nyuuzyou/wikis huggingface dataset:
Solid Amsterdam Meetup – 6 oktober 2022

Organisatie: Jeroen van Beele (guts2trust) & Pieter van Everdingen (PLDN)
Datum en Tijd: Donderdag 6 oktober 2022, 14:00 - 17:00
Locatie: Op Suyd, De Pleinzaal, Stadionplein 300, 1076 CK Amsterdam
Op donderdag 6 oktober van 14:00-17:00 uur organiseert Jeroen van Beele in samenwerking met PLDN de volgende Solid Amsterdam Meetup. Door de Corona hebben de fysieke lokale Meetups in Nederland een tijdje on hold gestaan. Maar in die tussentijd zijn er zowel in Belgie als in Nederland een aantal interessante ontwikkelingen geweest die we graag met u willen delen.
De slides van de presentaties van deze meetup zijn toegevoegd aan het programma hieronder en onder het programma zijn nog een aantal referenties opgenomen met de belangrijkste links naar een aantal bronnen die tijdens de meetup aan bod zijn gekomen..
==Programma==
Tijd 	Titel
14:00	Welkom + intro – Jeroen van Beele (guts2trust)
14:05	SolidLab Flanders – Esther de Loof (UGent/imec/SolidLab Flanders) ()
14:30	De Komst van Persoonlijke Datakluizen met Solid in Vlaanderen – Dorien Bauwens (Digitaal Vlaanderen) ()
14:55	Solid en use.id: Bundel je digitale leven, neem het in eigen handen en deel het met anderen – Wouter Janssens (Digita) ()
15:20	Pauze
15:40	Solid as foundation for Digital Heritage Networks – Miel Vander Sande (meemoo) ()
16:05	Solid Servers en Services: een praktijk overzicht, dingen die wij als Muze gedaan hebben om het Solid Protocol in de praktijk te brengen - Ben Peachey (Muze) (slides)
16:30	Meest-kansrijke Solid Use Cases – Discussie en vervolgstappen (allen)
16:55	Afronding – Jeroen & Pieter van Everdingen (PLDN)
17:00	Borrel
==Referenties==
Digitaal Vlaanderen
* Het Vlaams Datanutsbedrijf
* Open Standaarden voor Linkende Organisaties (OSLO) (met o.a. vocabulaires en applicatieprofielen)
Flanders Technology & Innovation
* Flanders Technology & Innovation (the big picture)
SolidLab Flanders
* SolidLab Flanders
* Challenges op GitHub
Universiteit Gent/imec (aantal Linked Data en Solid-gerelateerde activiteiten)
* Community Solid Server
* Comunica
* Linked Data Event Streams (LDES)
* Event Notifications in Value-Adding Networks (o.a. samen met meemoo)
Partners in het ecosysteem in Belgie (selectie)
* Digita
* Konsolidate
* Data Village
Partners in het ecosysteem in Nederland
* Muze
* PDS Interop
* Triply
Solid Christmas Meetup Enschede - How to Fix the Internet

__NOTOC__
 Organized by: IEBIS - University of Twente and Platform Linked Data Netherlands
Date: Friday December 20th, 2019
Time: 13:45 - 17:00 (16:30 drinks) 
Location: Campus University of Twente, Enschede 
Registration: Registration form
More information: Erwin Folmer (Erwin.folmer@utwente.nl)
==Description==
As Sir Tim Berners-Lee (inventor of the World Wide Web) already pointed out: The Web is broken, but he has a plan to fix it. It’s called Solid. Solid is an exciting new project led by Prof. Tim Berners-Lee taking place at MIT (Massachusetts Institute of Technology). The project aims to radically change the way Web applications work today, resulting in true data ownership as well as improved privacy.
One of the key members in this MIT group is prof. Ruben Verborgh (professor of Decentralized Web technology at Ghent University and research affiliate at MIT) and Ruben will come to Enschede to lead this meetup on Solid.
This session will be a mandatory lecture for master BIT students (BPIL-course) of the University of Twente. But because of our excitement about the topic and speaker we have decided to open the session for everyone who is interested, but registration is required as spaces are limited. 
The first part of the session will explain why the Web is broken, and will explain the Solid project, its underlying philosophy, and its future plans. The second part will consist of a hands-on tutorial on how to build Solid apps. 
In this second part of the session, you will learn the basics of developing decentralized apps for the Solid ecosystem. With nothing but a text editor and a browser, we will bring a small JavaScript application to life. You will learn how Linked Data is used to make different data pods interoperable, and how we can combine information from different sources at runtime. No developer expertise is required. 
If you want to know more about these exciting new developments on the Web, but don’t want to build a Solid app: Please join us in the first part of the session.
It will be an exciting way to start the Christmas holidays!
===More information on Solid=== 
Within Solid, decentralization means choice: being able to choose where you store your data, independently of the services you want on top of that data. On today’s Web, applications happily take our data in exchange for functionality, but we lose control over what happens to it. Moreover, because data is coupled to the service, we cannot share data across social network boundaries. In Solid, you instead remain the data owner: you decide for every single piece of data you produce where you want to store it. Applications can request permission to specific parts of people’s data, which they combine at runtime into a personal experience. 
===Links===
* https://solid.mit.edu/
* https://solidproject.org/ (new Solid Project organization web site)
* https://www.inrupt.com/blog/one-small-step-for-the-web
Spatial Data on The Web Event 10 February 2016

Location: RCE Amersfoort, The Netherlands
Program: 
Photo impression: Spatial Data on The Web Event
==Presentations==
* - Erwin Folmer (Kadaster)
* - Frans Knibbe (Geodan)
* - Ingo Simonis (OGC)
Block 1 - OGC/W3C Spatial Data on the Web (Linda van den Brink)
* - Jeremy Tandy (MET Office)
* - Linda van den Brink (Geonovum)
Block 2 - Platform Linked Data The Netherlands (Erwin Folmer)
* - Erwin Folmer (Kadaster)
* Topography as Linked Data ( & ) - Peter Lentjes (Kadaster)
* Linked Data for Cultural Heritage - Menno den Engelse (RCE)
* - Paul Janssen (Geonovum)
Block 3 - Linked Data European Initiatives (Dorus Kruse)
* - Jon Blower (University of Reading)
* - Dumitru Roman (Sintef)
* - Michael Lutz (JRC)
* (NEW version) - Andrea Perego (JRC)
* - Dorus Kruse (Kadaster)
* The GeoKnow project ( & GEM video) - Sebastian Hellmann (University of Leipzig)
Block 4 - EuroSDR Developments (Benedicte Bucher)
* - Benedicte Bucher (IGN)
* - Esa Tiainen (National Land Survey Finland)
* - Lars Hägg (Lantmäteriet)
* - Abdelfettah Feliachi, (IGN-F)
* - Eero Hietanen (National Land Survey Finland)
Closing announcements
* - Sebastian Hellman (University of Leipzig)
* - Richard Nagelmaeker (Smart Data Group)
==Original Announcement==
In the last two decades, location data has undergone many evolutions, due among other reasons to the development of the web. Many initiatives, related to the theme of Geodata on the Web, are currently on the go. This event will discuss the latest state of the art, both from the GIS perspective as well as the Web world. We bring together the Linked Data and GIS communities for a fruitful discussion of current and future steps to be taken. 
 
The event is co-organized by EuroSDR, Platform Linked Data The Netherlands (PLDN), OGC/W3C Spatial Data on The Web Workgroup and the European Projects: ELF, proDataMarket, Melodies, GEISER and IQMulus.
 
Registration is free of charge, and is open at the following link: Registration form
And on February 11th there will be an EuroSDR workshop on the same topic at the Kadaster in Amsterdam. See for the program (see page 2). For registration and questions, please send an e-mail to benedicte.bucher@ign.fr
Spatial Data on The Web Event 10 February 2016 Photo Impression

The RCE building on the right
Erwin Folmer (Kadaster)
Frans Knibbe (Geodan)
Coffee break
Igno Simonis (OGC)
Question for the audience
Sebastian Hellman (University of Leipzig)
Another break
Eero Hietanen (National Land Survey Finland)
Smart Data Group announcement by:
- Richard Nagelmaeker (Smart Data Group/BlueSky)
- Lieke Verhelst (Smart Data Group/Linked Data Factory)
- Pieter van Everdingen (Smart Data Group/OpenInc)
- Pano Maria (Smart Data Group/Taxonic)
Spatial Data on The Web Event 10 februari 2016

Locatie: RCE Amersfoort
Programma: 
Aanmelden: Inschrijvingsformulier
Logistiek: 
==Aankondiging==
In de afgelopen twee decennia heeft locatie data vele evoluties ondergaan, ook door andere redenen dan de ontwikkeling van het internet. Een groot aantal initiatieven die met geo data bezig zijn, zijn momenteel actief. Tijdens dit evenement worden de laatste ontwikkelingen gepresenteerd op het gebied van GIS en het internet. We brengen de leden van de Linked Data en de GIS communities bij elkaar om zinvolle discussies met elkaar te hebben over de huidige en toekomstige stappen die genomen moeten worden. 
Dit evenement wordt georganiseerd door EuroSDR, Platform Linked Data Nederland (PLDN), OGC/W3C Spatial Data on The Web Workgroup en de Europese Projecten: ELF, proDataMarket, Melodies, GEISER and IQMulus.
Er zijn geen inschrijvingskosten aan dit evenement verbonden en inschrijven kan via het volgende inschrijvingsformulier.
 
En op 11 februari zal er een EuroSDR workshop zijn over hetzelfde onderwerp bij het Kadaster in Amsterdam. Zie voor het programma: (zie pagina 2). Registreren en vragen stellen over deze workshop kan door een e-mail te sturen naar benedicte.bucher@ign.fr
Speed Dating

===Speed Dating @ PLDN Conference June 27th===
A major element of the PLDN Conference will be speed dating between knowledge suppliers and knowledge seekers, with the goal of creating matched couples who will explore their shared interests and seek for further collaboration. 
Each knowledge supplier and seeker can pitch the knowledge (supplier) or the problem /case (seeker) at the main stage. Afterwards, everybody can select his or her top 3 potential partners for dating. The organization committee will then set up a program of 3 rounds of speed dates. If there is a match, both partners fill in the available form in which they declare to work together on a proposal of 1-2 pages to be sent to the committee within 4 weeks after the event. It is expected that the knowledge supplier will invest a minimum of 2 days (but better 4 days) to work on the project. The Platform Linked Data Netherlands provides every selected successful match with a gift of 500 or 1000 euro. The committee will select about 10 proposals, and maybe more depending on the strength and amount of the proposals. The proposal needs to address the workload of both knowledge supplier and seeker, and how the 500 or 1000 EUR will be used. Potential usage is for instance to cover working hours of the knowledge suppliers, but also to cover costs for creating communication materials. 
Although we will accept (if space allows) on-site registrants, we encourage you to register yourself as knowledge supplier or seeker by simply sending an e-mail with your name, organization and role (seeker/supplier) to p.vaneverdingen@geonovum.nl.
Potential knowledge suppliers are PhD Students, knowledge institutes and consultants (including ZZP-ers). Knowledge seekers have a problem, but no (or part) of the solution. You are willing to invest and also to share insights of the problem situation with the knowledge supplier.
This is a unique opportunity to meet interesting partners for further collaboration without barriers!
===The organization committee===
Linda van den Brink, Kathrin Dentler, Erwin Folmer, Rinke Hoekstra
Sponsorship Packages

Brochure: and (PDF).
Het Platform Linked Data Nederland (PLDN) is een actieve open innovatie community, dat kennis en ervaring deelt over het maken, beheren en toepassen van Linked (Open) Data. Onze ambitie is begrip en het gebruik van Linked Data op een hoger plan te brengen door:
* Organiseren van evenementen op locatie bij een van onze sponsororganisaties
* Faciliteren van werkgroepen (Geo, Federatie van Catalogi, Referentiedata, Erfgoed, Play-a-LOD, Linked Bier, Solid)
* Produceren van publicaties over Linked Data aspecten en best practices
* Aanbieden van een experimenteeromgeving bij het BDVC in Utrecht
* Linked Data op beleidsniveau meer onder de aandacht te brengen
* Linked Data binnen nieuwe sectoren te introduceren en te stimuleren
* Het MKB aan te haken bij het ontwikkelen van nieuwe data innovaties
Volg de activiteiten van ons platform via onze PLDN website, onze Twitter account @linkeddatanl, onze LOD Nederland LinkedIn groep, onze nieuwsbrief en de websites van ECP en BDVC. Daar worden regelmatig updates over onze activiteiten gepubliceerd. 
De activiteiten van PLDN worden mede mogelijk gemaakt door de volgende sponsoren: Kadaster, TNO, Big Data Value Center (BDVC), ECP, Forum Standaardisatie, Kennisnet, SLO, Rijksdienst voor het Cultureel Erfgoed (RCE), Beeld en Geluid, Waternet, EuroSDR, KVK, Taxonic, Triply, Semmtech, en MarkLogic.
Heeft u interesse om met uw organisatie sponsor te worden van PLDN neem dan contact op met ons PLDN Sponsoring team: hans.vanbragt@bdvc.nl 
En meer informatie over onze sponsoring packages vindt u in onze and (PDF).
Statistische data linken aan locatie

category:case3
Geonovum (Michel Grothe, Thijs Brentjens) heeft meegewerkt aan een Europees onderzoek naar de OGC standaard Table Joining Service. Deze standaard wordt toegepast om tabelvormige data te koppelen aan geometrieën uit een andere databron. In dit project kwam regelmatig de vraag naar boven of in plaats van TJS ook linked data standaarden gebruikt zouden kunnen worden om hetzelfde te bereiken. 
De volgende activiteiten kunnen bijvoorbeeld worden uitgevoerd om deze vraag te beantwoorden: 
* Kijken of er al voorbeelden van bestaan
* Experimenteren: 
** omzetten statistische data naar RDF
** automatisch links aanbrengen
* Kan het uiteindelijk in een geoviewer bekeken worden 
etc. 
We kunnen hierbij gebruik maken van ervaringen uit de PiLOD 1 met het koppelen van statistische data aan andere databronnen. Zie twee artikelen uit het boek: 
http://www.pilod.nl/wiki/Boek/Hage
http://www.pilod.nl/wiki/Boek/Gueret-Linking 
PiLOD deelnemer Paul Hermans is betrokken bij het pas opgestarte Europees OpenCube project. http://opencube-project.eu/
Daarin wordt software ontwikkeld voor het omzetten van statistische data naar RDF, meer specifiek volgens het DataCube vocabularium, het automatisch aanbrengen van linken, het visualiseren van de data. Als we hiervoor specifieke requirements hebben, neemt Paul ze graag mee in het project. Wel van belang: Paul zou die requirements tegen eind december moeten hebben, kwestie van ze tijdig in het projectplan te krijgen.
Step 2: Prepare the data

Once the data has been selected, the next step is to prepare this data for publication. The following sub-steps have to be considered:
*a) Obtain access to the data source and or data extracts or create a new dataset in a way that can be replicated. 
*b) Obtain a copy of the logical and physical model of the database to be used in the data modelling Step 3.
*c) Perform a data quality assessment to get insights into the data quality of the dataset.
*d) Use data cleansing were needed to improve the data quality, e.g., by removing outdated, obsolete and irrelevant data 
*e) Implement technical interventions, such as anonymization of sensitive data elements or the integration of datasets identified when selecting the data. 
Different tools can be used for these steps ranging from general purpose spreadsheet and database tools to dedicated data cleansing tools. We will now describe sub-steps c, d and e, the data quality assessment, data cleansing and data integration in more detail.
Data quality assessment 
Data Cleansing
Data Integration
 Go back to overview
Step 5: Convert the data

== Convert the data to RDF ==
Once you have a schema that you are satisfied with, the next step is to convert the source data into a Linked Data representation or serialization. In this step the data is converted to RDF triples and while applying the naming scheme defined in Step 4. The Resource Description Framework (RDF) is used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is similar to classic conceptual modeling approaches such as entity–relationship or class diagrams, as it is based upon the idea of making statements about resources (in particular web resources) in the form of subject-predicate-object expressions. These expressions are known as triples in RDF terminology. The subject denotes the resource, and the predicate denotes traits or aspects of the resource and expresses a relationship between the subject and the object. RDF triples may be stored in a type of database called a triplestore. 
Before converting your data to RDF you need to decide how you want to publish the data. Do you want to publish the data as a webservice that can be queried? Following, you need to make sure that your data is in the right format. We advise that you do not chose one single serialization but multiple. Potential serializations for RDF are turtle (human readable), RDF/XML, N3, RDFa (in HTML), and the lately becoming very popular JSON-LD (for JavaScript Developers). 
You might decide to first make your data online available via a webservice (API) so developers can easily access your data and test its usability. This can provide you with valuable feedback about the potential value of your data before you engage in the investment to convert your data to RDF. 
Conversion approaches fall into three categories: 
*Automatic conversion, sometimes called triplication 
*Partial scripted conversion 
*Modeling by human and subject matter experts, followed by scripted conversion
There are different tools that can be used to do this conversion:
*LODRefine, an extension of OpenRefine
*RDF Translator
*Spyder
The Simile project made an attempt in proving a directory of tools for converting various data formats into RDF. A similar list can be found by W3C. A tutorial on converting relational data into RDF format is provided by Oracle. For an easy approach to transform spreadsheets to rdf, have a look at one of the books published by the PiLOD project containing a step by step approach based on the Open Refine tool, including screenshots of the tool. If you are interested in expressing customized mappings from relational databases to RDF datasets you should check out the R2RML language.
Once you have converted your data to RDF the next step is to make sure that you have some governance structure in place to maintain and manage your data. 
 Go back to overview
Step 6: Organize Governance

When publishing Linked (open) data it is of utmost importance to not only think of the technical aspects described in this roadmap but also take governance aspects into account. Things like a licensing structure, how maintenance will be deployed and other governance aspects need to be thought of and agreed upon before the data is published. We will not cover these issues in this roadmap but refer to the booklet about BOMOD which is published together with this roadmap. Organizing governance will be a step that takes a lot of throughput time, as it involves agreement with the involved stakeholders. Therefore, it is important to start early on in the data publication process and do this step in parallel with the other steps.
 Go back to overview
Step 7: Add metadata

While following the roadmap, and especially in the last step, the organization of governance, you will realize that metadata about your dataset is of crucial importance. In this step we will introduce three levels of metadata that you can use when describing your dataset. 
In order to make the dataset self-describing and thus support the re-usage of data, extra information about the data needs to be added to the data by the data supplier. Self-describing data suggests that information about the encodings used for each representation is provided explicitly within the representation. Such data about data is called metadata and includes information about the data origin, the data production date and for which applications the data can be used. Metadata that describes the process of data development is also referred to as provenance [Freie et al. 2008]. Provenance gives an indication of the reliability of the data. Another metadata aspect interesting for reusing data is information about the usability of the data. It might be interesting for data users to learn about successful applications of other data users. Information about data usability is also very valuable for Linked Data. It can provide a good indication of the potential success of similar applications in the future. Metadata can be added by simply adding triples to the RDF version of the dataset obtained in Step 5 describing facts about the dataset. 
Linked Data published on the Web should be as self-describing as possible in order to make it easier for clients to understand and use the data. Important aspects of self-descriptiveness are making vocabulary terms de-referenceable according to the best practices described in Publishing RDF Vocabularies, using terms from common vocabularies and providing vocabulary mappings for proprietary vocabulary terms. 
We structure this section using the three levels of metadata described by CKAN: 
*Level 1: basic metadata
*Level 2: minimal metadata 
*Level 3: complete metadata. 
We extend the aspects mentioned in that classification with aspects from our quality model developed during earlier research. The Dutch government has published a list with elements that metadata of datasets published at data.overheid.nl should include. Most of the elements are compulsory. The elements fall in four categories: context, data source, characteristics, involved organizations. We add these elements to the tables provided for the three levels of metadata using their original identifier from data.overheid.nl. 
[Freie et al.] Freire, J., Koop, D., & Moreau, L. (2008). Second International Provenance and Annotation Workshop. Paper presented at the IPAW 2008, Salt Lake City, Utah.
 Go back to overview
Step 9: Link the data

A final and optional step is to link the dataset to other datasets to be able to provide more context to the data. Linked Data, unlike other data formatting and publication approaches, provides a simple mechanism for combining data from multiple sources across the Web. 	
Several guidelines on how to combine datasets can be found on the web providing step-by-step guidelines . Different types of links can be made: ontology links and data links. While links to ontologies have been already made in Step 3, we will now describe data links. Data links: The data itself can also be linked to other available linked datasets. This may be useful to provide more context to the data. Consider for example a dataset that includes addresses which contain a reference to a town. It is likely that more information about these towns is already available on the web. DBpedia, for example, the linked data version of Wikipedia, usually has an entry for each town. One could add triples to the original dataset to link the addresses to the DBpedia entry providing more details about the town.
Another option is to create a new dataset that contains the links between your and other datasets. This way it can be done afterwards, but it can also be done by others that link your data to other datasets. 
 Go back to overview