dataesr/scientific-paragraphs-categorization huggingface dataset:
Gene bank database Within the gene bank the data stream focuses upon various processes associated with sample handling. For example, date of arrival, sender name and address, state of arrival (fresh or cryopreserved), the temperature, pH, and sperm movement analysis of fresh semen at arrival. For samples already cryopreserved, information includes data on the straw itself, noting if there were any peculiarities about the shipment, etc. Once samples are frozen, the storage location will also need documenting. This usually includes a hierarchy from the largest storage space to the smallest. For example, tank number, pie within a tank, canister, goblet and cane/visotube (the level where no individual animal samples are mixed).
Material storage The key factors to consider for storage are traceability and safety. Each storage unit should be uniquely identified (such as with a barcode label, a printed unique identification number or a colour code for semen visotubes) so that the identity and location of the biological material are unambiguously known and entered in the gene bank information system. Duplicate storage is recommended. In addition, an empty storage capacity should remain available to rescue material in the case of failure of storage equipment. Systems for continuous temperature control and control of access to the storage room must be implemented. The systems should record all fluctuations in temperature and entries of personnel into the room. These data are to be entered into the gene bank database so that long-term trends can be documented during gene bank reviews.
Non-conformity assessments Any deviation from normal operations or from achievement of the objectives, or any complaint from users, must be reported and classified according to its impact on gene bank operations. Impact can be minor, moderate or critical. Critical non-conformities are those that prevent the gene bank from performing its operations. Examples include: (i) long-term electricity blackouts without a safety generator; (ii) interruption of liquid nitrogen provision; and (iii) computer failure preventing access to the database and blocking material distribution. Minor non-conformities are those that can disrupt an operation but not block it completely, or those that do not affect technical quality of the material. Moderate non-conformities fall in between, such as those that may reduce technical quality of material but not cause it to be inviable, or that may block some operations for only a very short period.
A lab technician will be in charge of cryopreservation processes. Finally, a database manager will ensure that all information on the donor animal (such as species, breed, line, registration number, pedigree information, phenotypic and genomic information) and germplasm (such as viability, number of doses, location in the cryotank) are correctly digitally recorded (see  Section 8). These human resources should be a minimum to operate an animal gene bank adequately, and to efficiently provide services to stakeholders. Flexibility in the availability of the human resources and their responsibilities would help gene banks to anticipate variability in workload during the year. Basic equipment to collect and process germplasm is essential in a cryopreservation lab (see Table  4. 1). These instruments would allow the handling of germplasm and produce doses for storage in liquid nitrogen.
Annual operational budget When planning an operational budget, categories/items should be classified as fixed or variable costs. Fixed costs could be defined as a fixed expense required every year, regardless of the collection and cryopreservation activities in that year. It is important to have long-term commitments of relevant stakeholders to cover the fixed costs and to avoid compromise of the investments done in the previous years. Major categories/items classified as fixed costs are annual costs of cryopreservation lab facilities and cryostorage rooms, salary and overhead of the staff, basic equipment, database, and long-term storage tanks. Gene bank infrastructure requires preventive or corrective maintenance every year. Annual collection and preservation activities hardly influence the salary and overhead of human resources.
A basic framework for evaluating full costs of gene bank operations is presented in  The objectives: 1. Collect sperm or embryos from donations from producers or industries. These donations can be frozen germplasm, or field collections can be organized to capture Canada's animal resources. 2. Determine the genetic diversity of each Canadian breed. 3. Develop a database to record the animals' information, doses and location in the gene bank. Information contained in the database should be accessible to the public.
• Equipment: AnGRC acquired computer-assisted sperm analysis (CASA), a flow cytometer, a genetic sequencer, a straw filler and sealer, a straw printer, a programmable freezer, and several cryotanks for the adequate preservation and quality analyses of the donated germplasm. • Database: AnGRC joined an international group (Brazil, United States of America and Canada) to build a shared database to record the different information. Investment on informatics system and security programs were made to ensure the protection of the data (see Section 8 for more information). • Staff: AnGRC group comprises a curator, a field specialist, a genetic advisor and a programmer. Graduate and summer students help to complete the different AnGRC's preservation activities. (Cont. ) Operational budget: In general, fixed costs represent around 80 percent of the operational budget, while the variable costs are 20 percent.
MoBPS is an R-package to perform stochastic simulation of breeding programmes, and thus assist breeders in evaluating and optimizing their breeding programmes  (Pook, Schlather and Simianer, 2020). Similar to the gene-flow concept introduced by  Hill (1974) , MoBPS allows grouping of individuals into cohorts that have similar characteristics such as age, sex and genetic origin. Thus, MoBPS provides a highly flexible tool to allow detailed modelling of today's complex breeding programmes, which may include cohorts of animals with material stored in gene banks. MoBPS includes a variety of pre-implemented functions for common breeding practices such as optimum genetic contribution selection and estimation of genomic breeding values. Although breeds subject to conservation are often small, MoBPS allows for the simulation of breeding programmes with millions of animals, or population genetic studies with thousands of generations.
This scheme has been successfully simulated with the MoBPS program (see Figure  5. 2). Results showed that the purity of the recreated breed closely followed the expectation for each generation (e. g. 50 percent for BC1, 75 percent for BC2 and 87. 5 percent for BC3, etc. ) with hardly any variance. The input modules in MoBPS allow users to adjust parameters, such as pregnancy and survival rates, to account for differences among species, breeds and production systems. By doing so, gene bank managers can more precisely estimate the quantities of material to be collected for the prevailing circumstances in their country, and even explore the impacts of changing these parameters on the probability of successful breed reconstitution. Such an exercise may be particularly helpful for the development and utilization of collections consisting of older material and/or material from local breeds, for which knowledge about pregnancy and survival rates with cryopreserved material is typically limited.
Different programs are available for optimum contribution selection, and include the free R-package optiSel  (Wellmann, 2019) , the free software EVA  (Berg, Nielsen and Sørensen, 2006) , the free software Gencont  (Meuwissen, 2002)  and the commercial software TGRM  (Kinghorn, 2011). Constraints due to sex and the rate of increase in kinship can influence the results. For example, conserved genetic material can be used for the recovery of "native" genomes of the local breeds that have undergone "upgrading". Many local breeds have been subject to generations of occasional or systematic crossing with other breeds. Continued crossing eventually leads to the genetic extinction of the local breed because the native alleles are lost. To prevent this, breeders (or other stakeholders) may wish to remove the introgressed "foreign" genetic material from the genomes of the local breed as much as possible.
Older individuals of local breeds not only tend to have less foreign genetic material, but the foreign haplotypes also tend to be longer. Long haplotypes can more easily be removed than short haplotypes. The previously conserved genetic material from animals born years ago is therefore of high value for a breeding programme that aims at removing the foreign haplotypes from the population. The objective of such a selection programme could be to maximize the proportion of the local breed genome, while constraining the increase in the average kinship of native alleles below a certain threshold. An alternative is to reduce the frequencies of alleles associated with the foreign breed, while maximizing diversity in the rest of the genome. For both procedures, the R-package optiSel can be used. In many instances, local breeds that have been subject to crossbreeding will not have material from previous generations stored in a gene bank.
For countries that are not concerned with international exchange of germplasm, options for collecting material outside of approved centres are: (i) to use collection centres with lower sanitary standards; (ii) to collect material on farm; or (iii) to use slaughterhouse material. The use of the germplasm collected from these sources may or may not require national derogations for gene bank material. If a derogation is needed, it should state the exceptions from the national regulation and the conditions for collection, testing, storage and use of the material in the legal framework for the country. Utilizing collection centres with lower sanitary requirements may be a satisfactory solution. The sanitary status of each donor should be documented in the collection centre's or gene bank's database and quarantine measures are recommended.
This underlines the need for accurate recording of all necessary information, including sanitary status, in suitable database systems that also allow safe exchange and utilization of the material. International databases such as EUGENA (www. eugena-erfp. net/en/) could be a suitable platform to facilitate bilateral agreements between countries. Section 8 deals with data management in more detail. Finally, the development of new conservation technologies based on the collection of gonadal tissues will require an adaptation of the regulations on animal by-products in Europe, to allow exceptions where the tissues collected are intended for the establishment of germplasm banks. This issue may be pertinent in other countries and regions. A more recent initiative is the Vietnamese-Japanese project "Establishment of a cryobank system for Vietnamese native pig resources and a sustainable production system to conserve biodiversity," running from 2015 to 2020.
CRITICAL ISSUES FOR MANAGEMENT OF GENE BANK DATA Due to the special nature of the biological data, several challenges may be encountered when establishing or revising a scheme for data management for gene banks. General issues regarding management of bio-and gene bank data can be identified and are listed below. While databases and information systems will usually be constructed by professional software developers, it is critical for gene bank managers to drive the process of building the system and be full partners in the development and deployment of the software. They must understand the issues of importance for the software developer, and be able to communicate with the developer regarding to the needs of both the gene bank and its users.
Database technological solutions Database management systems (DBMS) are software packages designed to manage and optimize the storage and retrieval of data from databases. A DBMS provides a systematic approach to manage databases via a user interface. The various options for DBMS vary widely. Different types of software may be necessary to achieve the final desired system. Software options may include free open-access applications, commercial software, or a combination of the two. The decision about the most appropriate DBMS is very important. Development of a functional DBMS implies a substantial investment in time and money, even if free software can be used. The criteria for selecting a DBMS for gene bank data should include: (i) the expected size of the gene bank; (ii) the input mode and data flow that is in place or will be adopted; (iii) the need to export data or subsets of it; and (iv) the needs for linking to external public and private databases.
Definition of data type A formal definition of the data and their properties (often referred to as "attributes" of data), which indicates to the computer compiler how the programmer/provider intends to use the data, must be specified for sample and animal metadata. This document should state the expected format for each data type. This concept can be shown with a few examples: 1. Numeric: a number, with units specified. The database developer must indicate if units are given with or without abbreviations. The use of terms defined in the "Units of measurement ontology" (www. ebi. ac. uk/ols/ontologies/uo) is encouraged (For example, a birth weight could have a value of 1. 3 and the units specified as "kilogram"). 2. Dates: a record of when an event occurred. The format must be described; the use of the following format is recommended, YYYY-MM-DD for dates or YYYY-MM for months.
Genomic data In recent years, several national and international projects (e. g. Bovine HAPMAP Consortium et al. , 2009; Stella et al. , 2018)  have characterized genetic diversity using genotyping and sequencing of thousands of individuals from local, commercial and experimental populations. Much of these data are already in the public domain. Thus, genomic data represent a fundamental feature of samples hosted in gene banks, and should be stored and, when possible, made available to stakeholders in commonly used formats. For storing and exchanging genotype data files, the so-called "PLINK" format has become a universally recognized standard recommended for gene bank databases  (Purcell et al. , 2007). The PLINK files are either a bundle of plain text files or of binary files. Various applications are provided by PLINK to manage the data files and to perform statistical analyses  (Harvard University, 2017).
Genome sequencing data are highly informative, but present significant computing and bioinformatics challenges in terms of data storage capacity, computation time in management, and internet connectivity and bandwidth for transfer of information. The most used format is FASTQ, which is a text-based format for storing both biological sequence information, such as for DNA, and their corresponding quality scores  (Cock et al. , 2010). The massive size of genome data files (genome sequence information of a single animal can contain billions of data points) means that management of genomic data in a local database may prove very inefficient, due to storage and computing capacity limitations. Moreover, more and more frequently, a policy of open data is applied by funding agencies and peer reviewed scientific journals, which requires genomic data to be deposited onto public archives and made available to the scientific community.
MANAGEMENT OF DATA FOR INTERNAL USE The management of data for internal use is mainly concerned with sample retrieval, essential description and storage of technical information for sample management. However, it also provides the basis for data sharing, for querying and analyses that support decision making and optimization. Furthermore, the database should record the information necessary to trace a sample of material from the time of its entry into the gene bank until it exits the bank for utilization, as well as the conditions of its exit and subsequent utilization. Tables 8. 1 and 8. 2 list the information (metadata) regarding donor animals and stored samples, respectively, that should be considered required or recommended for gene banks, irrespective of their size and other characteristics.
DAD-IS and EFABIS-net The Domestic Animal Diversity Information System (DAD-IS) (FAO, 2017a) is not a gene bank database, but it plays an important role for countries undertaking cryoconservation. DAD-IS, developed and maintained by FAO, is the web interface to the Global Databank for Animal Genetic Resources. The European Farm Animal Biodiversity Information System network (EFABIS-net) is the network of European national "nodes" providing unique interfaces to DAD-IS. The DAD-IS holds information on more than 15 000 national breed populations (representing around 8 800 breeds and about 40 species) from 182 countries. The data in DAD-IS include basic information about each breed's physical appearance (including photos) and other defining characteristics, geographic range, history, uses, common management conditions, productive and reproductive performance, population size and any institutional form of management, including breed associations, in situ conservation programmes or gene banks.
Countries lacking gene banks are also requested to explicitly insert this information to eliminate uncertainty regarding the status of their breeds. Gene bank managers should communicate regularly with their respective National Coordinators to provide data on material stored, and thus help improve the quality and quantity of gene bank data in DAD-IS. Insertion of these data is also important for countries to meet their international obligations with respect to monitoring of implementation of the SDGs. DAD-IS includes a web page where all National Coordinators and their contact information are provided  (FAO, 2017b). FAO has recently developed an application programming interface (API) that allows the exchange of data between DAD-IS and other systems. The API will facilitate the transfer of data from national databases to DAD-IS, eliminating the duplication of efforts associated with reporting in both systems.
Animal Genetic Resources Information Network All animal gene banks have the common need to manage information about their respective country's genetic resources. The Agricultural Research Science, research agency of United States Department of Agriculture developed a first version of a database to deal with gene bank information, called Animal GRIN (Germplasm Resources Information Network), in 2001. As time passed, the need for continual evolution and improvement of Animal GRIN, including facilitation of international cooperation, became apparent. In 2006, the programmes for animal genetic resources for food and agriculture in the United States of America, Brazil and Canada formed a consortium to develop, implement and use a common information system to accomplish effective banking of biological material as well as to monitor in situ conservation programmes.
This represented the first time that three countries from different economic blocs have become partners to build a common database for genetic resources. This new information system is recognized today as Animal GRINv. 2 in English and "Alelo Animal" in Portuguese. It serves as a successful example of the type of collaboration encouraged by the Interlaken Declaration on Animal Genetic Resources  (FAO, 2007). Animal GRINv. 2 was developed in a customized way to meet each country's needs. For example, the National Animal Germplasm Program, or NAGP of the United States of America (USDA, 2021) does not include in situ conservation; hence, a live animal database was not part of the initial version of the database. This feature was included in the Animal GRINv. 2, however, to allow Brazilian Agricultural Research Corporation (Embrapa) of Brazil to document the populations being conserved in vivo at their research centres.
Version 2 of the system was implemented after discussions with numerous stakeholders including both traditional and emerging industries dealing with not only traditional livestock, but also aquaculture and honey bee species. The type of information included consists of a strong taxonomic structure, animal identification, pedigrees, germplasm/tissue storage, phenotypic information, descriptors of the production system where the animals were raised and recently, genomic (single nucleotide polymorphism chip data) and geographic coordinates. The database can be publicly viewed, providing real-time access to the database from anywhere in the world. The reports are generated via simple point and click procedures, requiring no prior knowledge of the database. AnGR management tools allow evaluation of the genetic diversity stored in the gene bank and assessment of needs before addition to the collection.
The tools can be used to compare the different countries' collections of the same transboundary breeds, and to develop tools that assist with in situ conservation activities. Another important new and strategic feature implemented in 2021 is the capacity to share data with DAD-IS. The system has different URL for each country, but can be accessed from anywhere in the world: • United States of America: https://agrin. ars. usda. gov/; • Brazil: https://an. cenargen. embrapa. br/database_collaboration_page_dev; and • Canada: https://agriculture. canada. ca/en/agricultural-science-and-innovation/agriculture-and-agri-food-research-centres-and-collections/animal-genetic-resources-canada/ about-animal-genetic-resources-collection.
IMAGE Data Portal In recent years, a large amount of genome sequence and genotyping data have become available through publicly funded research projects and breeding programmes. In addition to the information produced by modern genomic technologies, other types of very valuable information are also available, such as existing gene bank information, GIS data and phenotypic data. Therefore, large research projects, which generate data and information on thousands of samples and individuals, need to properly organize the collection and recording of genotypic and phenotypic data in order to facilitate the submission of these data to public archives/databases. Experience shows that information is often segmented with a lack of direct connection between the different sources of information, which has hampered the full exploitation of the currently available genetic resources.
The solution that was developed comprised the following: • a well-defined metadata ruleset ensuring high quality and comparable data across the diverse collections in different storage formats and languages; • development of a single "Inject tool" helping gene bank managers to enhance, standardize, tag and submit data to a Common Data Pool that integrates all gene bank records from across the Europe; • sustainability by archiving of this data within the BioSamples public archive of EBI; and • a bespoke data portal that integrates gene bank metadata with generated "omics" datasets from within IMAGE, and cross-referencing to other gene bank and breeding database resources from across Europe, such as DAD-IS and EUGENA. Within the data portal, a GIS tool is included to assist the user in identifying/storing the geographical origin of the samples, as well as displaying individual/population genetic parameters and biological attributes through interactive maps.