Amazon principal applied scientist Jens Lehmann, top right, received the Semantic Web journal 10-year award for “LinkedGeoData: A Core for a Web of Spatial Open Data” -- the paper's abstract is seen on the left. Lehmann’s coauthors are Claus Stadler, top left, a researcher at the Institute for Applied Informatics at the University of Leipzig; Konrad Höffner, bottom left, a researcher at the Institute for Medical Informatics, Statistics and Epidemiology; and Sören Auer, bottom right, director of Leibniz Information Centre for Science and Technology and professor at Leibniz University Hannover.
Amazon principal applied scientist Jens Lehmann, top right, received the Semantic Web journal 10-year award for “LinkedGeoData: A Core for a Web of Spatial Open Data". Lehmann’s coauthors are Claus Stadler, top left, a researcher at the Institute for Applied Informatics at the University of Leipzig; Konrad Höffner, bottom left, a researcher at the Institute for Medical Informatics, Statistics and Epidemiology; and Sören Auer, bottom right, director of Leibniz Information Centre for Science and Technology and professor at Leibniz University Hannover.

Jens Lehmann receives Semantic Web journal 10-year award for influential paper

The work of Lehmann and three co-authors helped demonstrate the feasibility of large-scale virtual knowledge graphs.

Amazon principal applied scientist Jens Lehmann and three coauthors recently received the Semantic Web journal 10-year award for their paper “LinkedGeoData: A Core for a Web of Spatial Open Data.”

The Semantic Web journal is a leading journal for knowledge graphs and web technologies. Its editorial board, including editors-in-chief Pascal Hitzler and Krzysztof Janowicz, selected the award-winning paper from a pool of papers published in 2012.

Lehmann’s coauthors are Claus Stadler, a researcher at the Institute for Applied Informatics at the University of Leipzig; Konrad Höffner, a researcher at the Institute for Medical Informatics, Statistics and Epidemiology (IMISE); and Sören Auer, director of Leibniz Information Centre for Science and Technology and professor at Leibniz University Hannover.

The paper helped demonstrate the feasibility of large-scale virtual knowledge graphs by describing a large-scale dataset derived from OpenStreetMap, a collaborative project that relies on a community of mappers to contribute and maintain data as part of a free geographic database of the world. It significantly expanded on an earlier version of the paper published at the International Semantic Web Conference (ISWC) in 2009, where it attracted attention from various stakeholders like Tim Berners-Lee — the inventor of the World Wide Web.

There were several reasons why the dataset got attention in the scientific community. One reason was the scale of several billion facts when performing a full extraction, which means it was one of the largest datasets at the time.
Jens Lehmann

“There were several reasons why the dataset got attention in the scientific community,” Lehmann said. “One reason was the scale of several billion facts when performing a full extraction, which means it was one of the largest datasets at the time. Another reason was the lightweight ontology layer we put on top of it, which simplified querying the dataset and the development of applications.”

Furthermore, connecting the data to DBpedia — a crowdsourced effort to extract structured content from various Wikimedia projects — and other datasets allowed users to fuse information from multiple sources, Lehmann said.

For publishing and querying the dataset, the authors’ rewriting approach transformed incoming queries in a language called SPARQL to queries over the underlying OpenStreetMap database. This made it possible to publish a virtual knowledge graph (VKG) over a relational database without requiring a change in the database itself. It also allowed live synchronization of the knowledge graph, which was important because OpenStreetMap could have thousands of changes per minute.

The main challenge for VKGs is to allow efficient querying without changing the underlying structure. LinkedGeoData uses the Sparqlify approach (or its distributed version, Sparklify) to address this challenge. More recently, LinkedGeoData added support for the Ontop rewriter as an alternative. Both specifically support querying using spatial predicates.

The full dataset contains around 8 billion entities and is several terabytes large, a challenging amount of data to handle. A dump that was extracted around the time the paper was published in 2012 contained 27 billion facts, surpassing the size of the Google Knowledge Graph at that time. For users who wish to work on smaller subsets — such as for particular regions or with a focus on certain spatial elements—there are filtering strategies to obtain snapshots for particular use cases.

LinkedGeoData uses the resource description framework (RDF) data model and includes links to other knowledge graphs. It has served as a resource for spatial entity linking, entity alignment, and topological relation discovery. The query logs of LinkedGeoData have also been used for various analytical tasks. Using the latest rewriter, researchers can build data snapshots for their own use cases and query them efficiently using SPARQL and its extension, OGC GeoSPARQL.

See some of Amazon's research centers in Germany

Lehmann joined Amazon in June of 2022 as an Alexa AI principal scientist. Based at Amazon’s office in Dresden, Germany, Lehmann works on the inclusion of knowledge graphs in machine learning and approaches toward building generalized intelligence for making Alexa more competent and natural for customers.

Apart from LinkedGeoData, Lehmann has cofounded and contributed to further knowledge graph projects, such as DBpedia. He has won 15 other best-paper awards for various contributions in artificial intelligence.

“I am interested in building intelligent systems combining knowledge graphs and machine learning,” says Lehmann. “Doing this at scale and ensuring that it is done in a way that is beneficial for Amazon customers is a big motivation for my work at Alexa AI.”

Related content

US, WA, Seattle
Note that this posting is for a handful of teams within Amazon Robotics. Teams include: Robotics, Computer Vision, Machine Learning, Optimization, and more.Are you excited about building high-performance robotic systems that can perceive and learn to help deliver for customers? The Amazon Robotics team is creating new science products and technologies that make this possible, at Amazon scale. We work at the intersection of computer vision, machine learning, robotic manipulation, navigation, and human-robot interaction.Amazon Robotics is seeking broad, curious applied scientists and engineering interns to join our diverse, full-stack team. In addition to designing, building, and delivering end-to-end robotic systems, our team is responsible for core infrastructure and tools that serve as the backbone of our robotic applications, enabling roboticists, applied scientists, software and hardware engineers to collaborate and deploy systems in the lab and in the field. We will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Come join us!A day in the lifeAs an intern you will develop a new algorithm to solve one of the challenging computer vision and manipulation problems in Amazon's robotic warehouses. Your project will fit your academic research experience and interests. You will code and test out your solutions in increasingly realistic scenarios and iterate on the idea with your mentor to find the best solution to the problem.
US, WA, Bellevue
The Global Supply Chain-ACES organization aims to raise the bar on Amazon’s customer experience by delivering holistic solutions for Global Customer Fulfillment that facilitate the effective and efficient movement of product through our supply chain. We develop strategies, processes, material handling and technology solutions, reporting and other mechanisms, which are simple, technology enabled, globally scalable, and locally relevant. We achieve this through cross-functional partnerships, listening to the needs of our customers and prioritizing initiatives to deliver maximum impact across the value chain. Within the organization, our Quality team balances tactical operation with operations partners with global engagement on programs to deliver improved inventory accuracy in our network. The organization is looking for an experienced Principal Data Scientist to partner with senior leadership to develop long term strategic solutions. As a Principal Scientist, they will lead critical initiatives for Global Supply Chain, leveraging complex data analysis and visualization to:a. Collaborate with business teams to define data requirements and processes;b. Automate data pipelines;c. Design, develop, and maintain scalable (automated) reports and dashboards that track progress towards plans;d. Define, track and report program success metrics.e. Serve as a technical science lead on our most demanding, cross-functional projects.
US, MA, North Reading
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. The Research Science team at Amazon Robotics is seeking interns with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects, including allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, and learning how to grasp all the products Amazon sells. We are seeking internship candidates with backgrounds in computer vision, machine learning, resource allocation, discrete optimization, search, planning/scheduling, and reinforcement learning. As an intern you will develop a new algorithm to solve one of the challenging computer vision and manipulation problems in Amazon's robotic warehouses. Your project will fit your academic research experience and interests. You will code and test out your solutions in increasingly realistic scenarios and iterate on the idea with your mentor to find the best solution to the problem.
US, WA, Seattle
Are you excited about building high-performance robotic systems that can perceive, learn, and act intelligently alongside humans? The Robotics AI team is creating new science products and technologies that make this possible, at Amazon scale. We work at the intersection of computer vision, machine learning, robotic manipulation, navigation, and human-robot interaction.The Amazon Robotics team is seeking broad, curious applied scientists and engineering interns to join our diverse, full-stack team. In addition to designing, building, and delivering end-to-end robotic systems, our team is responsible for core infrastructure and tools that serve as the backbone of our robotic applications, enabling roboticists, applied scientists, software and hardware engineers to collaborate and deploy systems in the lab and in the field. Come join us!
US, WA, Bellevue
Employer: Amazon.com Services LLCPosition: Research Scientist IILocation: Bellevue, WA Multiple Positions Available1. Research, build and implement highly effective and innovative methods in Statistical Modeling, Machine Learning, and other quantitative techniques such as operational research and optimization to deliver algorithms that solve real business problems.2. Take initiative to scope and plan research projects based on roadmap of business owners and enable data-driven solutions. Participate in shaping roadmap for the research team.3. Ensure data quality throughout all stages of acquisition and processing of the data, including such areas as data sourcing/collection, ground truth generation, data analysis, experiment, evaluation and visualization etc.4. Navigate a variety of data sources, understand the business reality behind large-scale data and develop meaningful science solutions.5. Partner closely with product or/and program owners, as well as scientists and engineers in cross-functional teams with a clear path to business impact and deliver on demanding projects.6. Present proposals and results in a clear manner backed by data and coupled with conclusions to business customers and leadership team with various levels of technical knowledge, educating them about underlying systems, as well as sharing insights.7. Perform experiments to validate the feature additions as requested by domain expert teams.8. Some telecommuting benefits available.The pay range for this position in Bellevue, WA is $136,000-$184,000 (yr); however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided by the Washington Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.#0000
US, VA, Arlington
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. As Director for PXT Central Science Technology, you will be responsible for leading multiple teams through rapidly evolving complex demands and define, develop, deliver and execute on our science roadmap and vision. You will provide thought leadership to scientists and engineers to invent and implement scalable machine learning recommendations and data driven algorithms supporting flexible UI frameworks. You will manage and be responsible for delivering some of our most strategic technical initiatives. You will design, develop and operate new, highly scalable software systems that support Amazon’s efforts to be Earth’s Best Employer and have a significant impact on Amazon’s commitment to our employees and communities where we both serve and employ 1.3 million Amazonians. As Director of Applied Science, you will be part of the larger technical leadership community at Amazon. This community forms the backbone of the company, plays a critical role in the broad business planning, works closely with senior executives to develop business targets and resource requirements, influences our long-term technical and business strategy, helps hire and develop engineering leaders and developers, and ultimately enables us to deliver engineering innovations.This role is posted for Arlington, VA, but we are flexible on location at many of our offices in the US and Canada.
US, VA, Arlington
Employer: Amazon.com Services LLCPosition: Data Scientist IILocation: Arlington, VAMultiple Positions Available1. Manage and execute entire projects or components of large projects from start to finish including data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.2. Oversee the development and implementation of data integration and analytic strategies to support population health initiatives.3. Leverage big data to explore and introduce areas of analytics and technologies.4. Analyze data to identify opportunities to impact populations.5. Perform advanced integrated comprehensive reporting, consultative, and analytical expertise to provide healthcare cost and utilization data and translate findings into actionable information for internal and external stakeholders.6. Oversee the collection of data, ensuring timelines are met, data is accurate and within established format.7. Act as a data and technical resource and escalation point for data issues, ensuring they are brought to resolution.8. Serve as the subject matter expert on health care benefits data modeling, system architecture, data governance, and business intelligence tools. #0000
US, TX, Dallas
Employer: Amazon.com Services LLCPosition: Data Scientist II (multiple positions available)Location: Dallas, TX Multiple Positions Available:1. Assist customers to deliver Machine Learning (ML) and Deep Learning (DL) projects from beginning to end, by aggregating data, exploring data, building and validating predictive models, and deploying completed models to deliver business impact to the organization;2. Apply understanding of the customer’s business need and guide them to a solution using AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances;3. Use Deep Learning frameworks like MXNet, PyTorch, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help our customers build DL models;4. Research, design, implement and evaluate novel computer vision algorithms and ML/DL algorithms;5. Work with data architects and engineers to analyze, extract, normalize, and label relevant data;6. Work with DevOps engineers to help customers operationalize models after they are built;7. Assist customers with identifying model drift and retraining models;8. Research and implement novel ML and DL approaches, including using FPGA;9. Develop computer vision and machine learning methods and algorithms to address real-world customer use-cases; and10. Design and run experiments, research new algorithms, and work closely with engineers to put algorithms and models into practice to help solve customers' most challenging problems.11. Approximately 15% domestic and international travel required.12. Telecommuting benefits are available.#0000
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLECompany: AMAZON.COM SERVICES LLCPosition Title: Manager III, Data ScienceLocation: Bellevue, WashingtonPosition Responsibilities:Manage a team of data scientists working to build large-scale, technical solutions to increase effectiveness of Amazon Fulfillment systems. Define key business goals and map them to the success of technical solutions. Aggregate, analyze and model data from multiple sources to inform business decisions. Manage and quantify improvement in the customer experience resulting from research outcomes. Develop and manage a long-term research vision and portfolio of research initiatives, with algorithms and models that to be integrated in production systems. Hire and mentor junior scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
US, VA, Arlington
MULTIPLE POSITIONS AVAILABLECompany: AMAZON.COM SERVICES LLCPosition Title: Data Scientist IILocation: Arlington, VirginiaPosition Responsibilities:Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000