- Identify the knowledge gaps that justify said low level of evidence3.- Design actions to respond to the knowledge gaps identified.

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43

Poisot, Timothée, Gabriel Bergeron, Kevin Cazelles, et al. "Global knowledge gaps in species interaction networks data." Journal of Biogeography 48, no. 7 (2021): 1552–63. http://dx.doi.org/10.1111/jbi.14127.

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44

Howe, David A., and Noah Schlossberger. "Characterizing Frequency Stability Measurements Having Multiple Data Gaps." IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 69, no. 2 (2022): 468–72. http://dx.doi.org/10.1109/tuffc.2021.3137425.

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45

Etard, Adrienne, Sophie Morrill, and Tim Newbold. "Global gaps in trait data for terrestrial vertebrates." Global Ecology and Biogeography 29, no. 12 (2020): 2143–58. http://dx.doi.org/10.1111/geb.13184.

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46

Newquist, Deborah D., Marguerite DeLiema, and Kathleen H. Wilber. "Beware of Data Gaps in Home Care Research." Medical Care Research and Review 72, no. 5 (2015): 622–40. http://dx.doi.org/10.1177/1077558715588437.

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47

Tymkiv, Mariia, and Dmytro Kasiyanchuk. "Research of Data Sequencesof Groundwater Levels with Gaps." Journal of Ecological Engineering 20, no. 3 (2019): 141–51. http://dx.doi.org/10.12911/22998993/99744.

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48

Grainger, A. "Measuring the planet to fill terrestrial data gaps." Proceedings of the National Academy of Sciences 106, no. 49 (2009): 20557–58. http://dx.doi.org/10.1073/pnas.0912298107.

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49

Nelson, Andy. "Crop-health survey aims to fill data gaps." Nature 541, no. 7638 (2017): 464. http://dx.doi.org/10.1038/541464a.

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50

Tollefson, Jeff. "Satellite images reveal gaps in global population data." Nature 545, no. 7653 (2017): 141–42. http://dx.doi.org/10.1038/545141a.

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