linked open data

METRO Annual Conference 2016

Streszczenie

W czwartek 21 stycznia 2016 braliśmy udział w dorocznej konferencji METRO – Metropolitan New York Library Council – która miała miejsce w Baruch College w Manhattanie. Konferencja ta, jak i poprzednie, była doskonałym przeglądem najnowszych inicjatyw, pomysłów, rozwiązań i projektów w dziedzinie humanistyki cyfrowej w społeczności GLAM. Poniżej przedstawiamy omówienie wybranych prezentacji w języku angielskim.

The annual METRO (Metropolitan New York Library Council) conferences are about the best sources of the latest inventions, projects and ideas in the GLAM community, concentrated in one day of intense briefings. This year was no exception – the conference that took place January 21, 2016 at the Baruch College in Manhattan. On the conference a number of “Project briefings” were presented – the intent was to show the projects in progress and discuss their workings, issues and plans, not necessarily the completed works. It was impossible to attend so many parallel briefings; we have selected two in each sessions, and report on them here as a sampling of the conference.

The full schedule of the conference is available, as well as a listing of the project briefings.

Keynote

The inaugurating keynote was delivered by Kari Lämsä, the manager of Library Number 10 and the Urban Workshop in Helsinki. He presented a fascinating case of modern library and a testbed for a library transformation to 21 century. [Presentation slides]

The author started with an observation, that only some 25% of the patrons check-out materials from the library and the library events are now organized in 80% to 90% by its customers. He then described the transformations, beginning with the furniture – traditionally uncomfortable library chairs to various places – some flexible, some comfortable, some creating a tranquil space, all movable by the customers from one place to another. Another change was to treat paperback editions as consumables – no reservations, no fixed order on shelves, read until fall apart. Czytaj dalej „METRO Annual Conference 2016”

Visualizing Cultural Heritage: Linked Open Data and the Carnegie Hall Archives p. 2

Wizualizacja spuścizny kulturowej: otwarte Linked Data w Carnegie Hall cz. 2

Przedstawiamy drugą część gościnnego blogu Roberta Hudsona, archiwisty z Carnegie Hall w Nowym Jorku. W drugim odcinku Rob opowiada o wynikach swojej pracy nad przekształceniem bazy danych Carnegie Hall w postac otwartego Linked Data. Po dokonaniu konwersji i uzyskaniu ok miliona „trójek” RDF, pora na dotarcie do narzędzi pozwalających na wizualizację i przeglądanie danych. Blog jest ilustorowany nagraniami pokazującymi na żywo eksploracje danych, z komentarzem autora.

Part II: Product

In Part I of this blog, I began telling you about my experience transforming Carnegie Hall’s historical performance history data into Linked Open Data, and in addition to giving some background on my project and the data I’m working with, I talked about process: modeling the data; how I went about choosing (and ultimately deciding to mint my own) URIs; finding vocabularies, or predicates, to describe the relationships in the data; and I gave some examples of the links I created to external datasets.

In this installment, I’d like to talk about product: the solutions I examined for serving up my newly-created RDF data, and some useful new tools that help bring the exploration of the web of linked data down out of the realm of developers and into the hands of ordinary users. I think it’s noteworthy that none of the tools I’m going to tell you about existed when I embarked upon my project a little more than two years ago!

As I’ve mentioned, my project is still a prototype, intended to be a proof-of-concept that I could use to convince Carnegie Hall that it would be worth the time to develop and publish its performance history data as Linked Open Data (LOD) — at this point, it exists only on my laptop. I needed to find some way to manage and serve up my RDF files, enough to provide some demonstrations of the possibilities that having our data expressed this way could afford the institution. I began to realize that without access to my own server this would be difficult. Luckily for me, 2014 saw the first full release of a linked data platform called Apache Marmotta by the Apache Software Foundation. Marmotta is a fully-functioning read-write linked data server, which would allow me to import all of my RDF triples, with a SPARQL module for querying the data. Best of all, for me, was the fact that Marmotta could function as a local, stand-alone installation on my laptop — no web server needed; I could act as my own, non-public web server. Marmotta is out-of-the-box, ready-to-go, and easy to install — I had it up and running in a few hours.

In addition to giving me the capability to serve up, query, and edit my RDF data, Marmotta has some great built-in visualization features. The screencast below demonstrates one of the map functions, with which I can make use of the GeoNames URIs I’ve used in my dataset to identify the birthplaces of composers and performers.

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Visualizing Cultural Heritage: Linked Open Data and the Carnegie Hall Archives p. 1

Wizualizacja spuścizny kulturowej: otwarte Linked Data w Carnegie Hall cz. 1

Rob Hudson – Photo by Gino Francesconi

Przedstawiamy gościnny blog Roberta Hudsona, archiwisty z Carnegie Hall w Nowym Jorku. Rob jest z wykształcenia muzykiem, zainteresowany archiwami, pracuje w Carnegie Hall od 1977 roku. Odkrywszy bazę danych występów w Carnegie Hall sięgających 19 wieku, Rob postanowił nauczyc sie programowania i dokonać konwersji danych w postać otwartego Linked Data tak, aby można było odkrywać powiązania i informacje o kompozytorach, wykonawcach i koncertach. Wielu polskich twórców i wykonawców przez lata brało udział w przedstawieniach w Carnegie Hall. Inicjatywa Roba przyczyni się, miejmy nadzieję, do udostępnienia ciekawego rozdziału z historii muzyki również polskim fanom.

Part I: Process

My name is Rob Hudson, and I’m the Associate Archivist at Carnegie Hall, where I’ve had the privilege to work since 1997. I’d like to tell you about my experience transforming Carnegie Hall’s historical performance history data into Linked Open Data, and how within the space of about two years I went from someone with a budding interest in linked data, but no clue how to actually create it, to having an actual working prototype.

First, one thing you should know about me: I’m not a developer or computer scientist. (For any developers and/or computer scientists out there reading this right now: skip to the next paragraph, and try to humor me.) I’m a musician who stumbled into the world of archives by chance, armed with subject knowledge and a love of history. I later went back and got my degree in library science, which was an incredibly valuable experience, and which introduced me to the concept of Linked Open Data (LOD), but up until relatively recently, the only lines of programming code I’d ever written was a “Hello, World!” – type script in Basic — in 1983. I mention this in order to give some hope to others out there like me, who discovered LOD, thought “Wow, this is fantastic — how can I do this?”, and were told “learn Python.” Well, I did, and if I can do it, so can you — it’s not that hard. Much harder than learning Python — and, one might argue, more important — is the much more abstract process of understanding your data, and figuring out how to describe it. Once you’ve dealt with that, the transformation via Python is just process — perhaps not a cakewalk, but nonetheless a methodical, straightforward process that you can learn and tackle, step by step.

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