Directory Data Research Articles

Bidirectional Gated Recurrent Unit Neural Network for Chinese Address Element Segmentation

Chinese address element segmentation is a basic and key step in geocoding technology, and the segmentation results directly affect the accuracy and certainty of geocoding. However, due to the lack of obvious word boundaries in Chinese text, the grammatical and semantic features of Chinese text are complicated. Coupled with the diversity and complexity in Chinese address expressions, the segmentation of Chinese address elements is a substantial challenge. Therefore, this paper proposes a method of Chinese address element segmentation based on a bidirectional gated recurrent unit (Bi-GRU) neural network. This method uses the Bi-GRU neural network to generate tag features based on Chinese word segmentation and then uses the Viterbi algorithm to perform tag inference to achieve the segmentation of Chinese address elements. The neural network model is trained and verified based on the point of interest (POI) address data and partial directory data from the Baidu map of Beijing. The results show that the method is superior to previous neural network models in terms of segmentation performance and efficiency.

Describing and mapping diversity and accessibility of the urban food environment with open data and tools

The food environment is a target for policy interventions aimed at improving diet, but there is a lack of consistent evidence to guide such policy interventions, partially attributed to spatial measures of the food environment that are too narrow in scope. This study developed a workflow in the R programming language for characterising food access using multivariate methods adapted from community ecology, not previously applied in food environment research. The workflow was tested in the city of Perth, Western Australia and applied to both standard business directory data and open, crowdsourced data. The workflow was run on all Census Mesh Blocks (MB) in the Perth urban area, using the following steps: 1) collect and process food outlet and MB data, calculating a 15-min walking network isochrone around each MB centroid; 2) cluster the MB based on food outlet availability and verify identified clusters using multivariate methods; and 3) profile clusters using measures of diversity and accessibility. The results show three zones of food access in Perth, differentiated by the type and abundance of food outlets available, with better accessibility and diversity in established suburbs. The workflow is a flexible and quick tool that can help professionals and practitioners to calculate a comprehensive set of indicators of food access in any location where food outlet data is available. The combination of open and standard business directory data provides a more complete picture of the food environment than one dataset alone.

Association of Provider Performance with Changes in Insurance Networks

Medicaid managed care plans change provider networks frequently, yet there is no evidence about the performance of exiting providers relative to those that remain. To investigate the association between provider cost and quality and network exit. Observational study with provider network directory data linked to administrative claims from managed care plans in Tennessee's Medicaid program during the period 2010-2016. 1,966,022 recipients assigned to 9593 unique providers. Exposures were risk-adjusted total costs of care and nine measures from the Healthcare Effectiveness Data and Information Set (HEDIS) were used to construct a composite annual indicators of provider performance on quality. Outcome was provider exit from a Medicaid managed care plan. Differences in quality and cost between providers that exited and remained in managed care networks were estimated using a propensity score model to match exiting to nonexiting providers. Over our study period, we found that 21% of participating providers exited at least one of the Medicaid managed care plans in Tennessee. As compared with providers that remained in networks, those that exited performed 3.8 percentage points [95% CI, 2.3, 5.3] worse on quality as measured by a composite of the nine HEDIS quality metrics. However, 22% of exiting providers performed above average in quality and cost and only 29% of exiting providers had lower than average quality scores and higher than average costs. Overall, exiting providers had lower aggregate costs in terms of the annual unadjusted cost of care per-member-month - $21.57 [95% CI, - $41.02, - $2.13], though difference in annual risk-adjusted cost per-member-month was nonsignificant. Providers exiting Medicaid managed care plans appear to have lower quality scores in the year prior to their exit than the providers who remain in network. Our study did not show that managed care plans disproportionately drop high-cost providers.

Automated data integration system at the aircraft factory

The paper discusses the experience of introducing a developed automated system for integrating data directories from various, often unrelated and heterogeneous, information sources at the aircraft manufacturing enterprise Aviastar-SP JSC (Ulyanovsk, Russia). This automated system allows both manual and automatic modes to integrate the databases of directories used at the enterprise. To test the operability on real data, the developed system went through trial exploitation and gave good results.

Harnessing Knowledge for Improving Access to Fruits and Vegetables at Farmers Markets: Interactive Data Visualization to Inform Food Security Programs and Policy.

High consumption of fruits and vegetables leads to decreased risk of various chronic diseases, including obesity and cardiovascular disease. Community-level barriers to access fruits and vegetables include the high cost, limited availability, and transportation. Farmers markets are a priority strategy for improving community access to fresh fruits and vegetables. The U.S. Department of Agriculture (USDA) National Farmers Market Directory is a voluntary self-reported data source on farmers markets. The objective of this investigation of the USDA farmers markets data directory was to determine how farmers markets in the United States are grouped according to (1) availability of fruits and vegetables and (2) the payment accepted. We designed and implemented interactive data visualizations in visual analytics software to understand access to fruits and vegetables at farmers markets from 8,497 entries in the USDA Farmers Market Directory. Among the 665 new or updated entries in year 2018, a subset of 641 (96%) farmers markets with availability of fresh fruits and vegetables had 16 subgroups. Additionally, a subgroup of 102 (16%) farmer markets accepted all four federal nutrition assistance benefits (SFMNP, SNAP, WIC CVVs, and WIC FMNP). The interactive data visualizations including geographic maps connected to social media resources can be useful in advocacy efforts and can inform policy improvements designed to improve physical, social, and economic access to fruits and vegetables at farmers markets.

Disparities in Geographic Access to Hospital Outpatient Pulmonary Rehabilitation Programs in the United States

For individuals with COPD, pulmonary rehabilitation (PR) improves outcomes in terms of exercise capacity, severity of dyspnea, and health-related quality of life. However, many US patients with COPD do not use PR services. There has been limited research on geographic access to needed health-care services for individuals who live in rural communities in the United States. This study: (1) examines the geographic distribution of hospital-based outpatient PR programs in the US; and (2) compares the organizational characteristics of hospitals that offer PR programs and those that do not. A multistep process supported the determination of whether a hospital provided PR services and included: program directory data from the American Association of Cardiovascular and Pulmonary Rehabilitation (AACVPR) website and websites for AACVPR state affiliates and other COPD-relevant organizations; searches of hospital websites; e-mails with state contacts and other state organizations; and phone calls with hospital staff and state contacts. The study population included all Medicare-certified short-term acute care general medical and surgical hospitals. Data were collected and analyzed from January to November 2018. Medicare Provider of Service and American Hospital association data were used to compare the characteristics of hospitals with and without PR programs, using descriptive and bivariate statistics. 1,776 US counties do not have a hospital outpatient PR program located in a short-term acute care general medical or surgical hospital in the county, including 697 counties that do not have a hospital. The availability of a hospital outpatient PR program varies significantly by county type, hospital type and Census region. Hospitals located in a noncore county, designated as a Critical Access Hospital, or located in the South and the West were less likely to have an outpatient PR program. Significant geographic disparities exist in access to hospital outpatient PR. Potential strategies for addressing these disparities include: increasing clinician and patient awareness of the potential benefits of PR; offering staff training and incentives to supervise and provide PR services; improving Medicare reimbursement rates for PR services; replicating PR programs that have success serving rural areas; expanding cardiac rehabilitation programs to include PR; and assessing the use of telehealth technologies to provide PR in isolated areas.

Facilitating accurate health provider directories using natural language processing

BackgroundAccurate information in provider directories are vital in health care including health information exchange, health benefits exchange, quality reporting, and in the reimbursement and delivery of care. Maintaining provider directory data and keeping it up to date is challenging. The objective of this study is to determine the feasibility of using natural language processing (NLP) techniques to combine disparate resources and acquire accurate information on health providers.MethodsPublically available state licensure lists in Connecticut were obtained along with National Plan and Provider Enumeration System (NPPES) public use files. Connecticut licensure lists textual information of each health professional who is licensed to practice within the state. A NLP-based system was developed based on healthcare provider taxonomy code, location, name and address information to identify textual data within the state and federal records. Qualitative and quantitative evaluation were performed, and the recall and precision were calculated.ResultsWe identified nurse midwives, nurse practitioners, and dentists in the State of Connecticut. The recall and precision were 0.95 and 0.93 respectively. Using the system, we were able to accurately acquire 6849 of the 7177 records of health provider directory information.ConclusionsThe authors demonstrated that the NLP- based approach was effective at acquiring health provider information. Furthermore, the NLP-based system can always be applied to update information further reducing processing burdens as data changes.

A Big Data approach for multi-experiment data management

Data sharing among similar experiments is made difficult by the usage of ad hoc directory structures, data and metadata naming and by the large variety of access protocols. The Big Data paradigm provides the context to overcome the current heterogeneity problems. In this work, we present a study for a Global Storage Ecosystem designed to manage large and distributed datasets, in the context of physics experiments. The proposed environment is based on HTTP/WebDav protocols, together with modern data searching technologies, according to the Big Data paradigm. The main goal is to aggregate multiple storage areas and to simplify the operations of data retrieval, using Elasticsearch and Apache Lucene library. This platform offers to physicists an effective instrument to simplify the multi-experiment data analysis without knowing a priori the directory format or the data itself. As a proof of concept, we realised a prototype over the ReCaS Supercomputing infrastructure in Napoli.

IoT Big Data Platform Based Data Management System for West Tianshan Forest Ecosystem Research Station

This paper introduced a data management Web application for West Tianshan forest ecosystem research station by accessing the REST service API provided by an IoT big data cloud platform for eco-station management. The Web application manages the retrieved data by observation systems, and provides commonly needed functions including data query, data directory management, data sharing, data visualization and data report for each observation system. This Web application demonstrates the IoT big data cloud platform, with the help of API, is very powerful and versatile, suggesting an easy and fast approach for a single eco-station to develop a management system based on cloud platform.

Systematic method for big manufacturing data integration and sharing

Manufacturing data integration and sharing (MDIS) is an essential and key technology in big data-driven intelligent manufacturing mode. The preconditions of MDIS are generating product life cycle scenarios; strategy for acquiring data and using service according to generated scenarios to balance the interests of user, manufacturer, and environmental impacts; and standardization of data services. Firstly, this paper discusses integration process within enterprise from internal equipment-cell-shop-plant-enterprise then to external cloud. According to the different scenarios or phases, three kinds of MDIS methods are proposed, i.e., physical centralization by merging multiple data sources into an unique source for ensuring correctness of meta or general data, physical centralization by maintaining multiple data sources for promoting composed service of heterogeneous or various thematic data, and logic centralization by developing data directory for ensuring private data security and department or enterprise interests. Then, a hybrid manufacturing cloud architecture is proposed, and local critical data safely managed through private cloud, external required data, or its own provided services available through public cloud. Finally, taking machine tool and magnetic bearing resources as an example, a unified service modeling methods based on semantic ontology are used to facilitate the interconnection and interoperability between cyber space and physical space.

BANK OF ANIMAL GENETIC RESOURCES OF INSTITUTE OF ANIMALS BREEDING AND GENETICS ND. A. M.V.ZUBETS OF NAAS SYSTEM OF ANIMAL BIODIVERSITY CONSERVATION OF UKRAINE

BANK OF ANIMAL GENETIC RESOURCES OF INSTITUTE OF ANIMALS BREEDING AND GENETICS ND. A. M.V.ZUBETS OF NAAS SYSTEM OF ANIMAL BIODIVERSITY CONSERVATION OF UKRAINE

Alaska’s Economy: The First World War, Frontier Fragility, and Jack London

The Northern Review 44 (2017): 327–346The two world wars had dramatically different effects on the Alaska economy. The military build-up during the Second World War created an economic boom and laid the foundation for the modern Alaska economy. The First World War contributed to an economic decline that followed the dramatic expansion of mining activity and population in the first decade of the century. The boom and bust story is familiar to anyone interested in the economies of frontier regions. The frontier is assumed to be a fragile economy dependent on the economic fortunes of its resource industries. The economy expands and contracts with staples production. The support sector plays a passive role in economic growth and development of the frontier. Jack London suggested a different role for firms in the frontier’s support sector. He hypothesized that in a staples bust some portion of this support sector would remain. This remainder would change the frontier economic environment, providing services and reducing costs for the future. The supporting industries become an active participant in a virtuous cycle of economic development on the frontier. The First World War provides a natural experiment to test Jack London’s hypothesis. This paper looks at the effects of the decline in Alaska’s staples industries, which started in the First World War, on the territory’s support sector. Did the supporting industries simply collapse like gold, copper, and fishing? Or did these industries seem resilient in the face of the staples decline? Census and Polk Directory data are used to test this hypothesis. This article is part of a special collection of papers originally presented at a conference on “The North and the First World War,” held May 2016 in Whitehorse, Yukon.https://doi.org/10.22584/nr44.2017.014

Conception and Implementation of an Austrian Biobank Directory Integration Framework.

Sample collections and data are hosted within different biobanks at diverse institutions across Europe. Our data integration framework aims at incorporating data about sample collections from different biobanks into a common research infrastructure, facilitating researchers' abilities to obtain high-quality samples to conduct their research. The resulting information must be locally gathered and distributed to searchable higher level information biobank directories to maximize the visibility on the national and European levels. Therefore, biobanks and sample collections must be clearly described and unambiguously identified. We describe how to tackle the challenges of integrating biobank-related data between biobank directories using heterogeneous data schemas and different technical environments. To establish a data exchange infrastructure between all biobank directories involved, we propose the following steps: (A) identification of core entities, terminology, and semantic relationships, (B) harmonization of heterogeneous data schemas of different Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) directories, and (C) formulation of technical core principles for biobank data exchange between directories. (A) We identified the major core elements to describe biobanks in biobank directories. Since all directory data models were partially based on Minimum Information About BIobank Data Sharing (MIABIS) 2.0, the MIABIS 2.0 core model was used for compatibility. (B) Different projection scenarios were elaborated in collaboration with all BBMRI.at partners. A minimum set of mandatory and optional core entities and data items was defined for mapping across all directory levels. (C) Major core data exchange principles were formulated and data interfaces implemented by all biobank directories involved. We agreed on a MIABIS 2.0-based core set of harmonized biobank attributes and established a list of data exchange core principles for integrating biobank directories on different levels. This generic approach and the data exchange core principles proposed herein can also be applied in related tasks like integration and harmonization of biobank data on the individual sample and patient levels.

Adult Congenital Cardiac Care.

The Adult Congenital Heart Association (ACHA) is dedicated to supporting patients with congenital heart disease. To guide patients to qualified providers and programs, it maintains a publicly accessible directory of dedicated adult congenital cardiac programs. We analyzed the directory in 2006 and 2015, aiming to evaluate the growth of the directory as a whole and to evaluate the growth of individual programs within the directory. We also hope this raises awareness of the growing opportunities that exist in adult congenital cardiology and cardiac surgery. Data in the directory are self-reported. Only data from US programs were collected and analyzed. By the end of 2015, compared to 2006, there were more programs reporting to the directory in more states (107 programs across 42 states vs 57 programs across 33 states), with higher overall clinical volume (591 vs 164 half-day clinics per week, 96,611 vs 34,446 patient visits). On average, each program was busier (5 vs 2 half-day clinics per week per program). Over the time period, the number of reported annual operations performed nearly doubled (4,346 operations by 210 surgeons vs 2,461 operations by 125 surgeons). Access to ancillary services including specific clinical diagnostic and therapeutic services also expanded. Between 2006 and 2015, the clinical directory and the individual programs have grown. Current directory data may provide benchmarks for staffing and services for newly emerging and existing programs. Verifying the accuracy of the information and inclusion of all programs will be important in the future.

TCGA Expedition: A Data Acquisition and Management System for TCGA Data.

BackgroundThe Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 500 cases of 20 different tumor types using genomic platforms and to make these data, both raw and processed, available to all researchers. TCGA data are currently over 1.2 Petabyte in size and include whole genome sequence (WGS), whole exome sequence, methylation, RNA expression, proteomic, and clinical datasets. Publicly accessible TCGA data are released through public portals, but many challenges exist in navigating and using data obtained from these sites. We developed TCGA Expedition to support the research community focused on computational methods for cancer research. Data obtained, versioned, and archived using TCGA Expedition supports command line access at high-performance computing facilities as well as some functionality with third party tools. For a subset of TCGA data collected at University of Pittsburgh, we also re-associate TCGA data with de-identified data from the electronic health records. Here we describe the software as well as the architecture of our repository, methods for loading of TCGA data to multiple platforms, and security and regulatory controls that conform to federal best practices.ResultsTCGA Expedition software consists of a set of scripts written in Bash, Python and Java that download, extract, harmonize, version and store all TCGA data and metadata. The software generates a versioned, participant- and sample-centered, local TCGA data directory with metadata structures that directly reference the local data files as well as the original data files. The software supports flexible searches of the data via a web portal, user-centric data tracking tools, and data provenance tools. Using this software, we created a collaborative repository, the Pittsburgh Genome Resource Repository (PGRR) that enabled investigators at our institution to work with all TCGA data formats, and to interrogate these data with analysis pipelines, and associated tools. WGS data are especially challenging for individual investigators to use, due to issues with downloading, storage, and processing; having locally accessible WGS BAM files has proven invaluable.ConclusionOur open-source, freely available TCGA Expedition software can be used to create a local collaborative infrastructure for acquiring, managing, and analyzing TCGA data and other large public datasets.

Data Gaps in Selected Segments of Financial and Related Sectors in India

This brief paper aims at providing an overview of the data gaps existing in the selected segments of the financial sector in India. In financial sector, the data gaps leading to asymmetric information create market inefficiencies. Hence, the open access data has positive externalities and it should be treated as a public good and should be freely accessible. The study emphasises that with technological advancement and big data analytics, the constraints on data warehousing are minimized. However, the data gaps still prevail, because of the ignorance about the usefulness of the data and also because of the reluctance of the data holders to share the data. A large portion of existing data gaps can be bridged merely with a planned, systematic and responsible data management by the public agencies and regulators. To remove the overlaps, fragmentation, inconsistency, and gaps in the data, the study recommends the creation of an all-India single point data bank consisting of a repository of master data and a Metadata directory of entire financial and economic data from all the sectors and layers of the economy.

FUTURE ESTIMATION OF CONVENIENCE LIVING FACILITIES WITHDRAWAL DUE TO POPULATION DECLINE ALL OVER JAPAN FROM 2010 TO 2040 - FOCUS ON SUPERMARKETS, CONVENIENCE STORES AND DRUGSTORES

Population explosion is considered to be one of the most crucial problems in the world. However, in Japan, the opposite problem: population decline has become serious now. Japanese population is estimated to decrease by twenty millions in 2040. This negative situation will cause to increase areas where many residents cannot make a daily living all over Japan because many convenience living facilities such as supermarkets, convenience stores and drugstores will be difficult to maintain their market area population due to future population decline. <br><br> In our research, we used point data of convenience living facilities developed by address geocoding of digital telephone directory and point data of future population projection developed by distribution of Japanese official population projection data proportionally among the building volume of digital residential map, which can monitor building volumes all over Japan. <br><br> In conclusion, we estimated that various convenience living facilities in Japan will shrink and close by population decline in near future. In particular, it is cleared that approximately 14.7% of supermarkets will be possible to withdraw all over Japan by 2040. In addition, it is cleared that over 40% of supermarkets in some countryside prefectures will be possible to withdraw by 2040. Thus, we estimated future distributions of convenience living facilities that cannot maintain their market area population due to future population decline. Moreover, we estimated the number of people that they will become inconvenience in buying fresh foods.

Measuring the Spatial Pattern of Ethnic Groups in San Antonio's Eastside: A Spatial Analysis Approach with the Colocation Quotient

ABSTRACTThe study of cities has evolved and shifted paradigms from the early local resources viewpoint, to the morphology perspective, and to the more recent spatial approach. Through these different angles, urban geographers and sociologists have documented the different factors that lead to the formation of unique urban residential patterns. This article focuses on measuring the spatial pattern of ethnic groups residing in the Eastside neighborhood of San Antonio, Texas, in the early 1900s. The goal is to use a replicable abstract approach that will create a baseline for the comparison of current and future patterns, and provide greater understanding of the origins of residential segregation in the City of San Antonio. A historical geodatabase was created by digitizing and georeferencing buildings, blocks, and streets using Sanborn maps from 1911 and 1912, and by linking the digitized shapefiles with 1910 city directory and census data. The data were analyzed to identify and test spatial associations among different ethnic groups using the colocation quotient. This point-based metric examines the overall spatial structure of the data set and highlights the bivariate spatial association between different ethnic groups. The colocation quotient quantifies both hierarchical processes to provide an in-depth analysis of residential segregation on San Antonio's East side.

Safety risk modeling and major accidents analysis of hydrogen and natural gas releases: A comprehensive risk analysis framework

The potential safety risk of hydrogen production is often the most important element to achieve authority approval and public acceptance. Safe application of hydrogen, especially in a large scale, will require adopting adequate risk control, which requires investment on reliable risk analysis methodology. In the present study, first of all, a reliable and comprehensive safety risk analysis methodology was developed for a hydrogen production plant in an oil refinery, that consists of two qualitative methods: Hazard and Operability (HAZOP) and Preliminary Risk Analysis (PRA), a hybrid method: Event Tree Analysis (ETA) and a quantitative method: Quantitative Risk Assessment (QRA) along with a risk and consequence simulator. A HAZOP study along with the PRA technique was used for determining main hazardous sources and carrying out a qualitative risk analysis. The incident outcomes of the identified high risk scenarios were modeled using the PHAST 6.7 simulator and the frequencies of the initial events and incident outcomes were calculated using risk assessment data directory of International Association Oil & Gas Producers (OGP) and ETA, respectively. Finally, the vulnerability areas of the incident outcomes were determined and the societal risk of hydrogen plant was shown using a ‘Frequency vs. Number of fatality’ graph, known as ‘F–N’ curves. The findings show that the maximum vulnerability distance is caused by the vapor cloud explosion (280 m, at 0.01 bar) and the jet fire (275 m, at 4 kW/m2), respectively. The societal risk of the plant fell in the As Low As Reasonable Practical (ALARP) and intolerable regions according to the F–N curve of UK HSE (Health, Safety Executive) The reformer were the highest and the heat exchanger was the lowest contributor to the total risk. Therefore, the ALARP principle should be applied to indicate the appropriate ways to reduce risks and, for the intolerable risks, the system must be modified structurally, functionally, or organizationally.

Historical Post Office Directory Parser (POD Parser) Software From the AddressingHistory Project

The POD Parser is Python software for parsing the OCR’d (optical character recognised) text of digitised historical Scottish Post Office Directories (PODs) to produce a consistent structured format for the data and for geocoding each address. The software was developed as part of the AddressingHistory project which sought to combine digitised historic directories with digitised and georeferenced historic maps. The software has potential for reuse in multiple research contexts where historical post office directory data is relevant, and is therefore particularly of use in historical research into social, economic or demographic trends. The POD Parser is currently designed for use with Scottish directories but is extensible, perhaps with some adaptation, to use with other similarly formatted materials such as the English Trade Directories.