The document describes a pet adoption center that rescues abandoned pets, provides them medical care, and helps them find new homes. Staff implant microchips in pets for identification and register potential adopters as members. Adopters must meet health and living requirements. The center uses a database to store pet and member information to help staff identify pets, retrieve records, and notify adopters. Adopters are interviewed to understand their needs and choose pets from an online catalog. The database tracks medical records, home visits, and statistics to improve operations.
The metadata about scientific experiments are crucial for finding, reproducing, and reusing the data that the metadata describe. We present a study of the quality of the metadata stored in BioSample—a repository of metadata about samples used in biomedical experiments managed by the U.S. National Center for Biomedical Technology Information (NCBI). We tested whether 6.6 million BioSample metadata records are populated with values that fulfill the stated requirements for such values. Our study revealed multiple anomalies in the analyzed metadata. The BioSample metadata field names and their values are not standardized or controlled—15% of the metadata fields use field names not specified in the BioSample data dictionary. Only 9 out of 452 BioSample-specified fields ordinarily require ontology terms as values, and the quality of these controlled fields is better than that of uncontrolled ones, as even simple binary or numeric fields are often populated with inadequate values of different data types (e.g., only 27% of Boolean values are valid). Overall, the metadata in BioSample reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements. The aberrancies in the metadata are likely to impede search and secondary use of the associated datasets.
Citing data in research articles: principles, implementation, challenges - an...FAIRDOM
Prepared and presented by Jo McEntyre (EMBL_EBI) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developedthe CEDAR Workbenchis a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templates to generate high-quality metadata, and to share and manage these resources. The CEDAR Workbench provides a versatile, REST-based environment for authoring metadata that are enriched with terms from ontologies. The metadata are available as JSON, JSON-LD, or RDF for easy integration in scientific applications and reusability on the Web. Users can leverage our APIs for validating and submitting metadata to external repositories. The CEDAR Workbench is freely available and open-source.
The Center for Expanded Data Annotation and Retrieval (CEDAR) has developed a suite of tools and services that allow scientists to create and publish metadata describing scientific experiments. Using these tools and services—referred to collectively as the CEDAR Workbench—scientists can collaboratively author metadata and submit them to public repositories. A key focus of our software is semantically enriching metadata with ontology terms. The system combines emerging technologies, such as JSON-LD and graph databases, with modern software development technologies, such as microservices and container platforms. The result is a suite of user-friendly, Web-based tools and REST APIs that provide a versatile end-to-end solution to the problems of metadata authoring and management. This talk presents the architecture of the CEDAR Workbench and focuses on the technology choices made to construct an easily usable, open system that allows users to create and publish semantically enriched metadata in standard Web formats.
Presentation on the Resource Identification Pilot Project, an initiative to develop a machine-processable citation system for key research resources used in scientific studies
The availability of high-quality metadata is key to facilitating discovery in the large variety of scientific datasets that are increasingly becoming publicly available. However, despite the recent focus on metadata, the diversity of metadata representation formats and the poor support for semantic markup typically result in metadata that are of poor quality. There is a pressing need for a metadata representation format that provides strong interoperation capabilities together with robust semantic underpinnings. In this talk, we describe such a format, together with open-source Web-based tools that support the acquisition, search, and management of metadata. We outline an initial evaluation using metadata from a variety of biomedical repositories.
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery.
The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
Step by step tutorial for conducting GO enrichment analysis and then creating a network from the results.
Material from the UC Davis 2014 Proteomics Workshop.
See more at: http://sourceforge.net/projects/teachingdemos/files/2014%20UC%20Davis%20Proteomics%20Workshop/
C:\Documents And Settings\Donna Youraine\Desktop\Adoption Center\Paws Pet Ado...PAWS of Carteret
Year long renovation of the PAWS Pet Adoption Center in Morehead City, North Carolina. This building was donated to PAWS and a grant received specific for the renovation of it.
The metadata about scientific experiments are crucial for finding, reproducing, and reusing the data that the metadata describe. We present a study of the quality of the metadata stored in BioSample—a repository of metadata about samples used in biomedical experiments managed by the U.S. National Center for Biomedical Technology Information (NCBI). We tested whether 6.6 million BioSample metadata records are populated with values that fulfill the stated requirements for such values. Our study revealed multiple anomalies in the analyzed metadata. The BioSample metadata field names and their values are not standardized or controlled—15% of the metadata fields use field names not specified in the BioSample data dictionary. Only 9 out of 452 BioSample-specified fields ordinarily require ontology terms as values, and the quality of these controlled fields is better than that of uncontrolled ones, as even simple binary or numeric fields are often populated with inadequate values of different data types (e.g., only 27% of Boolean values are valid). Overall, the metadata in BioSample reveal that there is a lack of principled mechanisms to enforce and validate metadata requirements. The aberrancies in the metadata are likely to impede search and secondary use of the associated datasets.
Citing data in research articles: principles, implementation, challenges - an...FAIRDOM
Prepared and presented by Jo McEntyre (EMBL_EBI) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developedthe CEDAR Workbenchis a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templates to generate high-quality metadata, and to share and manage these resources. The CEDAR Workbench provides a versatile, REST-based environment for authoring metadata that are enriched with terms from ontologies. The metadata are available as JSON, JSON-LD, or RDF for easy integration in scientific applications and reusability on the Web. Users can leverage our APIs for validating and submitting metadata to external repositories. The CEDAR Workbench is freely available and open-source.
The Center for Expanded Data Annotation and Retrieval (CEDAR) has developed a suite of tools and services that allow scientists to create and publish metadata describing scientific experiments. Using these tools and services—referred to collectively as the CEDAR Workbench—scientists can collaboratively author metadata and submit them to public repositories. A key focus of our software is semantically enriching metadata with ontology terms. The system combines emerging technologies, such as JSON-LD and graph databases, with modern software development technologies, such as microservices and container platforms. The result is a suite of user-friendly, Web-based tools and REST APIs that provide a versatile end-to-end solution to the problems of metadata authoring and management. This talk presents the architecture of the CEDAR Workbench and focuses on the technology choices made to construct an easily usable, open system that allows users to create and publish semantically enriched metadata in standard Web formats.
Presentation on the Resource Identification Pilot Project, an initiative to develop a machine-processable citation system for key research resources used in scientific studies
The availability of high-quality metadata is key to facilitating discovery in the large variety of scientific datasets that are increasingly becoming publicly available. However, despite the recent focus on metadata, the diversity of metadata representation formats and the poor support for semantic markup typically result in metadata that are of poor quality. There is a pressing need for a metadata representation format that provides strong interoperation capabilities together with robust semantic underpinnings. In this talk, we describe such a format, together with open-source Web-based tools that support the acquisition, search, and management of metadata. We outline an initial evaluation using metadata from a variety of biomedical repositories.
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery.
The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
Step by step tutorial for conducting GO enrichment analysis and then creating a network from the results.
Material from the UC Davis 2014 Proteomics Workshop.
See more at: http://sourceforge.net/projects/teachingdemos/files/2014%20UC%20Davis%20Proteomics%20Workshop/
C:\Documents And Settings\Donna Youraine\Desktop\Adoption Center\Paws Pet Ado...PAWS of Carteret
Year long renovation of the PAWS Pet Adoption Center in Morehead City, North Carolina. This building was donated to PAWS and a grant received specific for the renovation of it.
Workshop finding and accessing data - fiona nadia charlotte - cambridge apr...Fiona Nielsen
Workshop presentation on finding and accessing human genomics data for research.
Including statistics of publicly available data sources and tips on how to save time in your workflow of data access.
Organised in collaboration between DNAdigest and Open Data Cambridge.
Read more about our work:
http://DNAdigest.org
http://repositive.io
https://uk.linkedin.com/in/fionanielsen
http://www.data.cam.ac.uk
dkNET Webinar: The Mouse Metabolic Phenotyping Centers: Services and Data 01/...dkNET
The Mouse Metabolic Phenotyping Centers (MMPC) is a National Institutes of Health-Sponsored resource that provides experimental testing services to scientists studying diabetes, obesity, diabetic complications, and other metabolic diseases in mice. Dr. Richard McIndoe will introduce resources and tools that are available at MMPC.
Abstract
A common strategy to dissect the etiology, genetics and underlying physiology of a disease is to create mouse models using gene targeting and manipulation techniques. These mouse models were developed by targeting one or more candidate genes or by using a whole genome mutagenesis strategy. The careful and reproducible characterization of these animal models is important for the advancement of biomedical research. The expense, expertise and time required to develop state-of-the-art phenotyping technologies is beyond the reach of many investigators. The Mouse Metabolic Phenotyping Centers (MMPC) were created to provide the scientific community with cost effective, high quality, standardized metabolic and phenotyping services. The focus of the MMPC is on experiments that characterize living animals as well as providing technologies that are important for understanding metabolism and physiology. The MMPC provides state-of-the-art technologies to investigators for a fee, with their services including characterization of mouse metabolism, blood composition (including hormones), energy balance, eating and exercise, organ function and morphology, physiology and histology. There are currently five MMPC Centers located at Vanderbilt University, University of California Davis, University of Cincinnati, University of Massachusetts and the University of Michigan. Investigators using the MMPC services agree to release the data generated by the MMPC to the general public via the national website database. This talk will review the structure of the MMPC, the services it provides and the data generated by the consortium for public use.
Presenter: Dr. Richard McIndoe, Professor, College of Graduate Studies and the College of Allied Health Sciences, Medical College of Georgia.
More information: https://dknet.org/about/webinar
Workshop finding and accessing data - fiona - lunteren april 18 2016Fiona Nielsen
Workshop presentation on finding and accessing human genomics data for research.
Including statistics of publicly available data sources and tips on how to save time in your workflow of data access.
Presented at BioSB2016, pre-conference PhD retreat for young researchers in bioinformatics and systems biology at Congrescentrum De Werelt in Lunteren. #BioSB2016 #BioSB16
Link to event:
http://www.youngcb.nl/events/biosb-phd-retreat-2016/
Read more about my work:
http://DNAdigest.org
http://repositive.io
https://uk.linkedin.com/in/fionanielsen
A presentation given at the Duke Margollis Health Policy meeting in 2015 and providing insights into the current challenges related to EHR data quality. Proposes a new approach - OneSource.
Predicting of Hosting Animal Centre Outcome Based on Supervised Machine Learn...sushantparte
Research Project - The objective of this project is to predict the outcome of animals placed in shelters given features such as the animal’s age, breed, and colour. There are 5 possible outcomes for each animal with euthanasia being the worst outcome. The shelter hopes to be able to determine which animals are likely to be euthanized as well as find trends into what features increase the chance for adoption. This provides a chance for shelters to try to aid animals with a low chance of adoption. The overall goal is to decrease the yearly number of animals euthanized.
An introduction to Nowomics and how it helps biologists track new data and papers relevant to their research. With some background on how the site go started.
Redaction of Protected Health Information while Submitting SDTM or ADaM Datas...Venu Perla
One of the final steps in submission of clinical study report (CSR) to FDA involves submission of clinical or SDTM/ADaM datasets with protected health information (PHI). During this process, clinical programmers adopt different strategies to redact PHI. The objective of this presentation is to explain a uniform strategy for clinical programmers while redacting PHI in SDTM/ADaM datasets during the CSR development. This presentation covers Code of Federal Regulations related to PHI; how to categorize PHI for programming purpose; and how to redact each category of PHI in SDTM/ADaM datasets using programming techniques.
Ontology-Driven Clinical Intelligence: Removing Data Barriers for Cross-Disci...Remedy Informatics
The presentation describes how Remedy Informatics is advocating and innovating "flexible standardization" through an ontology-driven approach to clinical research. You will see in greater detail how a foundational, standardized Mosaic Ontology can be extended for more specific research applications and even more specific and focused disease research.
This module describes how missing data can be managed while maintaining data quality. It explains how to plan for missing data; defines different types of “missingness;” outlines the benefits of documenting missing data and illustrates how to document missing data; and describes procedures to minimize missing data. Upon completion of this module, students will be able to explain why data managers should strive to minimize missing data and develop a plan to record or code why data are missing.
Afternoon session: Workshop on systematic searching
- Defining a search strategy, database selection,tips and tricks
- Setting up your systematic review 'toolbox'
- How do you support your workflow? Documenting the search process, deduplication, prisma statement.
http://www.ub.uio.no/english/about/news-and-events/events/2014/systematic-reviews-seminar.html
Bioinformatics databases: Current Trends and Future PerspectivesUniversity of Malaya
Data is the most powerful resource in any field or subject of study. In Biology, data comes from scientists and their actions, while any institution that makes sense of the data collected, will be in the forefront in their respective research field. In the beginning of any data collection endeavour, it is critical to find proper management techniques to store data and to maximise its utilisation. This presentation reflects upon the current trends and techniques of data modeling, architecture with a highlight on the uses of database, focusing on Bioinformatics examples and case studies. Finally, the future of bioinformatics databases is highlighted to give an overview of the modeling techniques to accommodate the biological data escalation in coming years.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
Group A - pet adoption centre
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3. Pet adoption centre The place where rescued abandoned pets may be sent Pets wait for their next owner Electronic microchip implanted as “ID card” Health services: injection + de-sexing
4. Adoption Good health condition + suitable living environment required Register as members first Home visits to the adopter’s family after adoption Database system Used to store pet’s information consistently
15. Microchip implant for identification Locate and identify pets Assign unique number Notification to staff and members Signaling to staff when pets need treatment Notification of expiring membership Catalogue for keeping records Store pets’ information Retrieve the information by using search function
16. Updating pet information Help adopters on decision making When pets receive injections, update health records for keeping track on health condition Arranging of home visit after adoption Monitor the pets’ latest condition Summarizing statistics Formulate strategy for operation or promotion
25. Surprised to notice how metadata closely relates to us Impressed by the significance of: Planning for data structure Criteria for data selection No longer be appropriate to use single schema (Dublin Core) to construct a metadata scheme Adoption of mixing different metadata schema (Barker & Campbell, 2010)
26. Barker, P. & Campbell, L. M. (2010). Metadata for Learning Materials: An Overview of Existing Standards and Current Developments. Technology, Instruction, Cognition & Learning, 7(3/4), 225. Retrieved from EBSCOhost.
