United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, domain-specific databases, and the top journals compare how much data is in institutional vs. domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

snapshot-tab-pane Data-As-A-Service (DaaS) Market Size 2025-2029The data-as-a-service (daas) market size is valued to increase USD 40.76 billion, at a CAGR of 32.6% from 2024 to 2029. Growing amount of data will drive the data-as-a-service (daas) market.Major Market Trends & InsightsNorth America dominated the market and accounted for a 36% growth during the forecast period.By End-user - BFSI segment was valued at USD 2.53 billion in 2023By Deployment - Cloud segment accounted for the largest market revenue share in 2023Market Size & ForecastMarket Opportunities: USD 620.17 millionMarket Future Opportunities: USD 40757.80 millionCAGR : 32.6%North America: Largest market in 2023Market SummaryThe market represents a dynamic and continually evolving landscape, driven by the increasing demand for data-driven insights and analytics. Core technologies, such as artificial intelligence and machine learning, are revolutionizing the way businesses access and utilize data. DaaS applications span various industries, including healthcare, finance, and retail, enabling organizations to make informed decisions and improve operational efficiency. According to recent estimates, the adoption rate of DaaS is projected to reach 50% by 2025, underscoring its growing importance. Service types range from cloud-based solutions to on-premises offerings, catering to diverse client requirements. Regulatory compliance, such as GDPR and HIPAA, pose challenges for market participants, necessitating robust data security measures. The integration of Data-as-a-Service in blockchain technology is a significant trend, offering enhanced security and transparency. Despite these opportunities, data privacy concerns and the growing amount of data continue to present challenges. The DaaS Market's ongoing evolution reflects the ever-changing needs of businesses in the digital age.What will be the Size of the Data-As-A-Service (DaaS) Market during the forecast period?Get Key Insights on Market Forecast (PDF) Request Free SampleHow is the Data-As-A-Service (DaaS) Market Segmented and what are the key trends of market segmentation?The data-as-a-service (daas) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userBFSIRetailTelecomOthersDeploymentCloudOn-premisesSectorLarge enterprisesSMEsGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW)By End-user InsightsThe bfsi segment is estimated to witness significant growth during the forecast period.In the Business Financial Services Industry (BFSI), Data-as-a-Service (DaaS) is increasingly adopted for creating predictive models in trading, fund management, and risk control. The DaaS market's expansion, in terms of volume, variety, and complexity, enables financial institutions to derive valuable insights, enhancing their operational efficiency. Digital transformation in financial services has led to the evaluation of technology's impact and customer response to streamline financial operations. The financial sector witnesses significant data growth due to increasing financial transaction volumes. Digital marketing advancements and search engine optimization practices have altered consumer behavior, generating a vast amount of actionable data. Real-time data feeds and data warehousing solutions facilitate the processing and storage of this data.Data anonymization methods ensure data privacy, while predictive analytics models and machine learning algorithms help extract valuable insights. Data processing pipelines and data validation techniques ensure data accuracy, and API key management and containerization technologies secure access to this data. Data visualization dashboards and automated data pipelines simplify data analysis, with kubernetes orchestration ensuring scalability. Data access controls, data aggregation services, and data encryption methods secure data, while data transformation tools facilitate data integration. Cloud-based data storage and data security protocols ensure data availability and protection. The DaaS market's growth is evident, with 30% of financial firms adopting DaaS solutions.Furthermore, 45% of financial institutions anticipate a 35% increase in their data usage within the next two years. These statistics underscore the market's potential and the importance of DaaS for financial institutions. Market trends include the adoption of microservices architecture, big data processing, and data modeling techniques. Data version control, data quality metrics, data lineage tracking, and data governance policies ensure data accuracy and consistency. Data lake architectu

The Ultimate Arabic News Dataset is a collection of single-label modern Arabic texts that are used in news websites and press articles.

Arabic news data was collected by web scraping techniques from many famous news sites such as Al-Arabiya, Al-Youm Al-Sabea (Youm7), the news published on the Google search engine and other various sources.

• The data we collect consists of two Primary files:

UltimateArabic: A file containing more than 193,000 original Arabic news texts, without pre-processing. The texts contain words, numbers, and symbols that can be removed using pre-processing to increase accuracy when using the dataset in various Arabic natural language processing tasks such as text classification.

UltimateArabicPrePros: It is a file that contains the data mentioned in the first file, but after pre-processing, where the number of data became about 188,000 text documents, where stop words, non-Arabic words, symbols and numbers have been removed so that this file is ready for use directly in the various Arabic natural language processing tasks. Like text classification.

• We add two samples of data collected by web scraping techniques:

Sample_Youm7_Politic: An example of news in the "Politic" category collected from the Youm7 website.

Sample_alarabiya_Sport: An example of news in the "Sport" category collected from the Al-Arabiya website.

• The data is divided into 10 different categories: Culture, Diverse, Economy, Sport, Politic, Art, Society, Technology, Medical and Religion.

Personal Data Removal Services Market Outlook

As per our latest research, the global personal data removal services market size reached USD 1.65 billion in 2024, reflecting a robust momentum driven by increasing privacy concerns and stringent data protection regulations worldwide. The market is exhibiting a strong CAGR of 18.2% and is forecasted to reach USD 8.17 billion by 2033. This remarkable growth is underpinned by rising consumer awareness about digital footprints, a surge in cyber threats, and evolving regulatory frameworks mandating stricter data privacy compliance for organizations and individuals alike.

The primary growth driver for the personal data removal services market is the exponential rise in data breaches and cyber-attacks, which have significantly heightened the need for robust data privacy solutions. Organizations and individuals are increasingly realizing the risks associated with personal data exposure, including identity theft, financial loss, and reputational damage. This awareness, coupled with the proliferation of digital platforms and social networks, has led to a higher demand for services that can effectively remove or anonymize personal information from online databases, directories, and search engines. Businesses are also leveraging these services to comply with regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), which enforce strict guidelines for data handling and deletion, further accelerating market adoption.

Technological advancements and the integration of artificial intelligence (AI) and machine learning (ML) have also catalyzed the growth of the personal data removal services market. AI-powered solutions enable automated identification and removal of personal information across a multitude of online sources, enhancing efficiency and accuracy. These innovations have made it easier for service providers to offer scalable, customizable, and cost-effective solutions to a diverse client base. As the digital ecosystem continues to expand with the Internet of Things (IoT), wearable devices, and smart applications, the volume of personal data generated and stored online is expected to surge, further fueling the demand for comprehensive data removal services.

Another significant growth factor is the rising emphasis on consumer rights and transparency in data usage. Governments and regulatory bodies across the globe are enacting new laws and updating existing frameworks to empower individuals with greater control over their personal data. This shift is compelling organizations to adopt personal data removal services as a proactive measure to build trust with customers, avoid legal penalties, and maintain a positive brand image. The increasing adoption of remote work and digital transactions in the post-pandemic era has also contributed to the marketÂ’s expansion, as both enterprises and individuals seek to safeguard sensitive information from unauthorized access.

Takedown Services have become increasingly vital in the realm of personal data removal, providing a crucial layer of protection against unauthorized online content. These services specialize in identifying and removing unwanted or harmful information from the internet, which can include anything from defamatory content to unauthorized personal data. As the digital landscape becomes more complex, individuals and businesses are finding it challenging to manage their online presence effectively. Takedown Services offer a proactive approach to maintaining privacy and reputation by swiftly addressing potential threats. By collaborating with legal experts and leveraging advanced technology, these services ensure that sensitive information is not only removed but also prevented from resurfacing, thereby offering peace of mind to clients concerned about their digital footprint.

Regionally, North America continues to dominate the personal data removal services market, accounting for the largest share in 2024, followed by Europe and the Asia Pacific. The presence of leading technology firms, early adoption of privacy-centric solutions, and stringent regulatory requirements have cemented North America's leadership position. EuropeÂ’s growth is propelled by the enforcement of GDPR and a strong culture of data privacy, while the Asia Pacific is witnessing rapid expansion due to

A set of online services created in support of MIRIAM, a set of guidelines for the annotation and curation of computational models. The core of MIRIAM Resources is a catalogue of data types (namespaces corresponding to controlled vocabularies or databases), their URIs and the corresponding physical URLs or resources. Access to this data is made available via exports (XML) and Web Services (SOAP). MIRIAM Resources are developed and maintained under the BioModels.net initiative, and are free for use by all. MIRIAM Resources are composed of four components: a database, some Web Services, a Java library and this web application. * Database: The core of the system is a MySQL database. It allows us to store the data types (which can be controlled vocabularies or databases), their URIs and the corresponding physical URLs, and other details such as documentation and resource identifier patterns. Each entry contains a diverse set of details about the data type: official name and synonyms, root URI, pattern of identifiers, documentation, etc. Moreover, each data type can be associated with several resources (or physical locations). * Web Services: Programmatic access to the data is available via Web Services (based on Apache Axis and SOAP messages). In addition, REST-based services are currently being developed. This API allows one to not only resolve model annotations, but also to generate appropriate URIs, based upon the provision of a resource name and accession number. A list of available web services, and a WSDL are provided. A browser-based online demonstration of the Web Services is also available to try. * Java Library: A Java library is provided to access the Web Services. The documentation explains where to download it, its dependencies, and how to use it. * Web Application: A Web application, using an Apache Tomcat server, offers access to the whole data set via a Web browser. It is possible to browse by data type names as well as browse by tags. A search engine is also provided.

snapshot-tab-pane Library Management Software Market Size 2025-2029The library management software market size is forecast to increase by USD 871 million, at a CAGR of 6.5% between 2024 and 2029.The market is experiencing significant growth, driven by the increasing demand for efficient and technological solutions in managing library resources. This trend is particularly prominent in the Asia Pacific region, where the expanding education sector and growing literacy rates are fueling the need for advanced library management systems. Another key driver is the adoption of Virtual Reality (VR) and Augmented Reality (AR) technologies in libraries, enabling immersive learning experiences and enhancing user engagement. However, the market also faces challenges, including the growing concerns about data security and privacy, as libraries house vast amounts of sensitive information.Addressing these challenges through robust security measures and data encryption techniques will be crucial for market players seeking to capitalize on the opportunities presented by this dynamic market. Companies must remain agile and innovative to meet the evolving needs of libraries and adapt to the latest technological trends.What will be the Size of the Library Management Software Market during the forecast period?Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report. Request Free SampleThe market continues to evolve, driven by the dynamic needs of various sectors. Library statistics are integrated into comprehensive systems, enabling data analytics for informed decision-making. Library web services offer seamless access to library catalogs, ensuring user-friendly search experiences. Circulation management and digital archives facilitate efficient resource sharing and preservation. Patron engagement is enhanced through digital library platforms, accessibility features, and user interface design. Metadata management, including cataloging rules and metadata standards, ensures accurate and consistent data. Digital literacy initiatives and resource sharing through metadata harvesting and interlibrary loan further expand library offerings. Library instruction, collection development, and database access are crucial components, while digital asset management and discovery services streamline library operations.User analytics and subject headings provide valuable insights for collection development and research support. Electronic resource management, electronic journals, and subscription models enable cost-effective access to vast amounts of information. Classification systems and patron management tools streamline library operations and improve user experience. On-premise and cloud-based library software solutions cater to diverse organizational needs. Search engine optimization and bibliographic data management optimize library services for discoverability. Ongoing advancements in library management software reflect the continuous evolution of the information landscape.How is this Library Management Software Industry segmented?The library management software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. DeploymentCloud-basedOn-premisesEnd-userSchool libraryPublic libraryAcademic libraryOthersSectorSMEsLarge enterprisesTypeCataloging and classificationCirculation and patron managementReference and researchAnalytics and reportingPrice RangeSubscription-basedPerpetual licenseGeographyNorth AmericaUSCanadaEuropeFranceGermanyThe NetherlandsUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW). By Deployment InsightsThe cloud-based segment is estimated to witness significant growth during the forecast period.In today's digital age, cloud-based library management software has gained significant traction among end-users due to its accessibility and ease of use. Unlike traditional on-premise software, cloud-based applications require only a web browser and an Internet connection, eliminating the need for a powerful local server and substantial upfront investment. The subscription model allows for predictable expenses, with costs covering maintenance and upgrades instead of a large initial payment. This shift towards cloud-based solutions is driven by the widespread use of the Internet and the benefits it offers, including scalability, reduced costs, and easy upgrades. Library management software encompasses various functionalities, such as library statistics, catalogs, circulation management, digital archives, digital preservation, patron engagement, accessibility features, metadata management, digital library, c