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David Eichmann

dblp:e/DEichmann · also David A. Eichmann · DBLP profile ↗
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23ranked-venue papers
11as first author
3since 2021 · last 2025
0000-0003-3150-8758ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 8 · 6 first-authorDatabases, data management, data science and information retrieval · 6 · 3 first-authorApplied, interdisciplinary, general and emerging computing · 6 · 3 since 2021Artificial intelligence and machine learning · 5 · 3 first-authorHuman-computer interaction and ubiquitous computing · 3Computer networks · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
2 papers
Information retrieval · 65% Data models and query languages · 24% Query processing and optimization · 11%
Software engineering, system software, and programming languages
2 papers
Requirements engineering and software design · 53% Software maintenance and evolution · 24% Program analysis · 24%

Topics — the 10 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
cross-language information retrieval
0.011998
Cross-Language Information Retrieval with the UMLS Metathesaurus · SIGIR 1998
Information retrieval › cross-language information retrieval
query translation
0.011998
Cross-Language Information Retrieval with the UMLS Metathesaurus · SIGIR 1998
Requirements engineering and software design
web engineering
0.011997
Software Engineering (on) the World Wide Web (Workshop) · ICSE 1997
Program analysis › static analysis
program slicing
0.011993
Program and Interface Slicing for Reverse Engineering · ICSE 1993
Software maintenance and evolution
reverse engineering
0.011993
Program and Interface Slicing for Reverse Engineering · ICSE 1993
Query processing and optimization
query optimization
0.011991
A Polymorphic Relational Algebra and Its Optimization · ICDE 1991
Data models and query languages › type system
type inference
0.011991
A Polymorphic Relational Algebra and Its Optimization · ICDE 1991
Information retrieval › evaluation
retrieval effectiveness
0.011998
Cross-Language Information Retrieval with the UMLS Metathesaurus · SIGIR 1998
Requirements engineering and software design
software process
0.011997
Software Engineering (on) the World Wide Web (Workshop) · ICSE 1997
Data models and query languages
object-oriented data model
0.011991
A Polymorphic Relational Algebra and Its Optimization · ICDE 1991

Methods — techniques the papers use, named apart from their topics

vocabulary normalization · 0.0UMLS Metathesaurus · 0.0program slicing · 0.0type inference · 0.0
YearPublicationVenuePosition
2025 National COVID Cohort Collaborative data enhancements: a path for expanding common data models
abstract
OBJECTIVE: To support long COVID research in National COVID Cohort Collaborative (N3C), the N3C Phenotype and Data Acquisition team created data designs to aid contributing sites in enhancing their data. Enhancements include long COVID specialty clinic indicator; Admission, Discharge, and Transfer transactions; patient-level social determinants of health; and in-hospital use of oxygen supplementation. MATERIALS AND METHODS: For each enhancement, we defined the scope and wrote guidance on how to prepare and populate the data in a standardized way. RESULTS: As of June 2024, 29 sites have added at least one data enhancement to their N3C pipeline. DISCUSSION: The use of common data models is critical to the success of N3C; however, these data models cannot account for all needs. Project-driven data enhancement is required. This should be done in a standardized way in alignment with common data model specifications. Our approach offers a useful pathway for enhancing data to improve fit for purpose. CONCLUSION: In this initiative, we rapidly produced project-specific data modeling guidance and documentation in support of long COVID research while maintaining a commitment to terminology standards and harmonized data.
Kellie M. Walters, Marshall Clark, Sofia Dard, Stephanie S. Hong, Elizabeth Kelly, Kristin Kostka, Adam M. Lee, Robert T. Miller, Michele Morris, Matvey Palchuk, Emily R. Pfaff, Adam B. Wilcox, Alexis Graves, Alfred Anzalone, Amin Manna, Amit Saha, Amy Olex, Andrea Zhou, Andrew E. Williams, Andrew Southerland, Andrew T. Girvin, Anita Walden, Anjali A Sharathkumar, Benjamin R. C. Amor, Benjamin Bates, Brian Hendricks, Caleb Alexander, Carolyn T. Bramante, Cavin Ward-Caviness, Charisse R. Madlock-Brown, Christine Suver, Christopher G. Chute, Christopher Dillon, Chunlei Wu, Clare Schmitt, Cliff Takemoto, Dan Housman, Davera Gabriel, David Eichmann, Diego Mazzotti, Don Brown, Eilis A. Boudreau, Elaine L. Hill, Elizabeth Zampino, Emily Carlson Marti, Evan French, Farrukh M. Koraishy, Federico Mariona, Fred W. Prior, George Sokos, Greg Martin, Harold P. Lehmann, Heidi Spratt, Hemalkumar Mehta, Hythem Sidky, J. W. Awori Hayanga, Jami Pincavitch, Jaylyn Clark, Jeremy Richard Harper, Jessica Islam, Jin Ge, Joel Gagnier, Joel H. Saltz, Johanna Loomba, John Buse, Jomol P. Mathew, Joni L. Rutter, Julie A. McMurry, Justin Guinney, Justin Starren, Karen Crowley, Katie Rebecca Bradwell, Ken Wilkins, Kenneth R. Gersing, Kenrick Dwain Cato, Kimberly Murray, Lavance Northington, Lee Allan Pyles, Leonie Misquitta, Lesley Cottrell, Lili M. Portilla, Mariam Deacy, Mark M. Bissell, Mary Emmett, Mary Morrison Saltz, Melissa A. Haendel, Meredith C. B. Adams, Meredith Temple-O'Connor, Michael G. Kurilla, Nabeel Qureshi, Nasia Safdar, Nicole Garbarini, Noha Sharafeldin, Ofer Sadan, Patricia A. Francis, Penny Wung Burgoon, Peter N. Robinson, Philip R. O. Payne, Rafael Fuentes, Randeep Jawa, Rebecca Erwin-Cohen, Rena Patel, Richard A. Moffitt, Richard L. Zhu, Rishi Kamaleswaran, Robert Hurley, Saiju Pyarajan, Samuel G. Michael, Samuel Bozzette, Sandeep Mallipattu, Satyanarayana Vedula, Scott Chapman, Shawn T. O'Neil, Soko Setoguchi, Tellen D. Bennett, Tiffany Callahan, Umit Topaloglu, Usman Sheikh, Valery Gordon, Vignesh Subbian, Warren A. Kibbe, Wenndy Hernandez, Will Beasley, Will Cooper, William Hillegass, Xiaohan Tanner Zhang
J. Am. Medical Informatics Assoc.40
2022 Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C)
abstract
OBJECTIVE: This study sought to evaluate whether synthetic data derived from a national coronavirus disease 2019 (COVID-19) dataset could be used for geospatial and temporal epidemic analyses. MATERIALS AND METHODS: Using an original dataset (n = 1 854 968 severe acute respiratory syndrome coronavirus 2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip code-level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated. RESULTS: In general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean = 2.9 ± 2.4; max = 16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n = 171) and for all unsuppressed zip codes (n = 5819), respectively. In small sample sizes, synthetic data utility was notably decreased. DISCUSSION: Analyses on the population-level and of densely tested zip codes (which contained most of the data) were similar between original and synthetically derived datasets. Analyses of sparsely tested populations were less similar and had more data suppression. CONCLUSION: In general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression-an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.
Jason A. Thomas, Randi E. Foraker, Noa Zamstein, Jon D. Morrow, Philip R. O. Payne, Adam B. Wilcox, Melissa A. Haendel, Christopher G. Chute, Kenneth R. Gersing, Anita Walden, Tellen D. Bennett, David Eichmann, Justin Guinney, Warren A. Kibbe, Emily R. Pfaff, Peter N. Robinson, Joel H. Saltz, Heidi Spratt, Justin Starren, Christine Suver, Chunlei Wu, Davera Gabriel, Stephanie S. Hong, Kristin Kostka, Harold P. Lehmann, Richard A. Moffitt, Michele Morris, Matvey Palchuk, Xiaohan Tanner Zhang, Richard L. Zhu, Benjamin R. C. Amor, Mark M. Bissell, Marshall Clark, Andrew T. Girvin, Adam M. Lee, Robert T. Miller, Kellie M. Walters, Yooree Chae, Connor Cook, Alexandra Dest, Racquel R. Dietz, Thomas Dillon, Patricia A. Francis, Rafael Fuentes, Alexis Graves, Andrew J. Neumann, Shawn T. O'Neil, Usman Sheikh, Andréa M. Volz, Elizabeth Zampino, Christopher P. Austin, Samuel Bozzette, Mariam Deacy, Nicole Garbarini, Michael G. Kurilla, Samuel G. Michael, Joni L. Rutter, Meredith Temple-O'Connor, Katie Rebecca Bradwell, Amin Manna, Nabeel Qureshi, Mary Morrison Saltz, Julie A. McMurry, Carolyn T. Bramante, Jeremy Richard Harper, Wenndy Hernandez, Farrukh M. Koraishy, Federico Mariona, Saidulu Mattapally, Amit Saha, Satyanarayana Vedula, Yujuan Fu, Nisha Mathews, Ofer Mendelevitch
J. Am. Medical Informatics Assoc.12
2021 The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
abstract
OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.
Melissa A. Haendel, Christopher G. Chute, Tellen D. Bennett, David Eichmann, Justin Guinney, Warren A. Kibbe, Philip R. O. Payne, Emily R. Pfaff, Peter N. Robinson, Joel H. Saltz, Heidi Spratt, Christine Suver, John Wilbanks, Adam B. Wilcox, Andrew E. Williams, Chunlei Wu, Clair Blacketer, Robert L. Bradford, James J. Cimino, Marshall Clark, Evan W. Colmenares, Patricia A. Francis, Davera Gabriel, Alexis Graves, Raju Hemadri, Stephanie S. Hong, George Hripcsak, Dazhi Jiao, Jeffrey G. Klann, Kristin Kostka, Adam M. Lee, Harold P. Lehmann, Lora Lingrey, Robert T. Miller, Michele Morris, Shawn N. Murphy, Karthik Natarajan, Matvey Palchuk, Usman Sheikh, Harold R. Solbrig, Shyam Visweswaran, Anita Walden, Kellie M. Walters, Griffin M. Weber, Xiaohan Tanner Zhang, Richard L. Zhu, Benjamin R. C. Amor, Andrew T. Girvin, Amin Manna, Nabeel Qureshi, Michael G. Kurilla, Samuel G. Michael, Lili M. Portilla, Joni L. Rutter, Christopher P. Austin, Kenneth R. Gersing
J. Am. Medical Informatics Assoc.4
2017 The state and evolution of U.S. iSchools: From talent acquisitions to research outcome
abstract
The past 2 decades have witnessed the emergence of information as a scientific discipline and the growth of information schools around the world. We analyzed the current state of the iSchool community in the U.S. with a special focus on the evolution of the community. We conducted our study from the perspectives of acquiring talents and producing research, including the analysis on iSchool faculty members' educational backgrounds, research topics, and the hiring network among iSchools. Applying text mining techniques and social network analysis to data from various sources, our research revealed how the iSchool community gradually built its own identity over time, including the growing number of faculty members who received their doctorates from the field that studies information, the deviation from computer science and library science, the rising emphasis on the intersection of information, technology, and people, and the increasing educational and research homogeneity as a community. These findings suggest that iSchools in the U.S. are evolving into a mature and independent discipline with a more established identity.
Zhiya Zuo, Kang Zhao 0001, David Eichmann
J. Assoc. Inf. Sci. Technol.3
2016 The scientometrics of successful women in science
abstract
This paper examines the effects of gender differences in collaboration on research outcomes. We analyzed network characteristics of seventeen medical research institutions that are Clinical and Translational Science Awardees (CTSA) to determine if network connectivity characteristics have the potential to help mitigate the performance gap between the sexes. We determined betweenness centrality to identify well-connected researchers. Then we used clustering coefficient to determine how tightly connected their collaborators were with each other. We correlate these scores with productivity (number of total publications for each author), and h-index (the number of papers h for which an author has h citations). We also provide data on how network characteristics vary by role for each gender studied. Our results indicate that being well connected is more highly correlated with success for women than men for most of the institutions we studied. We believe these results can be leveraged to improve success rates for women in the future.
Charisse R. Madlock-Brown, David Eichmann
ASONAM2
2015 Assessing the Translational Capacity of Five CTSA Institutions
abstract
This paper presents collaboration trends for five Clinical and Translational Science Awardee (CTSA) institution to demonstrate the need for new evaluation metrics. Translational science, a methodology that bridges gaps between fundamental and applied science, has gained attention from both the medical research community and government funding agencies. To facilitate interdisciplinary research it is important to understand what aspects of the process act as a bottleneck and limit its effectiveness. Cultural norms within the scientific community make communication between disciplines difficult [1]. CTSAs are meant to help ease burdens and foster an environment where clinicians and basic scientists work together [2]. In 2013, NCATS director, Dr. Chris Austin, said the CTSAs operated "without particular encouragement or direction from the NIH, and this in a disjointed and uncoordinated fashion" [3]. Our intention is to highlight areas of concern and to demonstrate the need and potential for bibliometric translational indicators to help alleviate some of the difficulties with CTSA evaluation by determining the importance of basic scientists in research networks, discussing patterns of co-authorship by institution, and presenting two translational indicators, which can help institutions and funding agencies compare CTSA collaborative patterns.
Charisse R. Madlock-Brown, David Eichmann
ASONAM2
2014 Personal health records: a randomized trial of effects on elder medication safety
abstract
PURPOSE: To examine the impact of a personal health record (PHR) on medication-use safety among older adults. BACKGROUND: Online PHRs have potential as tools to manage health information. We know little about how to make PHRs accessible for older adults and what effects this will have. METHODS: A PHR was designed and pretested with older adults and tested in a 6-month randomized controlled trial. After completing mailed baseline questionnaires, eligible computer users aged 65 and over were randomized 3:1 to be given access to a PHR (n=802) or serve as a standard care control group (n=273). Follow-up questionnaires measured change from baseline medication use, medication reconciliation behaviors, and medication management problems. RESULTS: Older adults were interested in keeping track of their health and medication information. A majority (55.2%) logged into the PHR and used it, but only 16.1% used it frequently. At follow-up, those randomized to the PHR group were significantly less likely to use multiple non-steroidal anti-inflammatory drugs-the most common warning generated by the system (viewed by 23% of participants). Compared with low/non-users, high users reported significantly more changes in medication use and improved medication reconciliation behaviors, and recognized significantly more side effects, but there was no difference in use of inappropriate medications or adherence measures. CONCLUSIONS: PHRs can engage older adults for better medication self-management; however, features that motivate continued use will be needed. Longer-term studies of continued users will be required to evaluate the impact of these changes in behavior on patient health outcomes.
Elizabeth A. Chrischilles, Juan Pablo Hourcade, William Doucette, David Eichmann, Brian M. Gryzlak, Ryan R. Lorentzen, Kara Wright, Elena Letuchy, Michael Mueller, Karen Farris, Barcey Levy
J. Am. Medical Informatics Assoc.4
2011 Direct2Experts: a pilot national network to demonstrate interoperability among research-networking platforms
abstract
Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard data-exchange model and resistance of universities to share information about their faculty have presented barriers to forming an institutionally supported national network. This case report describes an initiative, which, in only 6 months, achieved interoperability among seven major research-networking products at 28 universities by taking an approach that focused on addressing institutional concerns and encouraging their participation. With this necessary groundwork in place, the second phase of this effort can begin, which will expand the network's functionality and focus on the end users.
Griffin M. Weber, William K. Barnett, Mike Conlon, David Eichmann, Warren A. Kibbe, Holly J. Falk-Krzesinski, Michael Halaas, Layne Johnson, Eric Meeks, Donald Mitchell, Titus Schleyer, Sarah C. Stallings, Michael Warden, Maninder Kahlon
J. Am. Medical Informatics Assoc.4
2010 Unintended consequences of health information technology: A need for biomedical informatics
Elmer V. Bernstam, William R. Hersh, Ida Sim, David Eichmann, Jonathan C. Silverstein, Jack W. Smith, Michael J. Becich
J. Biomed. Informatics4
2002 Adaptive Filtering of Newswire Stories using Two-Level Clustering
David Eichmann, Padmini Srinivasan
Inf. Retr.1
1998 Cross-Language Information Retrieval with the UMLS Metathesaurus
abstract
We investigate an automatic method for Cross Language Information Retrieval (CLIR) that utilizes the multilingual UMLS Metathesaurus to translate Spanish and French natural language queries into English. Two experiments are presented using OHSUMED, a subset of MEDLINE. Both experiments examine retrieval effectiveness of the translated queries. However, in the second experiment, the query translation procedure is augmented with digram based vocabulary normalization procedures. In this comparative study of retrieval effectiveness the measures used are: 11--point--average precision score (11--AvgP); average interpolated precision at recall of 0.1; and noninterpolated (i.e., exact) precision after 10 retrieved documents. Our results indicate that for Spanish the UMLS Metathesaurus based CLIR method appears equivalent to multilingual dictionary based approaches investigated in the current literature. French yields less favorable results and our analysis suggests that linguistic differences ...
David Eichmann, Miguel E. Ruiz, Padmini Srinivasan
SIGIR1
1997 Software Engineering (on) the World Wide Web (Workshop)
abstract
No abstract available.
David Eichmann
ICSE1
1997 A Neural Network Approach to Tracking Eye Position
abstract
The design of a neural network based eye tracker is presented. A series of experiments with counterpropagation neural networks convert synthetic video images into eye coordinates by an enhanced feed-forward neural network with multiple winning hidden layer nodes. Difficulties encountered during the design process are discussed. The results show that accurate, fine-grained tracking of a human's eye position is possible by processing the video image collected from a goggle-mounted miniature charge-coupled device (CCD) camera.
Bryn Wolfe, David Eichmann
Int. J. Hum. Comput. Interact.2
1996 Maintenance In a Dual-Lifecycle Software Engineering Process
abstract
Dual-lifecycle software processes have the potential to significantly improve the way in which suites of software applications are generated and sustained. However, several outstanding issues need to be more adequately addressed before the full potential of this philosophy can be realized. Detailed strategies for maintaining domain architectures in parallel with suites of fielded applications are at present particularly conspicuous by their absence. In this paper, we present a dual-lifecycle maintenance process that was developed for the ROSE (Reusable Object Software Engineering) project, a major reengineering and repository-building effort in the domain of flight design and dynamics. We present the major features of the process, the rationale behind these features, and changes which we feel would be beneficial based on lessons learned from the application of the process. The process is presented using a variant of the Fusion object-oriented design method known as Profusion.
M. Weisskopf, C. W. Irving, Charles McKay, Colin Atkinson 0001, David Eichmann
ICSM5
1995 Workshop on Domain Engineering as a Research Agenda for Software Engineering and Knowledge Engineering
David Eichmann, Mari Georges
SEKE1
1995 Ethical Web Agents
David Eichmann
Comput. Networks ISDN Syst.1
1995 Advances in Network Information Discovery and Retrieval
abstract
Access to information using the Internet has undergone dramatic change and expansion recently. The unrivaled success of the World Wide Web has altered the Internet from something approachable only by the initiated to something of a media craze — the information superhighway made manifest in the personal "home page". This paper surveys the beginnings of network information discovery and retrieval, how the Web has created a surprising level of integration of these systems, and where the current state of the art lies in creating globally accessible information spaces and supporting access to those information spaces.
David Eichmann
Int. J. Softw. Eng. Knowl. Eng.1
1994 Integrating Structured Databases into the Web: The MORE System
David Eichmann, Terry McGregor, Dann Danley
Comput. Networks ISDN Syst.1
1993 Program and Interface Slicing for Reverse Engineering
Jon Beck, David Eichmann
ICSE2
1992 Supporting Multiple Domains in a Single Reuse Repository
abstract
Domain analysis typically results in the construction of a domain-specific repository. Such a repository imposes artificial boundaries on the sharing of similar assets between related domains. A lattice-based approach to repository modeling can preserve a reuser's domain specific view of the repository, while avoiding replication of commonly used assets and supporting a more general perspective on domain interrelationships.>
David Eichmann
SEKE1
1992 Assessing Repository Technology: Where do We Go from Here?
abstract
Three sample information retrieval systems, archie, autoLib, and WAIS, are compared as to their expressiveness and usefulness — first, in the general context of information retrieval, and then as prospective software reuse repositories. While the representational capabilities of these systems are limited, they provide a useful foundation for future repository efforts, particularly from the perspective of repository distribution and coherent user interface design.
David Eichmann
Int. J. Softw. Eng. Knowl. Eng.1
1991 A Polymorphic Relational Algebra and Its Optimization
abstract
The notion of a polymorphic database and the optimization of polymorphic queries-specifically, optimization of queries under the Morpheus data model-is addressed. The notion of query optimization through type inference, applicable both to polymorphic databases and traditional monomorphic databases, is introduced. The Morpheus data model and its type inference rules are reviewed and a polymorphic relational algebra is characterized. It is shown how the inference rules can be used for static optimization of a few sample queries. It is concluded that type inference provides a formal mechanism for optimizing a very rich extension to the relational algebra. The approach retains the basic framework that lead to the wide acceptance of the relational model, while enriching it with the structural expressiveness of the object-oriented approaches of recent years.>
David Eichmann, D. Alton
ICDE1
1990 Design of a Lattice-Based Faceted Classification System
David Eichmann, John Atkins
SEKE1