Heritage Connector

Lead Research Organisation: Science Museum Group
Department Name: Science Museum Research

Abstract

As with almost all data, museum collection catalogues are largely unstructured, variable in consistency and overwhelmingly composed of thin records. This is largely a legacy of the development of these catalogues from handwritten paper records. The depth and form of collection catalogues has been primarily guided by collection management needs (records of acquisition, administration of loans, provenance documentation, etc.) where unstructured data can fulfil the needs of the organisation and comply with collection management standards. When computer technology was adopted for collection management in the 1980s it was implemented to handle these same back-office tasks rather than to support public access. The resulting form of the catalogues means that the potential for new forms of digital research, access and scholarly enquiry remain dormant, and searching across collections is currently possible only through aggregation which is labour intensive to implement, or by third-party search engines where results are unreliable. In this project, we will apply a battery of digital techniques to connect similar, identical and related items within and across collections. Our primary research question is "How can existing digital tools and methods be used to build relationships at scale between poorly and inconsistently catalogued digitised collection objects and other content sources?"

Since the turn of the twenty-first century enormous and growing volumes of material have been digitised, and catalogues have begun to address the needs of digital public access. However, this has been mainly at an institutional level or via a handful of content aggregators and thus the enhancement of catalogues for the purposes of public access has been driven by the needs of individual collection websites, with little or no interlinking to other collections or content sources. Where that linking (people, places, events, objects, etc.) does exist it has been undertaken by human intervention, and because of the number of records, it has been limited in scale and scope and rarely an ongoing endeavour despite the evolving nature of the catalogue.

Alongside the digitisation of collections, recent years have seen a growth in the publication online of scholarly research related to heritage collections: open access journals, theses, and other online resources. However, beyond the host institution, references to this material is rarely, if ever, ingested into the underlying collections systems and made available via links from related collection websites. This project will therefore also use computer analysis to attempt to identify and build links to this material. Finally, structured data and rich linking are an increasingly urgent concern as new forms of discovery and access emerge - notably artificial intelligence powered discovery and new interfaces such as voice search - that rely on these for their functionality.

This project will explore an alternative approach - a "Heritage Connection Engine" - that will analyse catalogues, published material and knowledge graphs, and build links at massive scale between these that can then be used for new forms of research. It will explore the opportunity for computer generated links with Wikidata to provide new levels of structure and machine-readable data that can form the foundation of new types of discovery and access. The "Heritage Connection Engine" will use a range of technologies including machine learning; named entity recognition; open data; and persistent IDs. These methods will create a large-scale data source of links, each with a confidence ranking. Computational enquiry to generated links via an application programming interface (API) will enable the creation of a range of proof-of-concept research and discovery tools. All software will be documented released under an open source Licence. All datasets will be released under the Creative Commons Zero license.

Planned Impact

As a public-facing institution, Science Museum Group (SMG) will disseminate the results of Heritage Connector beyond the academy to broad publics through the development of a thoroughly integrated and cross-referenced digital catalogue. This resource will unite files from different museum holdings, producing more relevant search results from databases. Users will gain unprecedented access to museum collections and archives, enriching knowledge of Britain's past and legacy in the arts and sciences, with long-term value for materials in store and on display. Improved collections knowledge will inform future gallery and exhibition development plans.
VISITORS TO SMG: With improved access to museum collections and archive holdings, SMG will be able to transform its programme of cultural events, broadening its scope to include hitherto overlooked or neglected topics and objects. These initiatives will directly impact the experiences of SMG's 6 million annual visitors to our five national museum sites. Public events such as the two-day hackathon will provide further opportunities for a specific public to engage critically with project activities, and contribute to the research findings.
VISITORS TO UK HERITAGE ATTRACTIONS MORE BROADLY: The ability to discover related material across heritage organisations representing different disciplinary areas will lead to new and richer narratives, enhancing the interdisciplinary offer in displays and programming across organisations to the benefit of visitors who will be exposed to a new, wide, range of experiences.
MUSEUM & HERITAGE PROFESSIONALS: Museum and heritage professionals will benefit from our aim to transform digital cataloguing practices. The production of more thoroughly integrated and cross-referenced national museum records will directly benefit curatorial activities and perspectives. The end of project conference and publications will extend the findings of the project further, reaching colleagues across the world. Cross-institutional collaboration between SMG and the V&A will also foster long-term research partnerships and enrich knowledge of their shared history.
WEBSITE AND ONLINE RESOURCES: SMG's 11 million online visitors will have improved digital access to museum objects and records. Improved image libraries with links to contextual information will allow users to realise the full breadth of SMG's collection and engage with material typically unavailable to the public in galleries. Academic findings about the application of new software can impact other digital developers, online communities, and projects, exposing new theories and practices, and collaborative opportunities.
AMATEUR & PROFESSIONAL HISTORIANS: Planned events will foster dialogues between these groups. Improved access to objects and records will allow those researchers working outside the Academy to pursue sustained investigations into the material history of science, technology, engineering and medicine. Providing an open-access catalogue on a digital platform ensures that all types of researchers regardless of their socio-economic background or location can use museum materials.
LIBRARIANS AND ARCHIVISTS: The impact on librarians and archivists will be in the form of knowledge exchange between them and project investigators. Archivists and librarians from across the country will be invited to convenings, allowing them to benefit from the expertise of Heritage Connector's investigator team, who will in turn benefit from improved knowledge of collections. Participants in the project will help librarians and archivists consider the relevance of these new digital tools for their collections, and how scholars and the wider public might use these digitally revamped collections for research activities.

Publications

10 25 50
 
Description The project explored three technologies that together have the potential to provide a step-change in access and discoverability, research and public engagement by augmenting traditional catalogue data and associated keyword search through generation of a vast number of interlinked resources and content. The three technologies Heritage Connector explored were:
? artificial intelligence (AI) - specifically, natural language processing (NLP), named entity recognition (NER) and entity linking (EL) - to build links at scale from thin collection records;
? linked open data (LOD) as a scalable and flexible structuring methodology;
? knowledge graphs to store links and make them accessible.
The project sought to demonstrate that generation of a rich web of links could be built and made available
using these technologies on the following source datasets:
? Science Museum Group (SMG) Collection catalogue,
? Victoria and Albert Museum (V&A) Collection catalogue,
? Wikidata,
? Science Museum Group Journal,
? Science Museum blog.
The final web of links (structured in the knowledge graph) has 1,208,256 entities and 53 relations. The techniques used to generate the links was tuned in ways which were able to provide high quality links and even though the accuracy of these links in some cases falls short of those generated manually, a greater wealth of associated material is surfaced which has practical benefits.
The project findings are:
? Overall, the Heritage Connector project demonstrated that the methods used can be used to build links at scale between and within collections.
? The approach taken by the project provides avenues to better solve existing challenges of discovery and exploration for large collection datasets and enable new forms of data-based analysis.
? In common with other linked data projects in the GLAM sector, the project found that the use of linked content in the cultural heritage sector has the potential to make collections more visible, expose hidden aspects, enrich existing catalogues, allow data reuse in new contexts, and enable improved user experiences.
? The availability of museum collection catalogues and other data sources as well-documented APIs (application programming interfaces) significantly speeded up the project's technical work. However, none of these APIs are designed for large-scale 'bulk' use and can be slow and/or unstable for this application. So, for this kind of project, data extracts are ideally required.
? As link building is undertaken on the collection catalogue datasets, the resulting dataset rapidly becomes extremely large. Given the size of the source datasets, there is significant benefit in being selective about the data and content processed and making sure it is focussed on specific outcomes.
? Aligning controlled and free-text dataset fields (such as those found in collection catalogues) to entities can take a significant time using existing tools, and using the NLP, NER and EL methods trailed by the project generated vast numbers of links: within collections, between collections, and to and from other content sources (Wikidata, journal articles and other texts such as blog posts).
? Working with the collections and NLP, NER and EL, a pipeline approach with various stages was demonstrated to work well.
? If the source collection data includes persistent identifiers (PIDs) and links to sources (e.g. Wikipedia or biographical sources), these can be used to build links with a high degree of confidence.
? False positives ('mistakes' by the machine learning) were a tiny minority of the links and are usually readily apparent, even to non-specialist audiences.
? For the best results, it is not a question of if human intervention and curation is needed, but when it should be used and how it may be most usefully focused. Providing descriptive texts for collection objects was proven to be valuable not only to human users but also for entity extraction by machine. Subject matter expertise is required to select the appropriate source datasets to ensure that they were manageable and to review machine learning outputs to improve the outputs in subsequent stages.
? Although it would be desirable to display a 'degrees of confidence' rating for each link in user interfaces, these were impossible to calculate in this project, as links were created by multiple machine learning models used in a pipeline approach.
? Using the project's methodologies generates an extremely large dataset of linked open data (LOD). Handling these output linked data sets of links in a knowledge graph was demonstrated to work well. Knowledge graphs make it relatively easy to visually map disparate data and apply mathematical functions across large volumes of data.
? Barriers to LOD in the cultural heritage sector fall under four broad headings: technical, conceptual, legal and financial. Working with LOD at any kind of scale is both time consuming and resource intensive. A great deal of LOD work to date has focused on records for people rather than objects. Many LOD projects involve only one or at most two institutions, and international collaboration is relatively rare.
? Wikidata is a rich and diverse data source that was shown to be valuable to enrich museum collection entities with new data and act as a bridging point between collections.
? Easy to use interfaces are important for non-technical users to visualise, explore and navigate output data (which is potentially colossal in scale). Rather than creating single monolithic user interfaces, there is significant potential to create multiple light-weight interfaces and tools of different kinds onto the same output dataset.
? When considering further projects of this type, it is important that consideration is given to framing and contextualisation for machine learning generated outputs. The approach taken challenges traditional cultural heritage notions of the 'canonical' collection catalogue.
Exploitation Route The project's software is open source and can be reused by others. The project's output datasets are available under an open access licence for further exploration and reuse.
Sectors Culture, Heritage, Museums and Collections

URL https://doi.org/10.5281/zenodo.6022678
 
Title CLI for loading Wikidata subsets into Elasticsearch 
Description Running text search programmatically on Wikidata means using the MediaWiki query API, either directly or through the Wikidata query service/SPARQL. There are a couple of reasons you may not want to do this when running searches programmatically: - time constraints/large volumes: APIs are rate-limited, and you can only do one text search per SPARQL query - better search: using Elasticsearch allows for more flexible and powerful text search capabilities. The created software is a set of simple CLI tools to load a subset of Wikidata into Elasticsearch. 
Type Of Material Improvements to research infrastructure 
Year Produced 2020 
Provided To Others? Yes  
Impact The software has been favourited 24 times on GitHub and "forked" 4 times meaning that others are reusing the software. 
URL https://github.com/TheScienceMuseum/elastic-wikidata
 
Title Heritage Connector: Transforming text into data to extract meaning and make connections 
Description The aims of the Heritage Connector (HC) project were to make a substantial contribution to enable realisation of the ambitions within the AHRC's Towards a National Collection (TaNC) programme to make collections accessible for research and public engagement purposes. Bringing multiple cultural heritage collections together is fundamentally about building links. Online, these can be manifested as hypertext links which create a rich web of deep and broad user journeys between related content and information. These links also have the potential for computational analysis and visualisation enabling new forms of digital humanities research into collections. The project explored three technologies that together have the potential to provide a step-change in access and discoverability, research and public engagement by augmenting traditional catalogue data and associated keyword search through generation of a vast number of interlinked resources and content. The three technologies Heritage Connector explored were: ? artificial intelligence (AI) - specifically, natural language processing (NLP), named entity recognition (NER) and entity linking (EL) - to build links at scale from thin collection records; ? linked open data (LOD) as a scalable and flexible structuring methodology; ? knowledge graphs to store links and make them accessible. The project sought to demonstrate that generation of a rich web of links could be built and made available using these technologies on the following source datasets: ? Science Museum Group (SMG) Collection catalogue, ? Victoria and Albert Museum (V&A) Collection catalogue, ? Wikidata, ? Science Museum Group Journal, ? Science Museum blog. The final web of links (structured in the knowledge graph) has 1,208,256 entities and 53 relations. The techniques used to generate the links was tuned in ways which were able to provide high quality links and even though the accuracy of these links in some cases falls short of those generated manually, a greater wealth of associated material is surfaced which has practical benefits. 
Type Of Material Improvements to research infrastructure 
Year Produced 2021 
Provided To Others? Yes  
Impact The methods trailed in the Heritage Connector project have generated interest across the cultural heritage sector with informal conversation with multiple institutions and researchers seeking to understand more about the approaches. 
URL https://thesciencemuseum.github.io/heritageconnector/post/2022/02/09/Final-Report/
 
Title Heritage Connector data outputs 
Description Data outputs for the Heritage Connector project. Contents: triples (.nt) and csv (.csv) files - the final knowledge graph produced. Includes data from Science Museum Group (SMG) and Victoria & Albert Museum (V&A) collections and Wikidata. triples (.nt) and csv (.csv) files - the knowledge graph produced from the SMG collection and Wikidata. kg_embeddings.zip - knowledge graph embeddings generated by training RotatE models on the above datasets. Also includes 2D and 3D projections of these embeddings generated using UMAP. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
Impact The data set includes the final outputs from the project and demonstrates that multiple museum collections, Wikidata and other sources can be interlinked using the methods applied. The dataset has been used to create a number of demonstrators which are open source so the ways in which the datasets has been applied in these instances can be understood. 
URL https://zenodo.org/record/5752010
 
Title Natural Language (NLP) tools for heritage collections 
Description Text processing for the Heritage Connector: a set of NLP utilities for the Heritage sector. Includes: - information extraction (NER, NEL, relation classification) - labelling (Label Studio) - test suite for models 
Type Of Material Computer model/algorithm 
Year Produced 2020 
Provided To Others? Yes  
Impact This is one of the main outputs of the project and demonstrates the capability of NLP for process cultural heritage collections data to extract entities and build knowledge graphs. 
URL https://github.com/TheScienceMuseum/heritage-connector-nlp
 
Title Heritage Connector APIs 
Description APIs for the Heritage Connector project 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The Girhub repository has been watched 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-apis
 
Title Heritage Connector Bookmarklet Demo 
Description A bookmarklet to show connections from one page its direct connections in the graph. Meant to be a quick way to prototype future collection website widgets. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The Github repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos/tree/main/2_bookmarklet
 
Title Heritage Connector Demos 
Description This repo contains various demos and sketches of demos for Heritage Connector, induding: an interactive streamlit app showing NER and entity linking which uses static data for speed (not hosted at the moment) a bookmarklet to view connections from an SMG collection, blog or journal page a macro visualisation of the whole collection/knowledge graph a visualisation of the combined SMG and V&A collections maps of all the places in the knowledge graph 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos
 
Title Heritage Connector Deployment 
Description An easy way to deploy all the Heritage Connector API's and Endpoints, with the exception of the main pipeline, in one step. The following services are included and all configured through environment variables: fuseki - RDF triplestore thor - front end for performing SPARQL queries thor-cors-proxy - CORS proxy to enable thor to connect to fuseki heritage-connector-vectors - an nearest neighbours on knowledge graph embeddings heritage-connector-apis - API endpoints to wrap some common SPARQL queries and the nearest neighbours API. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The Github repository has been followed 5 times 
URL https://github.com/TheScienceMuseum/heritage-connector-deployment
 
Title Heritage Connector Event Streamlit Demo 
Description Streamlit demo of NER and entity linking for the second Heritage Connector event. Runs on static data in demo_data.pkl rather than using the models, for speed. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos/tree/main/1_event_streamlit
 
Title Heritage Connector Hackathon Demos 
Description Suite of demos built as part to the Heritage Connector project one-day hackathon in partnership with Cogapp. The hackathon explored creative use of the project's knowledge graph and related APIs to develop new forms of user interface and audience engagement. The following list provides details of the projects developed at the hackathon: Augmenting From The Outside 3D Space Curator Heritage Connector Link Race Good Neighbours RHiZOME 
Type Of Technology Webtool/Application 
Year Produced 2021 
Impact The demos were presented at the final project webinar. 
URL https://thesciencemuseum.github.io/heritageconnector/post/2021/12/05/Hackathon-Demos/
 
Title Heritage Connector Map Demo 
Description Visualisation of all Wikidata QIDs in the knowledge graph with latitude and longitude properties, linked to the Metadata Explorer with onward links to V&A and Science Museum Group collections, Wikidata, etc. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos/tree/main/5_map_visualisation
 
Title Heritage Connector Metadata Explorer 
Description An interface for guided exploration of the Heritage Connector knowledge graph. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The Metadata explorer has been demoed through project webinars and convening. 
URL http://heritageconnector.sciencemuseum.org.uk/6_metadata_explorer/index.html
 
Title Heritage Connector NLP (Natural Language Processing) 
Description Text processing for the Heritage Connector: a set of NLP utilities for the Heritage sector. Includes: low-data extensions for information extraction (NER, NEL, relation classification) labelling (Label Studio) test suite for models 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 4 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-nlp
 
Title Heritage Connector Pipeline 
Description Contains the main bootstrap / pipeline used by the Heritage Connector to import data into a graph before performing NPL and Graph analysis on it. Individual repos provide much of the actual functionality and are listed separately. A set of tools to: load tabular collection data to a knowledge graph find links between collection entities and Wikidata perform NLP to create more links in the graph (also see hc-nlp) explore and analyse a collection graph ways that aren't possible in existing collections systems 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact The software has been favourited 18 times in the GitHub repository. 
URL https://github.com/TheScienceMuseum/heritage-connector
 
Title Heritage Connector Thor / Fuseki 
Description These repos provide a SPARQL server (Fuseki), a SPARQL client (Thor) and a Proxy server (to deal with CORS headers) as Docker containers. https://github.com/TheScienceMuseum/fuseki-docker https://github.com/TheScienceMuseum/thor-docker https://github.com/TheScienceMuseum/thor-cors-proxy 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact These repositories have been followed 4, 5 and 6 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-deployment
 
Title Heritage Connector Timeline Demos 
Description Interactive web-based timelines for events and people in the Heritage Connector knowledge graph built in Timeline JS. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Impact Timeline demoed at final project webinar. 
URL https://thesciencemuseum.github.io/heritageconnector/post/2021/12/04/Timeline/
 
Title Heritage Connector Vectors 
Description Generating graph and language embeddings for the Heritage Connector project. A library that: Takes JSON data of collection item descriptions or TSV/CSV data of triples, exported from heritage-connector. Calculates sentence (using sentence-transformers) or graph (using pyKEEN) embeddings for this data. Provides a unified interface for accessing these embeddings. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-vectors
 
Title Heritage Connector Visualisation Demo 1 
Description Visualisation of knowledge graph embeddings, projected to 2D via UMAP, created for the Heritage Connector project. Hosted at https://thesciencemuseum.github.io/heritage-connector-demos/3_visualisation/index.html. This implementation uses D3FC and is based on Colin Berhardt's Hathi Trust demo. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos/tree/main/3_visualisation
 
Title Heritage Connector Visualisation Demo 2 
Description Visualisation of knowledge graph embeddings, projected to 2D via UMAP, created for the Heritage Connector project. NOTE: this is a direct copy of the single collection visualisation in 3_visualisation with a few parameters modified, as github pages doesn't allow setting of environments. Hosted at https://thesciencemuseum.github.io/heritage-connector-demos/3_visualisation/index.html. 
Type Of Technology Webtool/Application 
Year Produced 2021 
Open Source License? Yes  
Impact The GitHub repository has been followed 5 times. 
URL https://github.com/TheScienceMuseum/heritage-connector-demos/tree/main/4_visualisation_vanda
 
Description Hands-on activity in linking and enriching geo-data, part of the Linked Pasts 6 conference 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact 39 participants took part in a technical workshop with hands-on activity as part of the Linked Pasts 6 conference hosted by the British Library and University of London. The Heritage Connector project team presented elements of the project's software and participants were able to test and play with the software. The team then took part in a roundtable discussion. The technical workshop was hosted by the AHRC TaNC Locating a National Collection project.
Year(s) Of Engagement Activity 2020
URL https://www.eventbrite.co.uk/e/linking-geo-data-through-test-and-play-tickets-129858356841#
 
Description Heritage Connector Project Blog 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact 1,302 users have made 2,164 visits to the project blog which collates project outcomes, documentation of events and links to reports, recordings and software developed.
Year(s) Of Engagement Activity 2020,2021
URL https://thesciencemuseum.github.io/heritageconnector
 
Description Heritage Connector YouTube Channel 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Webinars, presentations and demonstrations presented as part of the Heritage Connector project are collated on this YouTube channel which has received 222 video plays.
Year(s) Of Engagement Activity 2020,2021
URL https://www.youtube.com/channel/UCzO6jroIvj-JbFuiQ9BpZdQ
 
Description Heritage Connector Zotero Library 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Public project Zotero library established to collate literature review, case studies and related projects. The library currently contains 223 items organised by type and theme.
Year(s) Of Engagement Activity 2020,2021
URL https://www.zotero.org/groups/2439363/heritage_connector
 
Description Heritage Connector: Findings, Demonstrators and Potential 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact At 14.30-16.30 on 3 December 2021, the Heritage Connector project hosted a free, public webinar to share the findings from the project. The webinar was attended by 81 people.
The webinar featured:
Technical overview of the project's approach,
A set of demonstrators which have been developed by the project team and through a hackathon held with digital agency Cogapp,
Reflections on the project from a digital humanities and curatorial perspectives.
Year(s) Of Engagement Activity 2021
URL https://thesciencemuseum.github.io/heritageconnector/events/2021/10/22/webinar-findings-demos-and-po...
 
Description Machine Learning and Cultural Heritage: What Is It Good Enough For? 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact On 7 July 2021, Heritage Connector was presented at the AEOLIAN Network (Artificial Intelligence for Cultural Heritage)'s online workshop entitled Employing Machine Learning and Artificial Intelligence in Cultural Institutions. 81 people attended the workshop.
Year(s) Of Engagement Activity 2021
URL https://thesciencemuseum.github.io/heritageconnector/events/2021/07/15/aeolian-network-workshop-1/
 
Description Project Lightning Talk on AI4LAM Community Call 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact 61 participants viewed the lightning talk of the Heritage Connector's software on the AI4LAM (Artificial Intelligence for Libraries, Archives and Museums) Community Call, and participated in a Q&A.
Year(s) Of Engagement Activity 2021
URL https://docs.google.com/document/d/1gOQEPqSEBAkqpy6KtRsEIm5g1vCjsxdmnlkeO3YJM3Y/
 
Description Project hackathon event 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact In 19 November 2021, the Heritage Connector project held a one-day hackathon in partnership with Cogapp. The hackathon explored creative use of the project's knowledge graph and related APIs to develop new forms of user interface and audience engagement. 20 people attended the hackathon.
Year(s) Of Engagement Activity 2021
URL https://thesciencemuseum.github.io/heritageconnector/post/2021/12/05/Hackathon-Demos/
 
Description Project workshop 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact On 22 March 2021, the Heritage Connector project hosted a two-hour online workshop. The objectives of the workshop were to:
- introduce Heritage Connector affordances and possibilities to a model group of historians and curators,
- introduce concerns and interests of the model group of historians and curators to the Heritage Connector team and digital humanities practitioners,
- run exercises to create mutual learning.
54 participants attended, including collections management professionals, curators and archivists from the Science Museum Group's five museums, the V&A and other museums across the UK; Wikipedia professionals; academics from digital humanities, history and other disciplines; community-based historians and practitioners, and the project team.
Year(s) Of Engagement Activity 2021
URL https://thesciencemuseum.github.io/heritageconnector/events/2021/04/01/workshop-report-22-March-2021...
 
Description Towards a National Collection: Persistent Identifiers as IRO Infrastructure - Project Launch Webinar 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The AHRC TaNC Persistent Identifiers as IRO Infrastructure brings together best practices in the use of PIDs in the UK heritage sector, with a focus on those that are Independent Research Organisations. This webinar was run to introduce the community to our project and find out what stakeholders were interested in hearing more about as the project evolves. Heritage Connector was presented to align the two projects from the outset as there are areas of common interest. 118 people participated in the event.
Year(s) Of Engagement Activity 2020
URL https://www.pidforum.org/t/webinar-on-a-new-pids-in-glam-project-6th-april-2020/917
 
Description Using Machine Learning to Make Connections between and Within Collections. "Dealing with complexity". Collections Trust conference 2021 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presented talk called "Using Machine Learning to Make Connections between and Within Collections" at "Dealing with complexity". Collections Trust conference 2021. Attended by 271 people.
Year(s) Of Engagement Activity 2021
URL https://collectionstrust.org.uk/events/collections-trust-conference-2021/
 
Description Wikidata and cultural heritage collections webinar 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact On 19 June 2020, the Science Museum Group hosted a free, public webinar on Wikidata and cultural heritage collections. This was the first in a series of convening as part of the Heritage Connector project. The webinar brought together a set of short case studies from practitioners who have worked in this field to present their work and the opportunities and challenges as they saw them. 296 people participated in the webinar which brought together international speakers and participated in the Q&A session and online survey.
Year(s) Of Engagement Activity 2020
URL https://thesciencemuseum.github.io/heritageconnector/events/2020/06/22/wikidata-and-cultural-heritag...