Parcels and buildings as well as spatial data from the #Address Register have proved a hit with users since the opening of high-value datasets in #Lithuania. Published by the Registrų centras - State Enterprise Centre of Registers - the high-value datasets have been opened for re-use and are believed to be of particular importance for the development of value-added services. “The first datasets were opened by the Centre of Registers five years ago and, in the meantime, data from all the registers and information systems we administer have been opened to the public. With this opening of high-value datasets, we are implementing the objectives set out in the Open Data Strategy of the Centre of Registers and the provisions of the European Union directive, while contributing to the development of digital innovations and advanced services,” says Adrijus Jusas, Director General of the Centre of Registers. The Centre of Registers opened its first datasets to the public in 2019 attracting nearly 65,000 unique with a total of almost 2.2 million downloads. In 2024, a substantial increase in use was reported with as many downloads as in the period 2019 to 2023. Currently, everyone can use the data of the Real Property Register, the Register of Legal Entities, the Address Register, the Population Register, the Information System of Legal Entities Participants, the Register of Contracts and Restrictions on Rights, the Information System of Licenses, the Information System of Lists of the Members of Political Parties, and the e-Prescription subsystem free of charge. Data from the Address Register, the Register of Legal Entities and the Real Property Register attract the greatest interest of users. The data can be found here: https://lnkd.in/eRJ_fb_A #OpenData #HVD #Geospatial #MapsForEurope
EuroGeographics’ Post
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This weekend, I will be at FOSDEM and I will talk on Saturday at 17.45 CET at the #OpenResearch devroom about Wikirate's Beyond Compliance project and how crowdsource research is driving the fight against #modernslavery. If you're passionate about open data and corporate accountability, drop me a message or catch me after my talk on Saturday. Would love to chat! #FOSDEM2025 #OpenData #CorporateAccountability #ModernSlavery #CrowdsourcedResearch
Join Vasiliki Gkatziaki this Saturday, February 1, at 17:45 CET at FOSDEM 2025! Our Data Engineer will be speaking at the #OpenResearch #Devroom, exploring how #opendata and crowdsourced research are revolutionizing corporate accountability in the fight against #modernslavery. 🔍 What to expect? Vasiliki will showcase how the Wikirate platform enables large-scale assessment of #ModernSlaveryAct statements, helping researchers, activists, and organizations move beyond compliance to drive real change. 📅 Don’t miss it! 🗒️ Session details: https://lnkd.in/dfQ-5wff 📺 Watch live: https://lnkd.in/ds5bVqJ3 Let us know in the comments if you’ll be tuning in! #FOSDEM2025 #OpenData #CorporateAccountability #ModernSlavery #CrowdsourcedResearch
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It is my honor to announce that our article is one of the the most cited articles in the last 3 years in World Scientific according to Crossref data.
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SEMCOG has recently launched a new economic development and placemaking tool to assist our local communities with understanding location and foot traffic. https://lnkd.in/g733x9mz #econdev
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Our paper (with Ewa Dobrowolska) in Scientific Reports on the design of the 'Quality of Life Index' (QOLI) based on OpenStreetMap data is already online! Easy to replicate in R (see Github), powerful in checking if a city is '15 minutes city'. https://lnkd.in/dChMZ9Nr
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Thanks to OEGlobal for alerting me to this mapping project. OpenHistoricalMap is an interactive map of the world throughout history, created by people like you and dedicated to the public domain. OpenHistoricalMap is built by a community of mappers and historians that contribute and maintain data about the history of the world. OpenHistoricalMap is about historical data. Things that used to be there. From a variety of sources, contributed by mappers and historians across the world. OpenHistoricalMap’s community is diverse, passionate, and growing every day. Our contributors include enthusiast mappers, academics, digital historians, historical societies, and many more. To learn more about the community, see the user diaries etc OpenHistoricalMap is open data: you are free to use it for any purpose under the terms of the data you are using. OpenHistoricalMap identifies license and citation requirements at the object level (if any). Credit or citation to OpenHistoricalMap for consolidating this data is appreciated, but not required. If you alter or build upon the data in certain ways, you may distribute the result only under the same licence. See the Copyright and License page for details. Where is it?: https://lnkd.in/gpW9bUNh
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Live now: Panel Discussion: A Vision for Open Source in Europe #LFEUROPEMEMBERSUMMIT
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This interactive map shows you the most famous person from every single city, town and village around the world, revealing the birthplaces of some of the most famous human beings to have ever lived. The data is based on this study of notable people, which gave a ‘notability ranking’ to a whole load of famous peeps who lived between 3500BC and 2018. https://lnkd.in/gfZW6QWn The study of notable people: Laouenan, M., Bhargava, P., Eyméoud, JB. et al. A cross-verified database of notable people, 3500BC-2018AD. Sci Data 9, 290 (2022). https://lnkd.in/gnb6eKvK
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Missing relation prediction in knowledge graph using local and neighbour aware entity embedding In the world of knowledge graphs (KGs), uncovering hidden connections between entities is crucial. Traditional methods for relation prediction can become cumbersome for large KGs. This paper proposes a novel method called Local and Neighbor Aware Entity Embedding (LNAEE) for efficient relation prediction. LNAEE tackles this challenge with a two-pronged approach: 1. Capturing local entity features using skip-gram initialization. 2. Incorporating the influence of neighboring entities through an attention mechanism. This not only improves prediction accuracy but also reduces the relation search space, making LNAEE a lightweight and efficient solution. Explore the full paper: https://lnkd.in/drC5953b #KnowledgeGraph #RelationPrediction #LNAEE
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What does a course covering the fundamentals of #GIS look like when adapted to a web-centric approach? 💻 This article explores sharing and presenting information: https://ow.ly/5Ayo50TnO5C . #ModernGIS @GISEd
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The Yamas and Niyamas blog post
The Yamas and Niyamas blog post https://lnkd.in/g-FEH4tG
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