## 1 Introduction  
Data obtained from vulnerable populations, such as babies, children, and young people, is precious. When seeking to optimise the design and delivery of paediatrictrials, data considerations are paramount. At present, the lack of harmonisation and standardisation concerning the collection and representation of data elements in paediatric clinical trials is a significant challenge. conect4 children (c4c) is a six-year project established in 2018 and funded by the Innovative Medicines Initiative (IMI2) to address the multitude of barriers facing the development and delivery of effective paediatric clinical trials. This will include a trial feasibility, conducted through a single point of contact, expert advice, an educational academy for clinical trial personnel and data harmonisation services [1; 2; 3]. Clinical trials that contribute to drug registration are tightly regulated. Regulation includes the use of explicit data structures and controlled vocabularies. At present, many electronic case report form (eCRF) specifications are created manually with data structures and controlled vocabularies that are unique to each clinical trial, including those in paediatrics. That is, each trial (or family of trials within a sponsor's portfolio) has an implicit model, is designed for an ad hoc purpose, and is limited by how the model is captured (usually in a flat file or spreadsheet). There is presently a limited culture and practice of standardising and reusing clinical data specifications between clinical trials, and no vendor neutral specification for automated eCRF generation. The Clinical Data Interchange Standards Consortium (CDISC) standards--in particular, its Therapeutic Area User Guides (TAUG)--support access to data by specifying how data standards are expressed. The CDISC also encourages convergence in data standards across pharma clinical trials [4]. There is presently limited connection between the CDISC standards and those used for routinely collected (real-world) electronic health records, although the HL7 VULCAN project is starting to bridge between its Fast Healthcare Interoperability Resources (FHIR) standard suite and clinical research [5]. However, there is a growing recognition that clinical trial data should be reused for subsequent research [6], as exemplified by the Yale Open Data (YODA) initiative supported at Yale University by Janssen Pharmaceuticals [7]. Eligibility criteria for clinical trials are already being mapped into a computable form for execution as queries on hospital electronic health records (EHR) systems that requires reformulating those criteria as data items and structures that are realistic to find in EHRs [8; 9]. More recently, vendor neutral specifications for transferring hospital EHR data to electronic data capture systems (EDC) for pharma-sponsored trials has been demonstrated at multiple European sites [10]. It is therefore important to find ways to maximise the consistency and reusability of clinical trial data. The c4c project is addressing this issue by developing and supporting a standardised paediatric data dictionary, the Cross Cutting Paediatric Data Dictionary (CCPDD). This provides guidance on how to represent data items that are disease agnostic (cross cutting) and commonly collected during paediatric studies. Use of the CCPDD is expected to result in more harmonised, interoperable data that has a greater potential to be shared and re-used. The CCPDD has an explicit model and is designed to be used across multiple trials and sponsors. The c4c CCPDD was initially developed in Microsoft Excel and was successfully used to manually create case report forms (CRFs) for the non-industry c4c Proof of Viability (PoV) studies. However, the Excel format of the data dictionary resulted in several challenges due to the 'flat' structure of the worksheet and its limited ability to quality assure the content entered.