WP8: Knowledge Sharing

Lead: UDEPartners: UMA, CICE, MTA KSZI, FR, RICYT

Month 1 - Month 36

Overview

- Social dimensions and models related with scientific processes with respect to knowledge sharing and knowledge flows

- Research question: How the new knowledge• is generated,• can be identified by patterns,• is spread within scientific communities,• can be transferred to other areas of society

- Will provide and exemplify tools and indicators (based on WP 6) to measure the social appropriation of knowledge among different actors

Specific objectives

- Definition of indicators for knowledge flow and sharing in scientific communities

- Identification and characterisation of examples- "Deep" (software-supported) analysis of selected

examples- Provision of guidelines for decision makers.WP8 will be aware of possible effects between knowledge sharing and mobility, productivity and development of new disciplinary fields to make results comparable with the other case studies.

T8.1: Taxonomy of indicators for knowledge flow and sharing

1. Critical review of existing approaches to modeling knowledge flow and sharing in scientific communities

2. Identification of the main types of- actors and relationships, - communication channels, - "knowledge objects" (documents or data types)

3. Integration in a taxonomy of specific indicatorsAdditional aspects: distinction formal/informal knowledge; including meta knowledge “who is doing what”R: RICYT (2PM)C: UDE (2PM), MTA (2PM), FR (2PM), CICE (1PM)

T8.2: Ident. and first charact. of example communities

1. Identify interesting communities for case study by:- innovativeness- social and scientific relevance- accessibility to data and results

2. Description of the communities by the taxonomy (8.1) baseline for systematic theoretical sampling of the cases for the deeper analysis

Preferred: life sciences and nanotechnology, e.g. CENIDE UDE and Gene Ontology R: UDE (2PM).C: RICYT (2PM), FR (1PM)

T8.3: Software-based "deep" analysis

1. Identify relevant data sources2. Access data by inventory from WP6 3. SNA and semantic analysis of data considering dynamic

(time dimension) 4. Characterize by structural and process patterns5. Adapt and verify data format (semantic, structural,

dynamic)6. Evaluate and interpret considering indicators from WP4 R: UDE (2PM)C: UMA (2PM), CICE (1PM), FR (1PM), RICYT (1PM)

T8.4: Best practices and recommendations

Characterize best practices in the evolution of scientific communities to support:- strategic decisions around scientific innovations- right balance between informal and formal science - right sense of with whom one should share

knowledge at which phase of research or growth of the field

R: UDE (2PM)C: FR (2PM), RICYT (2PM), CICE (1PM), MTA (1PM)

Deliverables

- 8.1 Report on data collection and specification of needs for the construction of mobility indicators (RP:UDE,RV:CICE, C: all inv. / M8)

- 8.2 Preliminary report - taxonomy and examples (RP: UDE, RV: RICYT, C: all inv. / M30)

- 8.3 Analysis report (RP: UDE, RV: FR, C: all inv. / M26)

- 8.4 Guideline for decision makers for knowledge sharing (RP: UDE, RV: CICE, C: all inv. / M30)

WP dependencies

Task 4.2Instantiate into indicators the

general objectives of task 4.1 for the

selected case studie

Task 4.4Implement the

indicators within the generated modules in SISOB system

Task 2.3Define Conceptual

Model

Task 2.4Identification of data

sources, indices, representations and

tools

Task 6.2Semantic evaluation

and filtering

Task 6.4Data transformation

and structural modelling for SNA

Task 6.5Software platform

Task6.6Data analysis and

evaluation

Task 8.1Taxonomy of indicators for

knowledge flow and sharing

Task 8.2Identification and

first characterisation of example

communities

Task 8.3Software-based “deep” analysis

Task 8.4Best practices and recommendations for the evolution of

scientific communities

Task 2.2Define requirements

Task 5.2Design generic

visual mechanisms and build a

taxonomy with them

Task 3.1Build a standard

format to interchange

information within the project