scholarly journals Progress Out of a Pandemic: Global collections, data sharing, and changing standards of practice

Author(s):  
Deborah Paul ◽  
Pamela Soltis

The COVID-19 pandemic has disrupted all aspects of our lives, but has also spawned new opportunities. Months of multidisciplinary, global collaboration have explored the connections between natural history collections and COVID-19. Museums have unrivalled (and still largely untapped) potential to contribute data, methods, and expertise to prediction, mitigation, and prevention efforts related to zoonotic disease outbreaks (DiEuliis et al. 2016, Dunnum et al. 2017), and there is a clear need for ongoing collaboration across (at least) microbiology, disease ecology, and natural history collections. In addition, we note that the roadblocks to effective data access and integration related to microbes and their hosts are a microcosm of the larger data landscape; solving these issues in the context of COVID-19—from liberating data from publications to ensuring digital connections between voucher specimens and all derived viral genetic sequences—will improve biodiversity data access and use more broadly. Efforts since March 2020 have promoted collaboration across disciplines, international boundaries, and continents. At iDigBio, staff updated information about genetic/genomic resources available in US mammal collections; 24 records were added and information enhanced (Cortez and Soltis 2020). The Distributed System of Scientific Collections (DiSSCo) and the Consortium of European Taxonomic Facilities (CETAF) formed a worldwide COVID-19 Task Force (TaF). A US-led group formed the ViralMuse Task Force, working in concert with the TaF. Activities of the TaF centered on four areas: building a hub to coalesce knowledge from this group in a central location – including mining mammals-of-the-world literature, improving the metadata shared when publishing sequence data, encouraging virologists to voucher in museum collections, and gathering critical research questions around zoonotic disease from the scientific community. Through an online public event, this TaF shared work to date and critical next steps. Ongoing efforts include further refinement of metadata requirements for deposition of viral genetic data to include host specimen voucher identifiers, development of methods for better integration of bat and pathogen data from the literature and databases, analysis of community surveys, and development of webinars, symposia, and publications to report the work of the TaF. Members of the ViralMuse group worked to raise awareness of the critical value of and need for museum experts, collections data, and samples in any analyses of zoonotic events. ViralMuse members (Cook et al. 2020) stressed the need for collaborative action to: develop guidelines for keeping samples of both pathogens and hosts. develop and implement metadata requirements for physical specimens and samples. expand investment in infrastructure, both cyber and physical, to support archives of biological materials. increase communication and development of new channels of dialogue and collaboration among museum scientists, microbiologists, bioinformaticians, biomedical professionals, and disease ecologists. enhance financial support and realize strong leadership from federal agencies, international partners, and private foundations to develop proactive, multi-disciplinary approaches to future pandemics (see also da Silva et al. 2020). develop guidelines for keeping samples of both pathogens and hosts. develop and implement metadata requirements for physical specimens and samples. expand investment in infrastructure, both cyber and physical, to support archives of biological materials. increase communication and development of new channels of dialogue and collaboration among museum scientists, microbiologists, bioinformaticians, biomedical professionals, and disease ecologists. enhance financial support and realize strong leadership from federal agencies, international partners, and private foundations to develop proactive, multi-disciplinary approaches to future pandemics (see also da Silva et al. 2020). ViralMuse continues to advance these goals. To reach a broader audience, we published an article in The Conversation (Soltis et al. 2020). A new project, funded by the US National Science Foundation (NSF), is aimed at enhancing existing published museum specimen data relevant to one potential reservoir of SARS-CoV-2, horseshoe bats (Mast and Paul 2020). NSF has also provided support to foster continued collaboration, infrastructure development, and integration of communities of practice concerning zoonotic diseases (Soltis and Paul 2020). From a TDWG perspective, issues relating to data access, data standards, and data integration require attention. Methods to liberate data from publications need to be expanded, and proposed metadata requirements for viral genetic sequences need to be implemented by international databases and adopted by the community. A summit on collections management software could help align efforts to both store and share the necessary host-pathogen information in standards-compliant formats that support discovery, access, and citation/attribution. A new and effective communication strategy is needed to develop an integrated research community (comprising the biodiversity, collections, data science, disease ecology, microbiology, and One Health communities) and to support needed changes in standards of practice (emphasizing vouchering, data standards, and data integration).

2012 ◽  
Vol 26 (1) ◽  
pp. 199-205 ◽  
Author(s):  
Li Zhang ◽  
Amy R. Pawlicki ◽  
Dorothy McQuilken ◽  
William R. Titera

ABSTRACT Data acquisition difficulties have hindered the application of advanced audit technology and audit analytics, and accentuated the challenges to meet growing audit demands. To alleviate this problem, this paper discusses the main drivers to evolve the audit process: data standards, data access, audit applications, and continuous audit. As a joint effort between the AICPA and academia, this paper provides guidance and suggestions to internal and external auditors, as well as scholars to develop knowledge for leading edge practice (Kaplan 2011).


2019 ◽  
pp. 254-277 ◽  
Author(s):  
Ying Zhang ◽  
Chaopeng Li ◽  
Na Chen ◽  
Shaowen Liu ◽  
Liming Du ◽  
...  

Since large amount of geospatial data are produced by various sources, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. We mainly adopt four kinds of geospatial data sources to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).


2019 ◽  
pp. 230-253
Author(s):  
Ying Zhang ◽  
Chaopeng Li ◽  
Na Chen ◽  
Shaowen Liu ◽  
Liming Du ◽  
...  

Since large amount of geospatial data are produced by various sources and stored in incompatible formats, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. First, we provide a uniform integration paradigm for users to retrieve geospatial data. Then, we align the retrieved geospatial data in the modeling process to eliminate heterogeneity with the help of Karma. Our main contribution focuses on addressing the third problem. Previous work has been done by defining a set of semantic rules for performing the linking process. However, the geospatial data has some specific geospatial relationships, which is significant for linking but cannot be solved by the Semantic Web techniques directly. We take advantage of such unique features about geospatial data to implement the linking process. In addition, the previous work will meet a complicated problem when the geospatial data sources are in different languages. In contrast, our proposed linking algorithms are endowed with translation function, which can save the translating cost among all the geospatial sources with different languages. Finally, the geospatial data is integrated by eliminating data redundancy and combining the complementary properties from the linked records. We mainly adopt four kinds of geospatial data sources, namely, OpenStreetMap(OSM), Wikmapia, USGS and EPA, to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).


Author(s):  
Ying Zhang ◽  
Chaopeng Li ◽  
Na Chen ◽  
Shaowen Liu ◽  
Liming Du ◽  
...  

Since large amount of geospatial data are produced by various sources, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. We mainly adopt four kinds of geospatial data sources to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).


2020 ◽  
Vol 9 (8) ◽  
pp. 474
Author(s):  
Linfang Ding ◽  
Guohui Xiao ◽  
Diego Calvanese ◽  
Liqiu Meng

In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which mappings specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data.


2019 ◽  
Vol 1 (3) ◽  
pp. 201-223 ◽  
Author(s):  
Guohui Xiao ◽  
Linfang Ding ◽  
Benjamin Cogrel ◽  
Diego Calvanese

In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virtual and embed domain knowledge. We explain the main notions of this paradigm, its tooling ecosystem and significant use cases in a wide range of applications. Finally, we discuss future research directions.


1950 ◽  
Vol 44 (3) ◽  
pp. 593-607 ◽  
Author(s):  
Gilbert P. White

The central problem in national executive organization for water resources is that of fitting the service of specialized Federal agencies to the task of promoting the unified development of entire drainage basins. While technical recognition of the interlocking character of water resources development grew rapidly after 1920 and found expression in basin-wide plans, the administrative organization was unable to keep pace. It now presents conspicuous weaknesses which have been described by the Hoover Commission and its Task Force on Natural Resources. Remedial action involving the combination of several existing agencies and the creation of a central board of review have been recommended. An effort also has been initiated to correlate and reconcile the disperse and often conflicting Federal policies upon which the agencies are operating.


2006 ◽  
Vol 22 (5) ◽  
pp. 264-268 ◽  
Author(s):  
Joellyn Randall ◽  
Rachel Knee ◽  
Cynthia Galemore

Policy and procedure manuals are essential to establishing standards of practice and ensuring quality of care to students and families. The Olathe District Schools (Kansas) Technology Department created the Virtual File Cabinet to provide online access to employee policies, school board policies, forms, and other documents. A task force of school nurses was formed to convert the nursing department’s policies, procedures, protocols, and forms from hard copy to electronic format and make them available on the district’s Virtual File Cabinet. Having the policy and procedure manuals in electronic format allows for quick access and ease in updating information, thereby guaranteeing the school nurses have access to the most current information. Cost savings were realized by reducing the amount of paper and staff time needed to copy, collate, and assemble materials.


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