contact: info@kartography.org
Kartography will be partnering with The National Archives (TNA) as part of the UKRI RicHES heritage science data service project (HSDS).
TNA's Collection Care Department use the innovative ResearchSpace knowledge base platform (www.researchspace.org), a transdiscipinary system which uses Semantic Linked Data and takes full advantage of semantic ontologies like the CIDOC CRM.
Kartography CIC will be partnering in a National Gallery, London, project in the design and creation of the 'Reynolds Digital Research Resource', funded by UKRI.
This multidisciplinary project is particularly concerned with heritage science for conservation using different types and sources of data. It is a collaborative effort involving the synthesis of information from different collections and using the native Semantic Linked Data environment of ResearchSpace, a natural and flexible environment, enabling the full benefits of the CIDOC CRM ontology.
Who are Kartography?
Kartography are an interdisciplinary team drawing upon extensive experience of working in knowledge organisations including the Royal College of Arts, the British Museum and the National Gallery. Kartography are the designers and developers of ResearchSpace, a knowledge base platform that supports evolving knowledge processes using meaningful context.
We provide expert consultancy in:
What is ResearchSpace?
ResearchSpace is an open source system with over 10 years of research and development funded by the Mellon Foundation (New York). ResearchSpace has been designed to address many of the problems associated with representing complex data that databases or database appraches are not designed to address. For more information about how ResearchSpace works click here
How does ResearchSpace work?
In order for different system to effectively communicate they need a common understanding. When we communicate we use different words and phrases to describe similar things. When information is processed through computers this can cause serious problems. Every organisation is individual and has different perspectives and traditions.
The ResearchSpace Knowledge base provides an overarching framework based on real world empirical concepts providing a solid semantic referent for data. In this way both human and computer have common framework under which heterogenious information can be represented and interconnected, and provide a better basis for AI. The flexibility needed for human knowledge processes is supported but with all the advantages of computer processesing to cope with large amounts of data but essentially based on meaningful qualitative information. Instead of a database that only stores a field label and a value with a data type, ResearchSpace stores an effective semantic network of processes typed to the real world. This creates a highly effective knowledge base of information which can be dynamically extended and exchanged.
What does kartography do?
Kartography helps you move from the constraints of instrumental, abstract, one dimensional thinking, to a new digital environment in which a wider range of knowledge can be authored with greater context and diversity. It helps design systems that include parallel perspectives, argument and uncertainty, and multi-layered causation (influence). It provides transdisciplinary capability and the ability to include social and historical context. This often goes hand in hand with reviewing and changing internal processes to represent greater collaboration within and across departments and with external partners and audiences.
Kartography are experienced at creating flexible knowledge systems that grow and evolve as human working evolves without the overhead of a traditional bespoke system. All the meaning and logic is in the data making it easier to change the way ResearchSpace interacts and augments knowledge processes and decision making.
Kartography provides courses in how to change the way people work to make better use of the knowledge they produce. To radical change the relationship with information systems and to create data systems that eliminate bias and represent context that improves inclusivity. It also provides connected courses in the technicalities of the Semantic Web and Linked data without separating the technical processes from social context.