To address rising cost and risk pressures, improve innovation and focus on core competencies, many science-based organizations are moving collaborative relationships beyond traditional boundaries and creating flexible networks of researchers. Some are in-house; others are with industry and academic partners, research institutes, consortia and contract research organizations (CROs). Over time, these externalized networks are increasing in size and complexity. Many combine numerous partners with diverse objectives involving single or multiple research projects that, in some cases, can tie up more than 50% of a commissioning organizations IT budget. Internet-based collaboration solutions such as email, SharePoint, VPN, Citrix and other data exchange mechanisms often introduce security challenges, incompatible data formats and the need to prepare and curate files manually. These difficulties can reduce productivity, decrease data quality, lengthen project timelines and increase failures. <\/p>\n
With these challenges in mind, combined with an enormous pressure to reduce their informatics footprint, organizations are turning to cloud-based solutions as a scalable, secure, state-of-the-art environment for research collaboration. With cloud adoption significantly enhancing collaborative projects, increasing operational agility and lowering total cost of ownership, cloud computing has become a valuable and viable solution today; however, organizations are often uncertain about the best way to evaluate, select and implement a cloud collaboration platform. <\/p>\n
To learn more about cloud-based research informatics and the benefits and challenges of adopting this technology, we spoke to Ton van Daelen, senior product director for collaborative sciences at Dassault Systmes BIOVIA. <\/p>\n
What data challenges do scientific organizations face in the modern, collaboration-driven world? <\/p>\n
Science-based organizations across diverse industry sectors (e.g., life sciences, consumer packaged goods, energy\/process\/utilities and industrial equipment) are radically reinventing themselves by embracing globalization, innovating with outside partners and focusing on operational excellence. Externalized projects introduce substantial challenges that are typically not encountered in internal projects. How do you set up an IT infrastructure that supports external parties? How do you communicate effectively with partners in different geographies and time zones? How do you securely share data and reduce the amount of time required to clean up and standardize collaborator data? How do you secure the IP of different parties and share project data in real time? <\/p>\n
Faced with these challenges, external projects often do not meet their original expectations, or worse, they fail completely. This is a huge risk factor as organizations rely more than ever on external partners to advance discovery initiatives. External collaborations require internal staff to radically change the way they access, manage and interpret research data, which can disrupt established workflows and require significant retraining. As this is not often feasible, access to collaboration data tends to be managed by a few gatekeepers, further reducing collaboration effectiveness. <\/p>\n
Data exchange with external partners is often manual and therefore prone to error, and all collaborations bring their own sets of data representations. Highly-paid scientists can spend up to 50 percent of their time manually processing and checking collaborator data. Errors can go unnoticed for weeks or months, resulting in significant project delays and IP risk. Reliable, automated procedures for tech transfer, data standardization and data transfer to legacy databases are expensive to implement and maintain and often require highly skilled software developers. <\/p>\n
What are the key benefits of cloud-based data management? How much of an impact can implementing this kind of system have? <\/p>\n
Cloud-based data management provides web and mobile-accessible applications for uploading, processing, storing, searching and analyzing structured and unstructured scientific records. Most importantly, the cloud delivers improved agility and lowers total cost of ownership (TCO) for organizations tasked with responding quickly to changing business needs while also lowering costs. Being in the cloud means you can set up a robust collaboration systemaccessible anywhere, anytimewith minimal IT support quickly and easily, and you only pay for what you need and use. <\/p>\n
In a cloud environment: <\/p>\n
Scientists can rapidly access and share research data including experiments, chemical structures, assays and other test results which significantly accelerates informed decisions based on the most complete and current information available. No time is lost on data transformation and interpretation. Data originators ensure that their data resides in the system as intended. The ability to annotate data provides context for other scientists using the information. <\/p>\n
Research managers continuously gain visibility into projects along with the ability to understand the latest results across all partnering organizations. As a result, they can better schedule the project tasks to maximize the process efficiency. Data access is secure and controlled and not reliant on the partner, helping to protect IP and the organizations investment in collaborations. <\/p>\n
IT organizations benefit from low IT cost of ownership resulting from the pay-as-you-go model of a hosted system. As collaboration networks evolve, the cloud system makes it easy for sponsoring organizations to quickly spin up and spin down partner engagements with the data they provide securely partitioned in the system. A highly configurable cloud system can support the easy definition of sites, projects and user roles, as well as the definition of data access and upload permissions for each of these. A cloud system certified to the ISO-27001 industry standard helps to ensure that confidential and proprietary information remains secure in the cloud. <\/p>\n
Cloud-based technologies are completely new to many people in science. How can scientific organizations be confident that they are selecting a solution that will meet their requirements? <\/p>\n
The cloud is now a proven solution used by many companies of all sizes and in many industries. Solutions like Salesforce.com, Workday, SAP SuccessFactors and Concur Technologies have been handling confidential information in the cloud for millions of users over many years. The best way to deploy a cloud solution (and deal with cloud skeptics) is to create a strong cloud vision and build a compelling cloud strategy that aligns with organizational needs. Simplify governance issues by assessing impactful use cases, current workflows\/processes, security risks and the highest priority functions to be moved to the cloud. Additionally, carefully consider the cultural changes and new policies that will be needed to streamline governance and align employees with the new cloud environment. Your cloud provider should be able to guide you through the process of provisioning and managing users and groups across the cloud apps your organization needs. This includes the process of creating and managing groups, controlling who has access to apps, enabling self-signup, managing password requirements and the many other business process changes that come with a move to the cloud. <\/p>\n
A few figures: <\/p>\n
Worldwide spending on public cloud services will grow at a 19.4 percent compound annual growth rate (CAGR) from nearly $70B in 2015 to more than $141B in 2019.1 <\/p>\n
+171,000 paid attendees from 83 countries attended Dreamforce in 2016.2 <\/p>\n
Morgan Stanley predicts Microsoft cloud products will be 30 percent of revenue by 2018.1 <\/p>\n
By 2020, penetration of software as a service (SaaS) versus traditional software deployment will be over 25 percent. Packaged software will shrink to 10percent of new enterprise installations.1 <\/p>\n
Implementing a cloud-based data management system is a big step for any organization. How can they effectively measure the success of adopting this technology once it is all up and running? <\/p>\n<\/p>\n
Organizations can expect a number of benefits to materialize over time: time and cost savings through data exchange and communication automation, a lowered TCO resulting from infrastructure in the cloud, shorter project timelines and improved efficiency with cloud agilitymaking it possible for organizations to adapt to changing business environments by spinning collaborations up and down quickly in the cloud. Key Performance Indicators (KPIs) our customers typically use are 1) scientist productivity, 2) IT spending per user\/application, 3) time spent implementing new software applications and 4) average time to start up, run and close down a project. <\/p>\n
References <\/p>\n
1. Louis Columbus, Roundup of Cloud Computing Forecasts and Market Estimates, 2016 <\/p>\n
https:\/\/www.forbes.com\/sites\/louiscolumbus\/2016\/03\/13\/roundup-of-cloud-computing-forecasts-and-market-estimates-2016\/#192bad382187<\/a> <\/p>\n 2. https:\/\/www.salesforce.com\/blog\/2016\/10\/dreamforce-16-by-the-numbers.html<\/a> <\/p>\n <\/p>\n Continued here:<\/p>\n Cloud-based Research Informatics: Improving Collaboration, Increasing Agility and Reducing Operating Costs - Technology Networks<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" To address rising cost and risk pressures, improve innovation and focus on core competencies, many science-based organizations are moving collaborative relationships beyond traditional boundaries and creating flexible networks of researchers. Some are in-house; others are with industry and academic partners, research institutes, consortia and contract research organizations (CROs) Continue reading