Core Viewpoint - The National Bureau of Statistics and the State Administration for Market Regulation have introduced measures to enhance the efficiency of data circulation and transactions by releasing model contracts for data circulation transactions [1] Group 1: Data Circulation Transaction Measures - The initiative aims to address the low efficiency of data circulation and transaction processes [1] - Model contracts have been published to serve as a reference for businesses in need [1] Group 2: Typical Data Circulation Scenarios - There are four typical scenarios for data circulation transactions: 1. Data providers supplying data to data recipients 2. Data entrustors handing over data to data trustees for processing 3. Multiple parties collaborating on data fusion and development 4. Data intermediaries facilitating data circulation transactions [1]

Core Viewpoint - The article discusses the launch of a new global scientific literature data platform, dbdata.com, created by Chinese institutions, aimed at providing high-quality research support and reducing reliance on Western-dominated databases [2][3]. Group 1: Platform Overview - The dbdata.com platform includes nearly 90 million high-quality scientific literature metadata and incorporates AI functionalities to enhance research efficiency [2]. - The platform's basic features will be available for free to global users, facilitating literature retrieval, citation analysis, and data tracking [2]. Group 2: Issues with Existing Databases - The most widely used scientific literature database globally is Web of Science, which has over 100 million entries but suffers from issues such as manipulation of citation metrics, affecting the objectivity and accuracy of research evaluations [3]. - The existing citation evaluation system has not seen substantial improvements in 70 years, leading to the inclusion of many low-quality papers, which diminishes the academic value of the database [3]. Group 3: Dongbi Index - The platform is based on the Dongbi Index, a new evaluation standard developed by a team of young scientists, which aims to provide a more objective and accurate reflection of journal authority and impact [4]. - The Dongbi Index incorporates a quality grading system and a citation tracing method, moving beyond the traditional reliance on citation counts [4]. Group 4: Classification System - The platform has developed a classification system aligned with the habits of Chinese researchers, using the classification codes from the National Natural Science Foundation and the Ministry of Education, which are not represented in Web of Science [4]. - This classification system helps researchers understand their academic boundaries and provides precise decision-making support for management departments [4]. Group 5: AI Integration - The platform has integrated AI capabilities, including "scholar achievement interpretation" and "automatic review generation," effectively providing users with an "AI assistant" for research inquiries [5]. - Users can interact with the AI to obtain insights into scholars' research directions, characteristics, and contributions [5].

Group 1 - The core viewpoint of the news is the emphasis on the "Data Element ×" initiative, which aims to enhance data utilization and governance, particularly in emergency management and various industries [1][3][5] - The "Data Element ×" competition for 2025 will focus on three main topics in emergency management: improving safety production supervision capabilities, enhancing natural disaster monitoring and assessment capabilities, and advancing the intelligence level of emergency management [4][5] - The initiative is supported by a significant number of central enterprises, with nearly 500 digital technology companies established and about 66% of industry leaders having purchased data, indicating a growing enthusiasm for data development and utilization [1][2] Group 2 - Data is increasingly recognized for its multiplier effect, with examples showing that large enterprises in the industrial sector have reduced product development cycles by over 30% and inventory cycles from 3 months to 1 month through data integration [2] - In agriculture, data utilization has led to a 5.5% increase in crop yields and a 5.3-fold increase in marine biological resources in aquaculture [2] - The "Data Element ×" initiative will also focus on creating a unified data market and governance system to foster a more vibrant market environment, encouraging participation from various stakeholders [3][5]

Group 1 - The China Internet Association announced the establishment of two group standards, including the "Management Specifications for Recommendation Algorithms of Internet Platform Enterprises," which outlines management requirements for recommendation algorithms [1] - The State Administration for Market Regulation approved the release of seven national standards related to emerging industries such as artificial intelligence, information technology, and the Internet of Things, providing technical support for digital services and applications [2] - The first batch of 10 science and technology innovation bond ETFs was approved, with various fund companies tracking different indices related to technology innovation bonds [3] Group 2 - A globally independent scientific literature data platform was launched, collecting nearly 90 million high-quality scientific literature metadata, aiming to break the Western monopoly in this field [4] - The Ministry of Education is promoting a "Double Thousand" plan to enhance employment capabilities, focusing on artificial intelligence and other key areas, with 2,654 micro-specialties set up for the 2025 graduating class [5] - The Ministry of Education is implementing employment assistance programs for disadvantaged groups, including those from poverty-stricken families and zero-employment households, with nearly 10,000 students matched with support services [7][8] Group 3 - A 10 billion yuan humanoid robot industry investment fund has been established in Hubei Province, focusing on humanoid robots and artificial intelligence-related core sectors [9] - The Longhua District of Shenzhen is increasing support for mergers and acquisitions to enhance key technology levels, encouraging upstream and downstream mergers within the industrial chain [10] - Sichuan Province plans to implement policies to promote high-quality development of the platform economy, particularly in e-commerce, and accelerate the development of innovative AI products [11] Group 4 - The global DRAM market is expected to reach a historical high, with a 47.7% increase in the market price index from the beginning of 2025, driven by AI-related memory upgrades and strong demand [6]

标普道琼斯指数：美国数据服务公司Datadog将取代Juniper Network加入标普500指数。 ...

Group 1: Company Overview - The company initially conducted its own research to gather data due to limited data availability, but has since evolved to leverage data collection as a key service in the big data era, providing comprehensive data support to clients [2] - The core competitive advantage lies in the ability to quickly identify client needs and establish methodologies for model building, utilizing machine learning and natural language processing technologies [3] Group 2: Business Strategy and Model Development - The company is transitioning from manual data analysis to automated analysis, enhancing model innovation capabilities to address unique problems with tailored models [3] - The strategic development of software business focuses on modeling business experience, algorithm development, and software implementation [2] Group 3: Technology Implementation and Client Solutions - The company has developed responsive algorithm models for specific scenarios, such as the "12345 Government Service Hotline," which can be generalized to other service areas [4] - Various self-service analysis tools have been created, including visualization dashboards and automated reporting, to facilitate client analysis in both commercial and governmental sectors [4] Group 4: Knowledge Graph and Large Model Integration - The integration of knowledge graphs and large models enhances decision-making capabilities, addressing issues like high costs and low coverage in knowledge graph updates [5] - The company aims to leverage the combined strengths of knowledge graphs and large models to capture opportunities in sectors such as government, finance, and insurance [5] Group 5: Application of Knowledge Graphs - The experience in constructing ontologies in specialized fields can be adapted to civilian applications, improving policy recommendation accuracy in government sectors [5] - The knowledge graph technology accumulated in specialized fields will support the company's expansion into government, finance, and insurance sectors [5]

Core Insights - The 2025 Global Digital Economy Conference focused on "Deepening Big Data Value to Stimulate New Momentum in the Digital Economy" and highlighted five key initiatives that span from policy frameworks to technological platforms, showcasing the progress and future direction of data element reforms [1] Group 1: Key Initiatives - The Beijing Artificial Intelligence Data Application Development Platform was launched, featuring a comprehensive five-layer architecture that supports the entire data lifecycle from collection to model development, aimed at enhancing AI applications through a common technology platform [3] - The Beijing Economic and Technological Development Zone introduced a new data industry policy, emphasizing five core plans to eliminate barriers in data allocation, strengthen technological innovation, activate data circulation value, cultivate industrial clusters, and build a diverse ecosystem [3] - The upgraded version 3.0 of the Beijing Artificial Intelligence Data Sandbox was released, marking a transition from pilot projects to scalable and replicable models, with partnerships established with 12 leading companies across various sectors [4] Group 2: Infrastructure and Support - The Beijing (International) Data Annotation Base was officially launched, focusing on cutting-edge fields such as autonomous driving and intelligent manufacturing, aiming to create a national-level data annotation headquarters and research center [4] - The Dbdata Global Technology Literature Data Platform was introduced, featuring nearly 90 million high-quality scientific literature metadata, providing efficient literature retrieval and citation analysis services for the global research community [4] - The Deputy Director of the Beijing Economic and Information Technology Bureau outlined four strategic areas for future development, including innovation leadership, focus on key industries, infrastructure enhancement, and promoting digital economy integration [5]

Core Insights - The global technology literature data platform "Dongbi" was launched during the 2025 Global Digital Economy Conference, aiming to support high-quality scientific research through efficient literature retrieval, citation analysis, and data tracking services [1][3]. Group 1: Platform Features - The platform includes nearly 90 million high-quality scientific literature metadata and incorporates AI functionalities [1][3]. - It is designed to be free for global users, enhancing accessibility to scientific resources [1]. - The platform utilizes a new "seed journal citation tracing + citation network hierarchical structure" theory to create the "Dongbi Index," which provides a more objective and accurate reflection of journal authority and influence [3]. Group 2: Importance and Impact - The platform is considered a "data foundation" for scientific research, crucial for improving research efficiency and ensuring technological security in China [3][4]. - It serves as a cornerstone for evaluating scientific journals and is seen as a vital channel for the internationalization of Chinese scientific journals [4]. - The introduction of AI features, such as "scholar achievement interpretation" and "automatic review generation," aims to lower the barriers to understanding academic papers [4][5]. Group 3: Future Developments - The platform is currently in its initial version, with plans for rapid iteration to enhance its capabilities in providing high-quality scientific literature data services globally [5].

Core Insights - The launch of the Dongbi Global Scientific Literature Data Platform aims to provide a comprehensive resource for researchers, featuring nearly 90 million high-quality scientific literature metadata, with basic functionalities available for free to global users [1][4]. Group 1: Platform Overview - The platform is developed based on an evaluation index system proposed by Chinese institutions, focusing on self-collected and processed scientific literature data [1][4]. - It offers efficient literature retrieval, citation analysis, and data tracking services to facilitate research work [1]. Group 2: Importance of the Platform - The establishment of a globally influential scientific literature data platform is recognized as essential for supporting various research activities and enhancing the efficiency of scientific work [4]. - The platform is seen as a foundational infrastructure for scientific research, playing a crucial role in improving research efficiency and ensuring scientific security [4]. Group 3: Strategic Implications - The platform is expected to encourage significant research outcomes to be published and utilized in domestic journals and platforms, aligning with the consensus in the Chinese scientific community [4]. - A platform with independent intellectual property rights is considered vital for creating a domestic scientific journal evaluation system and for the internationalization of scientific journals, contributing significantly to building world-class scientific journals in China [4].

智通财经7月1日电，数据标注公司SURGE AI寻求至多10亿美元的资本募集。 ...