The web screen scraping tools market, valued at $2831.7 million in 2025, is projected to experience robust growth, driven by the escalating demand for real-time data across diverse sectors. The market's Compound Annual Growth Rate (CAGR) of 4.6% from 2025 to 2033 indicates a steady expansion, fueled primarily by the increasing adoption of data-driven decision-making in e-commerce, investment analysis, and the burgeoning cryptocurrency industry. The "Pay-to-Use" segment currently dominates, reflecting businesses' preference for reliable, feature-rich solutions. However, the "Free-to-Use" segment shows promising growth potential, particularly among smaller businesses and individual developers seeking cost-effective data extraction solutions. Geographic growth is expected to be broad, with North America and Europe maintaining significant market share, while the Asia-Pacific region presents considerable untapped potential due to increasing digitalization and e-commerce adoption. Competitive pressures amongst established players like Import.io, Scrapinghub, and Apify are driving innovation and improvements in ease-of-use, data accuracy, and scalability. The market faces challenges related to legal and ethical concerns surrounding data scraping, as well as the ongoing evolution of website structures that can render scraping tools ineffective, necessitating constant updates and adaptations. The sustained growth trajectory of the web screen scraping tools market is anticipated to continue due to several factors. Firstly, the increasing complexity of data management across various sectors necessitates efficient data acquisition tools. Secondly, the expansion of e-commerce and the growth of the global digital economy fuels demand for accurate, up-to-date product information and market intelligence. Thirdly, the rise of big data analytics and the associated need for large datasets will continue to propel the adoption of web screen scraping solutions. The evolving regulatory landscape regarding data scraping will necessitate solutions that emphasize ethical and compliant data acquisition practices. This will drive innovation within the industry towards more responsible and robust web scraping tools that cater to the needs of businesses while respecting data privacy and copyright regulations. This will also favor the development of specialized tools optimized for specific sectors such as finance and e-commerce, rather than universal solutions.

description: Resources for Advanced Data Analysis and VisualizationResearchers who have access to the latest analysis and visualization tools are able to use large amounts of complex data to find efficiencies in projects, designs, and resources. The Data Analysis and Assessment Center (DAAC) at ERDC's Information Technology Laboratory (ITL) provides visualization and analysis tools and support services to enable the analysis of an ever-increasing volume of data.Simplify Data Analysis and Visualization ResearchThe resources provided by the DAAC enable any user to conduct important data analysis and visualization that provides valuable insight into projects and designs and helps to find ways to save resources. The DAAC provides new tools like ezVIZ, and services such as the DAAC website, a rich resource of news about the DAAC, training materials, a community forum and tutorials on how to use data analysis and other issues.The DAAC can perform collaborative work when users prefer to do the work themselves but need help in choosing which visualization program and/or technique and using the visualization tools. The DAAC also carries out custom projects to produce high-quality animations of data, such as movies, which allow researchers to communicate their results to others.Communicate Research in ContextDAAC provides leading animation and modeling software which allows scientists and researchers may communicate all aspects of their research by setting their results in context through conceptual visualization and data analysis.Success StoriesWave Breaking and Associated Droplet and Bubble FormationWave breaking and associated droplet and bubble formation are among the most challenging problems in the field of free-surface hydrodynamics. The method of computational fluid dynamics (CFD) was used to solve this problem numerically for flow about naval vessels. The researchers wanted to animate the time-varying three-dimensional data sets using isosurfaces, but transferring the data back to the local site was a problem because the data sets were large. The DAAC visualization team solved the problem by using EnSight and ezVIZ to generate the isosurfaces, and photorealistic rendering software to produce the images for the animation.Explosive Structure Interaction Effects in Urban TerrainKnown as the Breaching Project, this research studied the effects of high-explosive (HE) charges on brick or reinforced concrete walls. The results of this research will enable the war fighter to breach a wall to enter a building where enemy forces are conducting operations against U.S. interests. Images produced show computed damaged caused by an HE charge on the outer and inner sides of a reinforced concrete wall. The ability to quickly and meaningfully analyze large simulation data sets helps guide further development of new HE package designs and better ways to deploy the HE packages. A large number of designs can be simulated and analyzed to find the best at breaching the wall. The project saves money in greatly reduced field test costs by testing only the designs which were identified in analysis as the best performers.SpecificationsAmethyst, the seven-node Linux visualization cluster housed at the DAAC, is supported by ParaView, EnSight, and ezViz visualization tools and configured as follows:Six computer nodes, each with the following specifications:CPU: 8 dual-core 2.4 Ghz, 64-bit AMD Opteron Processors (16 effective cores)Memory: 128-G RAMVideo: NVidia Quadro 5500 1-GB memoryNetwork: Infiniband Interconnect between nodes, and Gigabit Ethernet to Defense Research and Engineering Network (DREN)One storage node:Disk Space: 20-TB TerraGrid file system, mounted on all nodes as /viz and /work; abstract: Resources for Advanced Data Analysis and VisualizationResearchers who have access to the latest analysis and visualization tools are able to use large amounts of complex data to find efficiencies in projects, designs, and resources. The Data Analysis and Assessment Center (DAAC) at ERDC's Information Technology Laboratory (ITL) provides visualization and analysis tools and support services to enable the analysis of an ever-increasing volume of data.Simplify Data Analysis and Visualization ResearchThe resources provided by the DAAC enable any user to conduct important data analysis and visualization that provides valuable insight into projects and designs and helps to find ways to save resources. The DAAC provides new tools like ezVIZ, and services such as the DAAC website, a rich resource of news about the DAAC, training materials, a community forum and tutorials on how to use data analysis and other issues.The DAAC can perform collaborative work when users prefer to do the work themselves but need help in choosing which visualization program and/or technique and using the visualization tools. The DAAC also carries out custom projects to produce high-quality animations of data, such as movies, which allow researchers to communicate their results to others.Communicate Research in ContextDAAC provides leading animation and modeling software which allows scientists and researchers may communicate all aspects of their research by setting their results in context through conceptual visualization and data analysis.Success StoriesWave Breaking and Associated Droplet and Bubble FormationWave breaking and associated droplet and bubble formation are among the most challenging problems in the field of free-surface hydrodynamics. The method of computational fluid dynamics (CFD) was used to solve this problem numerically for flow about naval vessels. The researchers wanted to animate the time-varying three-dimensional data sets using isosurfaces, but transferring the data back to the local site was a problem because the data sets were large. The DAAC visualization team solved the problem by using EnSight and ezVIZ to generate the isosurfaces, and photorealistic rendering software to produce the images for the animation.Explosive Structure Interaction Effects in Urban TerrainKnown as the Breaching Project, this research studied the effects of high-explosive (HE) charges on brick or reinforced concrete walls. The results of this research will enable the war fighter to breach a wall to enter a building where enemy forces are conducting operations against U.S. interests. Images produced show computed damaged caused by an HE charge on the outer and inner sides of a reinforced concrete wall. The ability to quickly and meaningfully analyze large simulation data sets helps guide further development of new HE package designs and better ways to deploy the HE packages. A large number of designs can be simulated and analyzed to find the best at breaching the wall. The project saves money in greatly reduced field test costs by testing only the designs which were identified in analysis as the best performers.SpecificationsAmethyst, the seven-node Linux visualization cluster housed at the DAAC, is supported by ParaView, EnSight, and ezViz visualization tools and configured as follows:Six computer nodes, each with the following specifications:CPU: 8 dual-core 2.4 Ghz, 64-bit AMD Opteron Processors (16 effective cores)Memory: 128-G RAMVideo: NVidia Quadro 5500 1-GB memoryNetwork: Infiniband Interconnect between nodes, and Gigabit Ethernet to Defense Research and Engineering Network (DREN)One storage node:Disk Space: 20-TB TerraGrid file system, mounted on all nodes as /viz and /work

A publicly-accessible website to measure and visualize similarities and differences between molecular profiles of complex microbial communities. The project includes visualization tools such as heat maps that simultaneously compare the taxonomic distributions of multiple datasets and 3-D charts of the frequency distributions of 16S rRNA tags. Analytical tools include Chao diversity estimates and rarefaction curves. As a service to the community, researchers have the opportunity to upload their own data to the site for private viewing with the full range of data and analysis tools. Public data can be downloaded for further analysis locally.

G-Protein-coupled receptors (GPCRs) are an important superfamily of transmembrane proteins involved in cellular communication. Recently, it has been shown that dimerization is a widely occurring phenomenon in the GPCR superfamily, with likely important physiological roles. Here we use a novel hidden-site class model of evolution as a sequence analysis tool to predict possible dimerization interfaces in GPCRs. This model aims to simulate the evolution of proteins at the amino acid level, allowing the analysis of their sequences in an explicitly evolutionary context. Applying this model to aminergic GPCR sequences, we first validate the general reasoning behind the model. We then use the model to perform a family specific analysis of GPCRs. Accounting for the family structure of these proteins, this approach detects different evolutionarily conserved and accessible patches on transmembrane (TM) helices 4−6 in different families. On the basis of these findings, we propose an experimentally testable dimerization mechanism, involving interactions among different combinations of these helices in different families of aminergic GPCRs.

This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source software was Optional DLG-3 and the conversion software was ARC/INFO 6.1.2. For documentation refer to USGS Data Users Guide 4, National Mapping Program, Technical Instructions, 1986, Reston, VA. These data are processed in 1:250,000 scale map units, therefore file size varies for each map unit. chaco Mesa was processed at 1:100,000 scale.

This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source software was Optional DLG-3 and the conversion software was ARC/INFO 6.1.2. For documentation refer to USGS Data Users Guide 4, National Mapping Program, Technical Instructions, 1986, Reston, VA. These data are processed in 1:250,000 scale map units, therefore file size varies for each map unit. chaco Mesa was processed at 1:100,000 scale.

This paper explores tool-using activities undertaken in and around the earliest known evidence of post-built structures in Britain. Microwear results associated with at least three structures identified at the Early Mesolithic site of Star Carr, North Yorkshire, are examined as a means of identifying activity zones associated with the diverse stone tools used to process a variety of materials (e.g. wood, bone, antler, plant, hide, meat, fish). With 341 lithic artefacts analysed, this research represents the first microwear study focused on the post-built structures at Star Carr. A combination of spatial and microwear data has provided different scales of interpretation: from individual tool use to patterns of activity across the three structures. Different types of tool use observed have aided interpretations of possible activity areas where objects were produced and materials were processed. Zones of activity within one of the structures suggest that the working of some materials was more spatially restricted than others; even where there are high densities of flint deposition, spatial patterns in tool-using activity were observed. From this, it is interpreted that social norms and behaviours influenced the spatial organisation of different spaces. Our results demonstrate the importance of combining microwear analysis with GIS to explore function and variability in the use of Mesolithic structures—providing new insights into their role as social spaces.

This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source software was Optional DLG-3 and the conversion software was ARC/INFO 6.1.2. For documentation refer to USGS Data Users Guide 4, National Mapping Program, Technical Instructions, 1986, Reston, VA. These data are processed in 1:250,000 scale map units, therefore file size varies for each map unit. chaco Mesa was processed at 1:100,000 scale.

Protein function is a direct consequence of its sequence, structure, and the arrangement at the binding site. Bioinformatics using sequence analysis is typically used to gain a first insight into protein function. Protein structures, on the other hand, provide a higher resolution platform into understanding functions. As the protein structural information is increasingly becoming available through experimental structure determination and through advances in computational methods for structure prediction, the opportunity to utilize these data is also increasing. Structural analysis of small molecule ligand binding sites in particular provides a direct and more accurate window to infer protein function. However, it remains a poorly utilized resource due to the huge computational cost of existing methods that make large-scale structural comparisons of binding sites prohibitive. Here, we present an algorithm called FLAPP that produces very rapid atomic level alignments. By combining clique matching in graphs and the power of modern CPU architectures, FLAPP aligns a typical pair of binding sites at ∼12.5 ms using a single CPU core, ∼1 ms using 12 cores on a standard desktop machine, and performs a PDB-wide scan in 1–2 min. We perform rigorous validation of the algorithm at multiple levels of complexity and show that FLAPP provides accurate alignments. We also present a case study involving vitamin B12 binding sites to showcase the usefulness of FLAPP for performing an exhaustive alignment-based PDB-wide scan. We expect that this tool will be invaluable to the scientific community to quickly align millions of site pairs on a normal desktop machine to gain insights into protein function and drug discovery for drug target and off-target identification and polypharmacology.