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1. The Need for a Recurring Large-Scale Benchmarking Survey to Continually Evaluate Sampling Methods and Administration Modes: Lessons from the 2022 Collaborative Midterm Survey

Author

Enns, Peter K., Barry, Colleen L., Druckman, James N., Garcia-Rios, Sergio, Wilson, David C., and Schuldt, Jonathon P.

Subjects
Statistics - Other Statistics
Abstract

As survey methods adapt to technological and societal changes, a growing body of research seeks to understand the tradeoffs associated with various sampling methods and administration modes. We show how the NSF-funded 2022 Collaborative Midterm Survey (CMS) can be used as a dynamic and transparent framework for evaluating which sampling approaches - or combination of approaches - are best suited for various research goals. The CMS is ideally suited for this purpose because it includes almost 20,000 respondents interviewed using two administration modes (phone and online) and data drawn from random digit dialing, random address-based sampling, a probability-based panel, two nonprobability panels, and two nonprobability marketplaces. The analysis considers three types of population benchmarks (election data, administrative records, and large government surveys) and focuses on the national-level estimates as well as oversamples in three states (California, Florida, and Wisconsin). In addition to documenting how each of the survey strategies performed, we develop a strategy to assess how different combinations of approaches compare to different population benchmarks in order to guide researchers combining sampling methods and sources. We conclude by providing specific recommendations to public opinion and election survey researchers and demonstrating how our approach could be applied to a large government survey conducted at regular intervals to provide ongoing guidance to researchers, government, businesses, and nonprofits regarding the most appropriate survey sampling and administration methods.

Published
2024

2. STEP-CD study: ustekinumab use in paediatric Crohn’s disease—a multicentre retrospective study from paediatric IBD Porto group of ESPGHAN

Author

Pujol-Muncunill, Gemma, Navas-López, Víctor Manuel, Ledder, Oren, Cohen, Shlomi, Lekar, Marina, Turner, Dan, Kolho, Kaija-Leena, Levine, Arie, Croft, Nicholas M., Bronsky, Jiri, Shouval, Dror S., Assa, Amit, Harris, Rachel, Kiparissi, Fevronia, Aloi, Marina, Afzal, Nadeem Ahmad, Tzivinikos, Christos, Barrio, Josefa, Norden, Christoph, Vega, Maria Jesús Balboa, Buderus, Stephan, de Valderrama, Ana Fernández, de Ridder, Lissy, García-Romero, Ruth, Medina, Enrique, Sánchez, César, Velasco, Marta, Vicente, Saioa, Wilson, David C., Naik, Sandhia, Hradsky, Ondrej, Cococcioni, Lucia, and Martin-de-Carpi, Javier

Published
2024
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3. “Stop the Steal”: Racial Resentment, Affective Partisanship, and Investigating the January 6th Insurrection

Author

Davis, Darren W and Wilson, David C

Subjects
Political Science, Human Society, January 6th, Select Committee, racial resentment, affective partisanship, political polarization, insurrection, racial prejudice, General Arts, Humanities & Social Sciences
Abstract

Our analysis of data from a nationally representative survey of adults shows that beliefs in whether the January 6th insurrection was justifiable and whether it required investigation through the creation of the U.S. House Select Committee are inexorably steeped in affective partisanship and racial resentment. It is easy to attribute the insurrection to partisan machinations, but evidence shows that racial resentment is the dominant explanation: this includes the fact that allegations of election fraud were centered on districts with large African American and Latino populations; that many of the insurrectionists were white nationalists, racists, and members of radical right-wing groups; and that a large proportion of the electorate had voted to retain a president who fueled whites’ sense of victimization by African Americans and other minorities. We argue that reactions to the legitimacy of the January 6th insurrection have become an example of how racial resentment fuels affective partisanship.

Published
2023

4. Precision medicine in monogenic inflammatory bowel disease: proposed mIBD REPORT standards

Author

Uhlig, Holm H., Booth, Claire, Cho, Judy, Dubinsky, Marla, Griffiths, Anne M., Grimbacher, Bodo, Hambleton, Sophie, Huang, Ying, Jones, Kelsey, Kammermeier, Jochen, Kanegane, Hirokazu, Koletzko, Sibylle, Kotlarz, Daniel, Klein, Christoph, Lenardo, Michael J., Lo, Bernice, McGovern, Dermot P. B., Özen, Ahmet, de Ridder, Lissy, Ruemmele, Frank, Shouval, Dror S., Snapper, Scott B., Travis, Simon P., Turner, Dan, Wilson, David C., and Muise, Aleixo M.

Published
2023
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5. Race & Political Trust: Justice as a Unifying Influence on Political Trust

Author

Wu, Cary, Wilkes, Rima, and Wilson, David C

Subjects
Peace, Justice and Strong Institutions, Studies in Creative Arts and Writing, History and Archaeology, General Arts, Humanities & Social Sciences
Abstract

Abstract Americans’ trust in government is lower than ever. However, while all groups have seen a decline in trust since the 1960s, the gap in trust between racial and ethnic minorities and Whites in this period has varied not only in size but also in direction. At times, racial and ethnic minorities have actually had higher rates of trust than Whites, contradicting the broad assumptions in research about race and political trust. Explanations of the causes of trust in government that emphasize institutional experience and early socialization would not predict this outcome. We propose that an underutilized component in the study of race and political trust is perceived justice. On one hand, racial and ethnic minorities’ sensitivity to institutional injustice often leads to lower rates of trust. On the other hand, when racial and ethnic minorities perceive there are greater opportunities for racial progress, which signal that widespread harm can be repaired, their political trust tends to increase, sometimes to levels that exceed those for Whites. The interplay between political realities that shape perceived justice as well as political hope for racial progress likely creates the variable longitudinal patterns of racial and ethnic differences in trust.

Published
2022

6. Media Use, Interpersonal Communication, and Attitudes Toward Artificial Intelligence

Author

Brewer, Paul R, Bingaman, James, Paintsil, Ashley, Wilson, David C, and Dawson, Wyatt

Subjects
artificial intelligence, framing, interpersonal communication, news media, public opinion, science fiction, Business and Management, Communication and Media Studies, Science Studies
Abstract

This study examines how members of the public frame artificial intelligence (AI) along with how news use predicts “frames in mind” for AI. The study also tests whether news use, science fiction viewing, and discussing technology influence attitudes toward AI independently and in conjunction with one another. The analyses use data from a nationally representative online panel survey. Respondents invoked social progress and Pandora’s box frames for AI, and technology news use predicted mentioning each frame. Use of technology news also predicted change in support for AI, while science fiction viewing and discussing technology were conditionally related to such change.

Published
2022

7. The Prospect of Antiracism

Author

Davis, Darren W and Wilson, David C

Subjects
Behavioral and Social Science, Marketing, Political Science, Communication and Media Studies, Political Science & Public Administration
Abstract

Abstract Racial reckoning in response to racial injustice has compelled individuals, organizations, and institutions to acknowledge and adopt policies that actively challenge racial injustice. A central tenet of this era of reckoning is that it is no longer acceptable to ignore racist behaviors and expressions. To the extent that active opposition to racial prejudice is an effective strategy for individuals to pursue, we examine individual inclinations to act on matters of racial prejudice. We argue that in spite of best intentions, the motivation to act against racism, what we call “antiracism action orientation,” can be disrupted by system-justifying beliefs that raise questions about deservingness, legitimize the status quo, and therefore defend inaction. Survey data from the 2020 Congressional Election Study show that antiracism action orientation is strongest among African Americans, and those with more positive affect toward racial-ethnic minorities, and supporters of change. Among Whites, racial resentment dominates the motivations for antiracism to the point that typical political allies like Democrats, liberals, and those who acknowledge White privilege reduce their antiracism action orientation to lower levels than Republicans, conservatives, and deniers of White privilege. We conclude that most Americans, but especially Whites, have a high bar for change, making racism an ongoing American dilemma because of both racial attitudes and the costs of change.

Published
2022

11. “Siri, Show Me Scary Images of AI”: Effects of Text-Based Frames and Visuals on Support for Artificial Intelligence

Author

Bingaman, James, Brewer, Paul R, Paintsil, Ashley, and Wilson, David C

Subjects
Business and Management, Communication and Media Studies, Science Studies
Abstract

This research note examines how framing influences attitudes toward artificial intelligence (AI). It uses an experiment embedded in a nationally representative online survey to test the effects of text-based frames and visuals on opinion about developing, funding, and banning AI. Participants exposed to a “social progress” frame reported greater support for AI than those exposed to a “Pandora’s box” frame. Images (virtual assistants, personal robots, menacing movie AIs, or none) did not influence opinion by themselves but interacted with textual frames to do so. The results extend our understanding of framing effects on public attitudes toward emerging technologies.

Published
2021

12. HLA-DP on Epithelial Cells Enables Tissue Damage by NKp44+ Natural Killer Cells in Ulcerative Colitis

Author

Akar, Alaa, Flemming, Cornelius, Felix, Flomm, Flosbach, Markus, Jäger, Julia, Jeromin, Niklas, Jung, Johannes, Ohms, Mareike, Reinshagen, Konrad, Rische, Johann, Sagebiel, Adrian, Sandfort, Deborah, Steinert, Fenja, Tomuschat, Christian, Wesche, Jasmin, Shifteh Abedian, Abraham, Clara, Achkar, Jean-Paul, Ahmad, Tariq, Alberts, Rudi, Alizadeh, Behrooz, Amininejad, Leila, Ananthakrishnan, Ashwin N., Andersen, Vibeke, Anderson, Carl A., Andrews, Jane M., Annese, Vito, Aumais, Guy, Baidoo, Leonard, Baldassano, Robert N., Bampton, Peter A., Barclay, Murray, Barrett, Jeffrey C., Bethge, Johannes, Bewshea, Claire, Bis, Joshua C., Bitton, Alain, BK, Thelma, Boucher, Gabrielle, Brain, Oliver, Brand, Stephan, Brant, Steven R., Cheon, Jae Hee, Chew, Angela, Cho, Judy H., Cleynen, Isabelle, Cohain, Ariella, Cooney, Rachel, Croft, Anthony, Daly, Mark J., D'Amato, Mauro, Danese, Silvio, Daryani, Naser Ebrahim, Datta, Lisa Wu, Degenhardt, Frauke, Denapiene, Goda, Denson, Lee A., Devaney, Kathy L., Dewit, Olivier, D'Inca, Renata, Drummond, Hazel E., Dubinsky, Marla, Duerr, Richard H., Edwards, Cathryn, Ellinghaus, David, Ellul, Pierre, Esaki, Motohiro, Essers, Jonah, Ferguson, Lynnette R., Festen, Eleonora A., Fleshner, Philip, Florin, Tim, Franchimont, Denis, Franke, Andre, Fuyuno, Yuta, Gearry, Richard, Georges, Michel, Gieger, Christian, Glas, Jürgen, Goyette, Philippe, Green, Todd, Griffiths, Anne M., Guthery, Stephen L., Hakonarson, Hakon, Halfvarson, Jonas, Hanigan, Katherine, Haritunians, Talin, Hart, Ailsa, Hawkey, Chris, Hayward, Nicholas K., Hedl, Matija, Henderson, Paul, Hold, Georgina L., Hong, Myhunghee, Hu, Xinli, Huang, Hailiang, Hugot, Jean-Pierre, Hui, Ken Y., Imielinski, Marcin, Jazayeri, Omid, Jonaitis, Laimas, Jostins, Luke, Juyal, Garima, Chandra Juyal, Ramesh, Kalla, Rahul, Karlsen, Tom H., Kennedy, Nicholas A., Khan, Mohammed Azam, Kim, Won Ho, Kitazono, Takanari, Kiudelis, Gediminas, Kubo, Michiaki, Kugathasan, Subra, Kupcinskas, Limas, Lamb, Christopher A., de Lange, Katrina M., Latiano, Anna, Laukens, Debby, Lawrance, Ian C., Lee, James C., Lees, Charlie W., Leja, Marcis, Lewis, Nina, Van Limbergen, Johan, Lionetti, Paolo, Liu, Jimmy Z., Louis, Edouard, Luo, Yang, Mahy, Gillian, Malekzadeh, Masoud Mohammad, Malekzadeh, Reza, Mansfield, John, Marriott, Suzie, Massey, Dunecan, Mathew, Christopher G., Matsui, Toshiyuki, McGovern, Dermot P.B., van der Meulen, Andrea, Midha, Vandana, Milgrom, Raquel, Mirzaei, Samaneh, Mitrovic, Mitja, Montgomery, Grant W., Mowat, Craig, Müller, Christoph, Newman, William G., Ng, Aylwin, Ng, Siew C., Evelyn Ng, Sok Meng, Nikolaus, Susanna, Ning, Kaida, Nöthen, Markus, Oikonomou, Ioannis, Okou, David, Orchard, Timothy R., Palmieri, Orazio, Parkes, Miles, Phillips, Anne, Ponsioen, Cyriel Y., Potocnik, Urõs, Poustchi, Hossein, Prescott, Natalie J., Proctor, Deborah D., Radford-Smith, Graham, Rahier, Jean- Francois, Regueiro, Miguel, Reinisch, Walter, Rieder, Florian, Rioux, John D., Roberts, Rebecca, Rogler, Gerhard, Russell, Richard K., Sanderson, Jeremy D., Sans, Miquel, Satsangi, Jack, Schadt, Eric E., Scharl, Michael, Schembri, John, Schreiber, Stefan, Schumm, L. Philip, Scott, Regan, Seielstad, Mark, Shah, Tejas, Sharma, Yashoda, Silverberg, Mark S., Simmons, Alison, Simms, Lisa A., Singh, Abhey, Skieceviciene, Jurgita, van Sommeren, Suzanne, Song, Kyuyoung, Sood, Ajit, Spain, Sarah L., Steinhart, A. Hillary, Stempak, Joanne M., Stronati, Laura, Sung, Joseph J.Y., Targan, Stephan R., Taylor, Kirstin M., Theatre, Emilie, Torkvist, Leif, Torres, Esther A., Tremelling, Mark, Uhlig, Holm H., Umeno, Junji, Vahedi, Homayon, Vasiliauskas, Eric, Velde, Anje ter, Ventham, Nicholas T., Vermeire, Severine, Verspaget, Hein W., De Vos, Martine, Walters, Thomas, Wang, Kai, Wang, Ming-Hsi, Weersma, Rinse K., Wei, Zhi, Whiteman, David, Wijmenga, Cisca, Wilson, David C., Winkelmann, Juliane, Wong, Sunny H., Xavier, Ramnik J., Yamazaki, Keiko, Yang, Suk-Kyun, Ye, Byong Duk, Zeissig, Sebastian, Zhang, Bin, Zhang, Clarence K., Zhang, Hu, Zhang, Wei, Zhao, Hongyu, Zhao, Zhen Z., Baumdick, Martin E., Niehrs, Annika, Schwerk, Maria, Hinrichs, Ole, Jordan-Paiz, Ana, Padoan, Benedetta, Wegner, Lucy H.M., Schloer, Sebastian, Zecher, Britta F., Malsy, Jakob, Joshi, Vinita R., Illig, Christin, Schröder-Schwarz, Jennifer, Möller, Kimberly J., Martin, Maureen P., Yuki, Yuko, Ozawa, Mikki, Sauter, Jürgen, Schmidt, Alexander H., Perez, Daniel, Giannou, Anastasios D., Carrington, Mary, Davis, Randall S., Schumacher, Udo, Sauter, Guido, Huber, Samuel, Puelles, Victor G., Melling, Nathaniel, Altfeld, Marcus, and Bunders, Madeleine J.

Published
2023
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15. Justice: The Racial Motive We All Have and Need

Author

Wilson, David C

Subjects
Peace, Justice and Strong Institutions, Reduced Inequalities
Abstract

AbstractThis essay posits that justice is the core value epitomizing our moment. Justice is violated when positive outcomes are undeserved, and the felt sense of injustice motivates a need for retribution. Because politics involves allocation (distribution and redistribution), deservingness is a core appraisal of “who gets what” and therefore justice is fundamental for politics. This is especially germane to race, ethnicity, and politics scholars. I present a few core tenets of justice theory, and argue that political science can take advantage of the moment to engage the concept of justice; especially as it relates to the study of racial attitudes and the identification of racial enablers—those ostensible non-racists who facilitate the status quo. Summarily, I propose that justice can unify debates over prejudice and politics, and advance our scholarly understanding of how well-intentioned people—regardless of their identities, or ideological or partisan labels—can facilitate racism, racial inequality, and injustice.

Published
2021

17. Granular Emotion Detection in Social Media Using Multi-Discipline Ensembles

Author

Frye, Robert H., Wilson, David C., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ceci, Michelangelo, editor, Flesca, Sergio, editor, Masciari, Elio, editor, Manco, Giuseppe, editor, and Raś, Zbigniew W., editor

Published
2022
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19. Genomic diagnosis and care co-ordination for monogenic inflammatory bowel disease in children and adults: consensus guideline on behalf of the British Society of Gastroenterology and British Society of Paediatric Gastroenterology, Hepatology and Nutrition

Author

Kammermeier, Jochen, Lamb, Christopher A, Jones, Kelsey D J, Anderson, Carl A, Baple, Emma L, Bolton, Chrissy, Braggins, Helen, Coulter, Tanya I, Gilmour, Kimberly C, Gregory, Vicki, Hambleton, Sophie, Hartley, David, Hawthorne, A Barney, Hearn, Sarah, Laurence, Arian, Parkes, Miles, Russell, Richard K, Speight, R Alexander, Travis, Simon, Wilson, David C, and Uhlig, Holm H

Published
2023
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21. Author Correction: Somatic mosaicism and common genetic variation contribute to the risk of very-early-onset inflammatory bowel disease

Author

Serra, Eva Gonçalves, Schwerd, Tobias, Moutsianas, Loukas, Cavounidis, Athena, Fachal, Laura, Pandey, Sumeet, Kammermeier, Jochen, Croft, Nicholas M., Posovszky, Carsten, Rodrigues, Astor, Russell, Richard K., Barakat, Farah, Auth, Marcus K. H., Heuschkel, Robert, Zilbauer, Matthias, Fyderek, Krzysztof, Braegger, Christian, Travis, Simon P., Satsangi, Jack, Parkes, Miles, Thapar, Nikhil, Ferry, Helen, Matte, Julie C., Gilmour, Kimberly C., Wedrychowicz, Andrzej, Sullivan, Peter, Moore, Carmel, Sambrook, Jennifer, Ouwehand, Willem, Roberts, David, Danesh, John, Baeumler, Toni A., Fulga, Tudor A., Carrami, Eli M, Ahmed, Ahmed, Wilson, Rachel, Barrett, Jeffrey C., Elkadri, Abdul, Griffiths, Anne M., Snapper, Scott B., Shah, Neil, Muise, Aleixo M., Wilson, David C., Uhlig, Holm H., and Anderson, Carl A.

Published
2022
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22. Noise Constraints on Global Body-Wave Measurement Thresholds.

Author

Ringler, Adam T., Wilson, David C., Earle, Paul, Yeck, William, Mason, David B., and Wilgus, Justin

Abstract

Intermediate sized earthquakes (≈M4-6.5) are often measured using the teleseismic body-wave magnitude (mb). mb measurements are especially critical at the lower end of this range when teleseismic waveform modeling techniques (i.e., moment tensor analysis) are difficult. The U.S. Geological Survey National Earthquake Information Center (NEIC) determines the location and magnitude of all M 5 and greater earthquakes worldwide within 20 min of the rupture time, and therefore accurate magnitude estimates are essential to fulfill its mission. To better understand how network geometry and noise levels affect the global response capabilities, we developed a method to spatially estimate the minimum measurable mb. To do this, we compare expected mb amplitudes at every station to the station's background noise level. We find that using NEIC's current network geometry and these idealized thresholds, NEIC can potentially estimate mb magnitudes down to M 4.5 globally. Low-latitude regions in the Southern Hemisphere present the biggest opportunity to improve monitoring capabilities. However, logistically they also present the biggest hurdles for network operators. Finally, to test the resiliency of the network we removed the 20 most important stations and found the mb threshold remains mb 4.5. However, the region where only mb 4.5 and greater can be estimated increases and is again restricted to the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

Published
2024
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24. The Racial Double Standard

Author

Wilson, David C and Davis, Darren W

Subjects
Marketing, Political Science, Communication and Media Studies, Political Science & Public Administration
Published
2018

35. Predicting Outcomes in Pediatric Ulcerative Colitis for Management Optimization: Systematic Review and Consensus Statements From the Pediatric Inflammatory Bowel Disease–Ahead Program

Author

Orlanski-Meyer, Esther, Aardoom, Martine, Ricciuto, Amanda, Navon, Dan, Carman, Nicholas, Aloi, Marina, Bronsky, Jiri, Däbritz, Jan, Dubinsky, Marla, Hussey, Séamus, Lewindon, Peter, Martin De Carpi, Javier, Navas-López, Víctor Manuel, Orsi, Marina, Ruemmele, Frank M., Russell, Richard K., Veres, Gabor, Walters, Thomas D., Wilson, David C., Kaiser, Thomas, de Ridder, Lissy, Griffiths, Anne, and Turner, Dan

Published
2021
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36. Predicting Outcomes in Pediatric Crohn’s Disease for Management Optimization: Systematic Review and Consensus Statements From the Pediatric Inflammatory Bowel Disease–Ahead Program

Author

Ricciuto, Amanda, Aardoom, Martine, Orlanski-Meyer, Esther, Navon, Dan, Carman, Nicholas, Aloi, Marina, Bronsky, Jiri, Däbritz, Jan, Dubinsky, Marla, Hussey, Séamus, Lewindon, Peter, Martín De Carpi, Javier, Navas-López, Víctor Manuel, Orsi, Marina, Ruemmele, Frank M., Russell, Richard K., Veres, Gabor, Walters, Thomas D., Wilson, David C., Kaiser, Thomas, de Ridder, Lissy, Turner, Dan, and Griffiths, Anne M.

Published
2021
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47. Linking Geographic Vocabularies through WordNet

Author

Ballatore, Andrea, Bertolotto, Michela, and Wilson, David C.

Subjects
Computer Science - Information Retrieval, Computer Science - Computation and Language
Abstract

The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between heterogeneous vocabularies and ontologies that provides the semantic backbone of the growing constellation of open geo-knowledge bases. In this article, we show how to utilize WordNet as a semantic hub to increase the integration of LOD. With this purpose in mind, we devise Voc2WordNet, an unsupervised mapping technique between a given vocabulary and WordNet, combining intensional and extensional aspects of the geographic terms. Voc2WordNet is evaluated against a sample of human-generated alignments with the OpenStreetMap (OSM) Semantic Network, a crowdsourced geospatial resource, and the GeoNames ontology, the vocabulary of a large digital gazetteer. These empirical results indicate that the approach can obtain high precision and recall., Comment: 21 pages, 1 figure

Published
2014
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48. An evaluative baseline for geo-semantic relatedness and similarity

Author

Ballatore, Andrea, Bertolotto, Michela, and Wilson, David C.

Subjects
Computer Science - Computation and Language
Abstract

In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer's semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity., Comment: GeoInformatica 2014

Published
2014
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49. A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Author

Ballatore, Andrea, Wilson, David C., and Bertolotto, Michela

Subjects
Computer Science - Digital Libraries, Computer Science - Computers and Society, Computer Science - Information Retrieval
Abstract

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects.

Published
2014
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50. The semantic similarity ensemble

Author

Ballatore, Andrea, Bertolotto, Michela, and Wilson, David C.

Subjects
Computer Science - Computation and Language
Abstract

Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE) as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach., Comment: Special feature on Semantic and Conceptual Issues in GIS (SeCoGIS)

Published
2014
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