市场调查报告书
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1494876
到 2030 年科学资料管理系统的市场预测:按组件、部署类型、组织规模、最终用户和区域进行全球分析Scientific Data Management System Market Forecasts to 2030 - Global Analysis By Component (Hardware, Software and Services), Deployment Mode, Organization Size, End User and By Geography |
根据 Stratistics MRC 的数据,2024 年全球科学资料管理系统市场规模为 1.61 亿美元,预计到 2030 年将达到 15.666 亿美元,预测期内复合年增长率为 46.1%。
科学资料管理系统 (SDMS) 是一个整合平台,旨在有效管理、储存和搜寻科学资料。促进实验室产生的大量资料的无缝收集、处理和共用,确保资料和可存取性。 SDMS 的主要功能包括从各种装置资料撷取、元资料註释以及对多种资料格式的支援。它还具有强大的搜寻功能、版本控制和符合监管标准。 SDMS 支援资料生命週期管理,从原始资料撷取到分析和长期存储,确保资料始终可用且可追溯。
根据美国国家医学图书馆报道,2020年3月,上海交通大学医学院附属上海总医院宣布开展总体基因体学二代定序技术精准治疗感染患者的病原菌确定及疗效评估第4阶段。此类临床试验会产生大量需要安全储存解决方案的关键科学资料,从而推动了市场需求。
增加研究活动和资料生成
随着各个科学领域研究的加速,产生的资料量呈指数级增长,需要强大的系统来进行高效的资料管理、储存和分析。 SDMS 解决方案提供资料整合、即时存取和安全储存等关键功能,使其在现代研究环境中至关重要。资料密集型研究的激增,特别是在基因组学、製药和环境科学等领域,正在推动对先进 SDMS 处理复杂资料集的需求。
实施和维护 SDMS 成本高昂
购买、客製化和整合 SDMS 解决方案的初始成本可能很高,使得预算有限的中小型研究和学术机构难以实施。此外,与软体更新、系统维护和员工培训相关的持续成本也增加了财务负担。对于某些组织来说,这些成本可能超过了预期的效益,导致他们不愿意实施 SDMS。由于这些系统的复杂性,它们通常需要专门的 IT 支持,从而进一步增加营运成本。
资料安全、合规性和协作的需求
敏感的研究资料需要强而有力的保护,SDMS 提供存取控制和加密等功能,以确保符合 HIPAA 和 GDPR 等法规。此外,合作在现代研究中也很重要。 SDMS 充当集中式平台,允许地理上分散的团队无缝共用和分析资料。这促进了更快的科学进步和创新。随着研究变得更加复杂,对安全和协作资料管理的需求预计将继续推动 SDMS 市场向前发展。
缺乏标准化
在不同的研究环境中部署 SDMS 解决方案时,缺乏普遍接受的资料格式、通讯协定和互通性标准会产生整合和相容性问题。标准化的缺乏使不同系统之间的资料共用、协作和无缝资讯交流变得复杂,并降低了研究效率和生产力。此外,缺乏标准化的资料管治框架可能会导致资料品质、完整性和安全性不一致,从而削弱对 SDMS 解决方案的信任。
COVID-19 的影响
随着研究机构优先考虑远端协作和资料共用,COVID-19 大流行加速了科学资料管理系统 (SDMS) 的采用。由于对实验室和研究设施的实体存取受到限制,对促进远端资料存取和协作的云端基础的SDMS 解决方案的需求激增。此外,疫情凸显了资料完整性和安全性的重要性,促使研究机构投资强大的 SDMS 平台,以确保合规性并保护敏感的研究资料。儘管面临经济挑战,但对高效资料管理解决方案支援偏远地区研究活动的需求推动了大流行期间 SDMS 市场的成长。
预计硬体领域将在预测期内成为最大的领域
由于高效能伺服器、储存系统和网路设备能够实现高效的资料储存、搜寻和共用,预计硬体在预测期内将达到高峰。此外,图形处理单元 (GPU) 和现场可程式闸阵列 (FPGA) 等专用硬体加速器可增强复杂资料分析任务的运算能力。硬体技术的进步,包括处理能力、储存容量和网路频宽的提高,正在推动创新并促进更强大和可扩展的 SDMS 解决方案的开发。
预计云端基础的细分市场在预测期内将出现最高的复合年增长率。
透过利用云端基础设施,公司可以储存、处理和分析大量科学资料,而无需在硬体或IT基础设施基础设施上进行大量前期投资。云端基础的SDMS 解决方案可实现无缝协作、随时随地即时存取资料,并透过强大的加密和存取控制来增强资料安全性。此外,云端平台的可扩展性使公司能够轻鬆适应波动的资料量和运算要求,从而提高科学研究的效率和创新。
由于其较高的数位素养和促进科学资料管理系统采用的法规,预计北美在预测期内将占据最大的市场占有率。此外,TIBCO Software 和 Abbott Laboratories 等重要市场参与企业的存在也支持了市场成长。此外,在当前的 COVID-19 大流行期间,美国政府正在积极致力于保持科学研究设施之间的安全距离。预计这将增加对安全储存和管理科学资料并减少劳动力的科学资料管理系统的需求。
由于实验室自动化支出增加以及医疗保健行业采用技术先进的设备,预计亚太地区在预测期内将保持最高的复合年增长率。此外,由于政府资助和倡议的增加,对科学资料管理系统和软体的需求也在增加。这些疾病的高盛行率在涉及寻找这些疾病的可行治疗方法的实验室中产生了大量资料。
According to Stratistics MRC, the Global Scientific Data Management System Market is accounted for $161.0 million in 2024 and is expected to reach $1566.6 million by 2030 growing at a CAGR of 46.1% during the forecast period. A Scientific Data Management System (SDMS) is an integrated platform designed to manage, store, and retrieve scientific data efficiently. It facilitates the seamless collection, processing, and sharing of large volumes of data generated by research laboratories, ensuring data integrity and accessibility. Key features of an SDMS include data capture from various instruments, metadata annotation, and support for diverse data formats. It also provides robust search functionalities, version control, and compliance with regulatory standards. It supports data lifecycle management, from raw data acquisition to analysis and long-term archival, ensuring data is consistently available and traceable.
According to the U.S. National Library of Medicine in March 2020, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, initiated a phase-4 clinical trial to determine the pathogen and efficacy evaluation of Metagenomics second generation sequencing technology for precision therapy on the infected patients. These clinical trials also generate significant amount of crucial scientific data that requires secure storage solutions thereby, driving the demand for the market.
Increased research activity and data generation
As research in various scientific fields accelerates, the volume of data generated rises exponentially, necessitating robust systems for efficient data management, storage, and analysis. SDMS solutions offer critical functionalities such as data integration, real-time access, and secure storage, making them indispensable for modern research environments. The surge in data-intensive research, particularly in fields like genomics, pharmaceuticals, and environmental sciences, amplifies the demand for advanced SDMS to handle complex datasets.
Implementing and maintaining SDMS can be expensive
The high initial costs of purchasing, customizing, and integrating SDMS solutions can deter small to mid-sized research organizations and academic institutions with limited budgets. Additionally, ongoing expenses related to software updates, system maintenance, and staff training add to the financial burden. These costs may outweigh perceived benefits for some organizations, leading to resistance in adopting SDMS. The complexity of these systems often requires specialized IT support, further increasing operational expenses.
Need for data security, compliance, and collaboration
Sensitive research data requires robust protection, and SDMS offer features like access controls and encryption to ensure compliance with regulations like HIPAA and GDPR. Additionally, collaboration is crucial in modern research. SDMS act as centralized platforms, enabling geographically spread teams to seamlessly share and analyze data. This fosters faster scientific progress and innovation. As research complexity grows, the demand for secure and collaborative data management will continue to propel the SDMS market forward.
Lack of Standardization
Without universally accepted standards for data formats, protocols, and interoperability, integration and compatibility issues arise when implementing SDMS solutions across different research environments. This lack of standardization complicates data sharing, collaboration, and the seamless exchange of information between disparate systems, hindering research efficiency and productivity. Furthermore, the absence of standardized data governance frameworks can lead to inconsistencies in data quality, integrity, and security, eroding trust in SDMS solutions.
Covid-19 Impact
The COVID-19 pandemic has accelerated the adoption of Scientific Data Management Systems (SDMS) as research organizations prioritize remote collaboration and data sharing. With restrictions on physical access to laboratories and research facilities, demand for cloud-based SDMS solutions surged to facilitate remote data access and collaboration. Additionally, the pandemic highlighted the importance of data integrity and security, prompting organizations to invest in robust SDMS platforms to ensure compliance and protect sensitive research data. Despite economic challenges, the need for efficient data management solutions to support remote research activities has bolstered the growth of the SDMS market during the pandemic.
The hardware segment is expected to be the largest during the forecast period
The hardware is expected to be the largest during the forecast period owing to high-performance servers, storage systems, and networking equipment enable efficient data storage, retrieval, and sharing. Additionally, specialized hardware accelerators, such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs), enhance computational capabilities for complex data analysis tasks. Advancements in hardware technology, including increased processing power, storage capacity, and network bandwidth, drive innovation and enable the development of more robust and scalable SDMS solutions.
The cloud-based segment is expected to have the highest CAGR during the forecast period
The cloud-based segment is expected to have the highest CAGR during the forecast period, by leveraging cloud infrastructure, organizations can store, process, and analyze vast amounts of scientific data without the need for significant upfront investments in hardware and IT infrastructure. Cloud-based SDMS solutions enable seamless collaboration, real-time access to data from anywhere, and enhanced data security through robust encryption and access controls. Moreover, the scalability of cloud platforms allows organizations to easily accommodate fluctuating data volumes and computational requirements, driving efficiency and innovation in scientific research.
North America is projected to hold the largest market share during the forecast period because of its high digital literacy and rules that promote the adoption of a scientific data management system. Also, the presence of significant market players in the regions, such as TIBCO Software and Abbott Laboratories, is fueling the market growth. In addition, amid the current COVID-19 epidemic, the US government has aggressively concentrated on keeping safe-distance even among scientific research facilities. This is expected to increase demand for scientific data management systems to securely store and manage scientific data while reducing the requirement for labor.
Asia Pacific is projected to hold the highest CAGR over the forecast period due to growing expenditures in the healthcare industry for lab automation and the adoption of technologically advanced equipment. Also, the need for scientific data management system software is increasing as a result of rising government financing and positive initiatives. The high prevalence of these disorders creates a massive quantity of data across the research laboratories involved in discovering viable treatments for the condition.
Key players in the market
Some of the key players in Scientific Data Management System market include Abbott Laboratories, Accelerated Technology Laboratories Inc, Advanced Chemistry Development, Inc, Bellefleur Physiotherapy, Benchling, Bon Secours Health System, Inc., Dassault Systemes SE, Flywheel.io, LabVantage Solutions Inc, LabWare, MediaLab, Inc, Merck KGaA, SciCord LLC, Shimadzu Corporation, Sutter Health, Thermo Fisher Scientific Inc, TIBCO Software Inc, Uncountable Inc. and SuVitas
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